diff --git a/.github/workflows/api-tests.yml b/.github/workflows/api-tests.yml index f08befefb8..a5a5071fae 100644 --- a/.github/workflows/api-tests.yml +++ b/.github/workflows/api-tests.yml @@ -47,15 +47,17 @@ jobs: - name: Run Unit tests run: | uv run --project api bash dev/pytest/pytest_unit_tests.sh + + - name: Coverage Summary + run: | + set -x # Extract coverage percentage and create a summary TOTAL_COVERAGE=$(python -c 'import json; print(json.load(open("coverage.json"))["totals"]["percent_covered_display"])') # Create a detailed coverage summary echo "### Test Coverage Summary :test_tube:" >> $GITHUB_STEP_SUMMARY echo "Total Coverage: ${TOTAL_COVERAGE}%" >> $GITHUB_STEP_SUMMARY - echo "\`\`\`" >> $GITHUB_STEP_SUMMARY - uv run --project api coverage report >> $GITHUB_STEP_SUMMARY - echo "\`\`\`" >> $GITHUB_STEP_SUMMARY + uv run --project api coverage report --format=markdown >> $GITHUB_STEP_SUMMARY - name: Run dify config tests run: uv run --project api dev/pytest/pytest_config_tests.py @@ -83,9 +85,15 @@ jobs: compose-file: | docker/docker-compose.middleware.yaml services: | + db + redis sandbox ssrf_proxy + - name: setup test config + run: | + cp api/tests/integration_tests/.env.example api/tests/integration_tests/.env + - name: Run Workflow run: uv run --project api bash dev/pytest/pytest_workflow.sh diff --git a/.github/workflows/vdb-tests.yml b/.github/workflows/vdb-tests.yml index 7d0a873ebd..912267094b 100644 --- a/.github/workflows/vdb-tests.yml +++ b/.github/workflows/vdb-tests.yml @@ -84,6 +84,12 @@ jobs: elasticsearch oceanbase + - name: setup test config + run: | + echo $(pwd) + ls -lah . + cp api/tests/integration_tests/.env.example api/tests/integration_tests/.env + - name: Check VDB Ready (TiDB) run: uv run --project api python api/tests/integration_tests/vdb/tidb_vector/check_tiflash_ready.py diff --git a/.gitignore b/.gitignore index 4c938b7682..dd4673a3d2 100644 --- a/.gitignore +++ b/.gitignore @@ -179,6 +179,7 @@ docker/volumes/pgvecto_rs/data/* docker/volumes/couchbase/* docker/volumes/oceanbase/* docker/volumes/plugin_daemon/* +docker/volumes/matrixone/* !docker/volumes/oceanbase/init.d docker/nginx/conf.d/default.conf @@ -213,3 +214,4 @@ mise.toml # AI Assistant .roo/ +api/.env.backup diff --git a/README.md b/README.md index ca09adec08..1dc7e2dd98 100644 --- a/README.md +++ b/README.md @@ -226,6 +226,15 @@ Deploy Dify to AWS with [CDK](https://aws.amazon.com/cdk/) - [AWS CDK by @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Using Alibaba Cloud Computing Nest + +Quickly deploy Dify to Alibaba cloud with [Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Using Alibaba Cloud Data Management + +One-Click deploy Dify to Alibaba Cloud with [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Contributing For those who'd like to contribute code, see our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). diff --git a/README_AR.md b/README_AR.md index df288fd33c..d93bca8646 100644 --- a/README_AR.md +++ b/README_AR.md @@ -209,6 +209,14 @@ docker compose up -d - [AWS CDK بواسطة @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### استخدام Alibaba Cloud للنشر + [بسرعة نشر Dify إلى سحابة علي بابا مع عش الحوسبة السحابية علي بابا](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### استخدام Alibaba Cloud Data Management للنشر + +انشر ​​Dify على علي بابا كلاود بنقرة واحدة باستخدام [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## المساهمة لأولئك الذين يرغبون في المساهمة، انظر إلى [دليل المساهمة](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) لدينا. diff --git a/README_BN.md b/README_BN.md index 4a5b5f3928..3efee3684d 100644 --- a/README_BN.md +++ b/README_BN.md @@ -225,6 +225,15 @@ GitHub-এ ডিফাইকে স্টার দিয়ে রাখুন - [AWS CDK by @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud ব্যবহার করে ডিপ্লয় + + [Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management ব্যবহার করে ডিপ্লয় + + [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Contributing যারা কোড অবদান রাখতে চান, তাদের জন্য আমাদের [অবদান নির্দেশিকা] দেখুন (https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)। diff --git a/README_CN.md b/README_CN.md index ba7ee0006d..21e27429ec 100644 --- a/README_CN.md +++ b/README_CN.md @@ -221,6 +221,15 @@ docker compose up -d ##### AWS - [AWS CDK by @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### 使用 阿里云计算巢 部署 + +使用 [阿里云计算巢](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) 将 Dify 一键部署到 阿里云 + +#### 使用 阿里云数据管理DMS 部署 + +使用 [阿里云数据管理DMS](https://help.aliyun.com/zh/dms/dify-in-invitational-preview) 将 Dify 一键部署到 阿里云 + + ## Star History [![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date) diff --git a/README_DE.md b/README_DE.md index f6023a3935..20c313035e 100644 --- a/README_DE.md +++ b/README_DE.md @@ -221,6 +221,15 @@ Bereitstellung von Dify auf AWS mit [CDK](https://aws.amazon.com/cdk/) ##### AWS - [AWS CDK by @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +Ein-Klick-Bereitstellung von Dify in der Alibaba Cloud mit [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Contributing Falls Sie Code beitragen möchten, lesen Sie bitte unseren [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). Gleichzeitig bitten wir Sie, Dify zu unterstützen, indem Sie es in den sozialen Medien teilen und auf Veranstaltungen und Konferenzen präsentieren. diff --git a/README_ES.md b/README_ES.md index 12f2ce8c11..e4b7df6686 100644 --- a/README_ES.md +++ b/README_ES.md @@ -221,6 +221,15 @@ Despliegue Dify en AWS usando [CDK](https://aws.amazon.com/cdk/) ##### AWS - [AWS CDK por @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +Despliega Dify en Alibaba Cloud con un solo clic con [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Contribuir Para aquellos que deseen contribuir con código, consulten nuestra [Guía de contribución](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). diff --git a/README_FR.md b/README_FR.md index b106615b31..8fd17fb7c3 100644 --- a/README_FR.md +++ b/README_FR.md @@ -219,6 +219,15 @@ Déployez Dify sur AWS en utilisant [CDK](https://aws.amazon.com/cdk/) ##### AWS - [AWS CDK par @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +Déployez Dify en un clic sur Alibaba Cloud avec [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Contribuer Pour ceux qui souhaitent contribuer du code, consultez notre [Guide de contribution](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). diff --git a/README_JA.md b/README_JA.md index 26703f3958..a3ee81e1f2 100644 --- a/README_JA.md +++ b/README_JA.md @@ -155,7 +155,7 @@ DifyはオープンソースのLLMアプリケーション開発プラットフ [こちら](https://dify.ai)のDify Cloudサービスを利用して、セットアップ不要で試すことができます。サンドボックスプランには、200回のGPT-4呼び出しが無料で含まれています。 - **Dify Community Editionのセルフホスティング
** -この[スタートガイド](#quick-start)を使用して、ローカル環境でDifyを簡単に実行できます。 +この[スタートガイド](#クイックスタート)を使用して、ローカル環境でDifyを簡単に実行できます。 詳しくは[ドキュメント](https://docs.dify.ai)をご覧ください。 - **企業/組織向けのDify
** @@ -220,6 +220,13 @@ docker compose up -d ##### AWS - [@KevinZhaoによるAWS CDK](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management +[Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) を利用して、DifyをAlibaba Cloudへワンクリックでデプロイできます + + ## 貢献 コードに貢献したい方は、[Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)を参照してください。 diff --git a/README_KL.md b/README_KL.md index ea91baa5aa..3e5ab1a74f 100644 --- a/README_KL.md +++ b/README_KL.md @@ -219,6 +219,15 @@ wa'logh nIqHom neH ghun deployment toy'wI' [CDK](https://aws.amazon.com/cdk/) lo ##### AWS - [AWS CDK qachlot @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +[Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Contributing For those who'd like to contribute code, see our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). diff --git a/README_KR.md b/README_KR.md index 89301e8b2c..3c504900e1 100644 --- a/README_KR.md +++ b/README_KR.md @@ -213,6 +213,15 @@ Dify를 Kubernetes에 배포하고 프리미엄 스케일링 설정을 구성했 ##### AWS - [KevinZhao의 AWS CDK](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +[Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/)를 통해 원클릭으로 Dify를 Alibaba Cloud에 배포할 수 있습니다 + + ## 기여 코드에 기여하고 싶은 분들은 [기여 가이드](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)를 참조하세요. diff --git a/README_PT.md b/README_PT.md index 157772d528..fb5f3662ae 100644 --- a/README_PT.md +++ b/README_PT.md @@ -218,6 +218,15 @@ Implante o Dify na AWS usando [CDK](https://aws.amazon.com/cdk/) ##### AWS - [AWS CDK por @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +Implante o Dify na Alibaba Cloud com um clique usando o [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Contribuindo Para aqueles que desejam contribuir com código, veja nosso [Guia de Contribuição](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). diff --git a/README_SI.md b/README_SI.md index 14de1ea792..647069a220 100644 --- a/README_SI.md +++ b/README_SI.md @@ -219,6 +219,15 @@ Uvedite Dify v AWS z uporabo [CDK](https://aws.amazon.com/cdk/) ##### AWS - [AWS CDK by @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +Z enim klikom namestite Dify na Alibaba Cloud z [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Prispevam Za tiste, ki bi radi prispevali kodo, si oglejte naš vodnik za prispevke . Hkrati vas prosimo, da podprete Dify tako, da ga delite na družbenih medijih ter na dogodkih in konferencah. diff --git a/README_TR.md b/README_TR.md index 563a05af3c..f52335646a 100644 --- a/README_TR.md +++ b/README_TR.md @@ -212,6 +212,15 @@ Dify'ı bulut platformuna tek tıklamayla dağıtın [terraform](https://www.ter ##### AWS - [AWS CDK tarafından @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +[Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) kullanarak Dify'ı tek tıkla Alibaba Cloud'a dağıtın + + ## Katkıda Bulunma Kod katkısında bulunmak isteyenler için [Katkı Kılavuzumuza](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) bakabilirsiniz. diff --git a/README_TW.md b/README_TW.md index f4a76ac109..71082ff893 100644 --- a/README_TW.md +++ b/README_TW.md @@ -224,6 +224,15 @@ Dify 的所有功能都提供相應的 API，因此您可以輕鬆地將 Dify - [由 @KevinZhao 提供的 AWS CDK](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) +#### 使用 阿里云计算巢進行部署 + +[阿里云](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### 使用 阿里雲數據管理DMS 進行部署 + +透過 [阿里雲數據管理DMS](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/)，一鍵將 Dify 部署至阿里雲 + + ## 貢獻 對於想要貢獻程式碼的開發者，請參閱我們的[貢獻指南](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)。 diff --git a/README_VI.md b/README_VI.md index 4e1e05cbf3..58d8434fff 100644 --- a/README_VI.md +++ b/README_VI.md @@ -214,6 +214,16 @@ Triển khai Dify trên AWS bằng [CDK](https://aws.amazon.com/cdk/) ##### AWS - [AWS CDK bởi @KevinZhao](https://github.com/aws-samples/solution-for-deploying-dify-on-aws) + +#### Alibaba Cloud + +[Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88) + +#### Alibaba Cloud Data Management + +Triển khai Dify lên Alibaba Cloud chỉ với một cú nhấp chuột bằng [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/) + + ## Đóng góp Đối với những người muốn đóng góp mã, xem [Hướng dẫn Đóng góp](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) của chúng tôi. diff --git a/api/.env.example b/api/.env.example index 7878308588..baa9c382c8 100644 --- a/api/.env.example +++ b/api/.env.example @@ -137,7 +137,7 @@ WEB_API_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,* CONSOLE_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,* # Vector database configuration -# support: weaviate, qdrant, milvus, myscale, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector, couchbase, vikingdb, upstash, lindorm, oceanbase, opengauss, tablestore +# support: weaviate, qdrant, milvus, myscale, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector, couchbase, vikingdb, upstash, lindorm, oceanbase, opengauss, tablestore, matrixone VECTOR_STORE=weaviate # Weaviate configuration @@ -294,6 +294,13 @@ VIKINGDB_SCHEMA=http VIKINGDB_CONNECTION_TIMEOUT=30 VIKINGDB_SOCKET_TIMEOUT=30 +# Matrixone configration +MATRIXONE_HOST=127.0.0.1 +MATRIXONE_PORT=6001 +MATRIXONE_USER=dump +MATRIXONE_PASSWORD=111 +MATRIXONE_DATABASE=dify + # Lindorm configuration LINDORM_URL=http://ld-*******************-proxy-search-pub.lindorm.aliyuncs.com:30070 LINDORM_USERNAME=admin @@ -332,9 +339,11 @@ PROMPT_GENERATION_MAX_TOKENS=512 CODE_GENERATION_MAX_TOKENS=1024 PLUGIN_BASED_TOKEN_COUNTING_ENABLED=false -# Mail configuration, support: resend, smtp +# Mail configuration, support: resend, smtp, sendgrid MAIL_TYPE= +# If using SendGrid, use the 'from' field for authentication if necessary. MAIL_DEFAULT_SEND_FROM=no-reply +# resend configuration RESEND_API_KEY= RESEND_API_URL=https://api.resend.com # smtp configuration @@ -344,7 +353,8 @@ SMTP_USERNAME=123 SMTP_PASSWORD=abc SMTP_USE_TLS=true SMTP_OPPORTUNISTIC_TLS=false - +# Sendgid configuration +SENDGRID_API_KEY= # Sentry configuration SENTRY_DSN= diff --git a/api/.ruff.toml b/api/.ruff.toml index facb0d5419..0169613bf8 100644 --- a/api/.ruff.toml +++ b/api/.ruff.toml @@ -1,6 +1,4 @@ -exclude = [ - "migrations/*", -] +exclude = ["migrations/*"] line-length = 120 [format] @@ -9,14 +7,14 @@ quote-style = "double" [lint] preview = false select = [ - "B", # flake8-bugbear rules - "C4", # flake8-comprehensions - "E", # pycodestyle E rules - "F", # pyflakes rules - "FURB", # refurb rules - "I", # isort rules - "N", # pep8-naming - "PT", # flake8-pytest-style rules + "B", # flake8-bugbear rules + "C4", # flake8-comprehensions + "E", # pycodestyle E rules + "F", # pyflakes rules + "FURB", # refurb rules + "I", # isort rules + "N", # pep8-naming + "PT", # flake8-pytest-style rules "PLC0208", # iteration-over-set "PLC0414", # useless-import-alias "PLE0604", # invalid-all-object @@ -24,19 +22,19 @@ select = [ "PLR0402", # manual-from-import "PLR1711", # useless-return "PLR1714", # repeated-equality-comparison - "RUF013", # implicit-optional - "RUF019", # unnecessary-key-check - "RUF100", # unused-noqa - "RUF101", # redirected-noqa - "RUF200", # invalid-pyproject-toml - "RUF022", # unsorted-dunder-all - "S506", # unsafe-yaml-load - "SIM", # flake8-simplify rules - "TRY400", # error-instead-of-exception - "TRY401", # verbose-log-message - "UP", # pyupgrade rules - "W191", # tab-indentation - "W605", # invalid-escape-sequence + "RUF013", # implicit-optional + "RUF019", # unnecessary-key-check + "RUF100", # unused-noqa + "RUF101", # redirected-noqa + "RUF200", # invalid-pyproject-toml + "RUF022", # unsorted-dunder-all + "S506", # unsafe-yaml-load + "SIM", # flake8-simplify rules + "TRY400", # error-instead-of-exception + "TRY401", # verbose-log-message + "UP", # pyupgrade rules + "W191", # tab-indentation + "W605", # invalid-escape-sequence # security related linting rules # RCE proctection (sort of) "S102", # exec-builtin, disallow use of `exec` @@ -47,36 +45,37 @@ select = [ ] ignore = [ - "E402", # module-import-not-at-top-of-file - "E711", # none-comparison - "E712", # true-false-comparison - "E721", # type-comparison - "E722", # bare-except - "F821", # undefined-name - "F841", # unused-variable + "E402", # module-import-not-at-top-of-file + "E711", # none-comparison + "E712", # true-false-comparison + "E721", # type-comparison + "E722", # bare-except + "F821", # undefined-name + "F841", # unused-variable "FURB113", # repeated-append "FURB152", # math-constant - "UP007", # non-pep604-annotation - "UP032", # f-string - "UP045", # non-pep604-annotation-optional - "B005", # strip-with-multi-characters - "B006", # mutable-argument-default - "B007", # unused-loop-control-variable - "B026", # star-arg-unpacking-after-keyword-arg - "B903", # class-as-data-structure - "B904", # raise-without-from-inside-except - "B905", # zip-without-explicit-strict - "N806", # non-lowercase-variable-in-function - "N815", # mixed-case-variable-in-class-scope - "PT011", # pytest-raises-too-broad - "SIM102", # collapsible-if - "SIM103", # needless-bool - "SIM105", # suppressible-exception - "SIM107", # return-in-try-except-finally - "SIM108", # if-else-block-instead-of-if-exp - "SIM113", # enumerate-for-loop - "SIM117", # multiple-with-statements - "SIM210", # if-expr-with-true-false + "UP007", # non-pep604-annotation + "UP032", # f-string + "UP045", # non-pep604-annotation-optional + "B005", # strip-with-multi-characters + "B006", # mutable-argument-default + "B007", # unused-loop-control-variable + "B026", # star-arg-unpacking-after-keyword-arg + "B903", # class-as-data-structure + "B904", # raise-without-from-inside-except + "B905", # zip-without-explicit-strict + "N806", # non-lowercase-variable-in-function + "N815", # mixed-case-variable-in-class-scope + "PT011", # pytest-raises-too-broad + "SIM102", # collapsible-if + "SIM103", # needless-bool + "SIM105", # suppressible-exception + "SIM107", # return-in-try-except-finally + "SIM108", # if-else-block-instead-of-if-exp + "SIM113", # enumerate-for-loop + "SIM117", # multiple-with-statements + "SIM210", # if-expr-with-true-false + "UP038", # deprecated and not recommended by Ruff, https://docs.astral.sh/ruff/rules/non-pep604-isinstance/ ] [lint.per-file-ignores] diff --git a/api/commands.py b/api/commands.py index 0a6cc61a68..86769847c1 100644 --- a/api/commands.py +++ b/api/commands.py @@ -281,6 +281,7 @@ def migrate_knowledge_vector_database(): VectorType.ELASTICSEARCH, VectorType.OPENGAUSS, VectorType.TABLESTORE, + VectorType.MATRIXONE, } lower_collection_vector_types = { VectorType.ANALYTICDB, diff --git a/api/configs/app_config.py b/api/configs/app_config.py index 3a3ad35ee7..20f8c40427 100644 --- a/api/configs/app_config.py +++ b/api/configs/app_config.py @@ -1,8 +1,11 @@ import logging +from pathlib import Path from typing import Any from pydantic.fields import FieldInfo -from pydantic_settings import BaseSettings, PydanticBaseSettingsSource, SettingsConfigDict +from pydantic_settings import BaseSettings, PydanticBaseSettingsSource, SettingsConfigDict, TomlConfigSettingsSource + +from libs.file_utils import search_file_upwards from .deploy import DeploymentConfig from .enterprise import EnterpriseFeatureConfig @@ -99,4 +102,12 @@ class DifyConfig( RemoteSettingsSourceFactory(settings_cls), dotenv_settings, file_secret_settings, + TomlConfigSettingsSource( + settings_cls=settings_cls, + toml_file=search_file_upwards( + base_dir_path=Path(__file__).parent, + target_file_name="pyproject.toml", + max_search_parent_depth=2, + ), + ), ) diff --git a/api/configs/feature/__init__.py b/api/configs/feature/__init__.py index a3da5c1b49..df15b92c35 100644 --- a/api/configs/feature/__init__.py +++ b/api/configs/feature/__init__.py @@ -609,7 +609,7 @@ class MailConfig(BaseSettings): """ MAIL_TYPE: Optional[str] = Field( - description="Email service provider type ('smtp' or 'resend'), default to None.", + description="Email service provider type ('smtp' or 'resend' or 'sendGrid), default to None.", default=None, ) @@ -663,6 +663,11 @@ class MailConfig(BaseSettings): default=50, ) + SENDGRID_API_KEY: Optional[str] = Field( + description="API key for SendGrid service", + default=None, + ) + class RagEtlConfig(BaseSettings): """ diff --git a/api/configs/middleware/__init__.py b/api/configs/middleware/__init__.py index 2dcf1710b0..427602676f 100644 --- a/api/configs/middleware/__init__.py +++ b/api/configs/middleware/__init__.py @@ -24,6 +24,7 @@ from .vdb.couchbase_config import CouchbaseConfig from .vdb.elasticsearch_config import ElasticsearchConfig from .vdb.huawei_cloud_config import HuaweiCloudConfig from .vdb.lindorm_config import LindormConfig +from .vdb.matrixone_config import MatrixoneConfig from .vdb.milvus_config import MilvusConfig from .vdb.myscale_config import MyScaleConfig from .vdb.oceanbase_config import OceanBaseVectorConfig @@ -222,6 +223,10 @@ class CeleryConfig(DatabaseConfig): default=None, ) + CELERY_SENTINEL_PASSWORD: Optional[str] = Field( + description="Password of the Redis Sentinel master.", + default=None, + ) CELERY_SENTINEL_SOCKET_TIMEOUT: Optional[PositiveFloat] = Field( description="Timeout for Redis Sentinel socket operations in seconds.", default=0.1, @@ -323,5 +328,6 @@ class MiddlewareConfig( OpenGaussConfig, TableStoreConfig, DatasetQueueMonitorConfig, + MatrixoneConfig, ): pass diff --git a/api/configs/middleware/vdb/matrixone_config.py b/api/configs/middleware/vdb/matrixone_config.py new file mode 100644 index 0000000000..9400612d8e --- /dev/null +++ b/api/configs/middleware/vdb/matrixone_config.py @@ -0,0 +1,14 @@ +from pydantic import BaseModel, Field + + +class MatrixoneConfig(BaseModel): + """Matrixone vector database configuration.""" + + MATRIXONE_HOST: str = Field(default="localhost", description="Host address of the Matrixone server") + MATRIXONE_PORT: int = Field(default=6001, description="Port number of the Matrixone server") + MATRIXONE_USER: str = Field(default="dump", description="Username for authenticating with Matrixone") + MATRIXONE_PASSWORD: str = Field(default="111", description="Password for authenticating with Matrixone") + MATRIXONE_DATABASE: str = Field(default="dify", description="Name of the Matrixone database to connect to") + MATRIXONE_METRIC: str = Field( + default="l2", description="Distance metric type for vector similarity search (cosine or l2)" + ) diff --git a/api/configs/packaging/__init__.py b/api/configs/packaging/__init__.py index 0107df22c5..f511e20e6b 100644 --- a/api/configs/packaging/__init__.py +++ b/api/configs/packaging/__init__.py @@ -1,17 +1,13 @@ from pydantic import Field -from pydantic_settings import BaseSettings +from configs.packaging.pyproject import PyProjectConfig, PyProjectTomlConfig -class PackagingInfo(BaseSettings): + +class PackagingInfo(PyProjectTomlConfig): """ Packaging build information """ - CURRENT_VERSION: str = Field( - description="Dify version", - default="1.4.3", - ) - COMMIT_SHA: str = Field( description="SHA-1 checksum of the git commit used to build the app", default="", diff --git a/api/configs/packaging/pyproject.py b/api/configs/packaging/pyproject.py new file mode 100644 index 0000000000..90b1ecba06 --- /dev/null +++ b/api/configs/packaging/pyproject.py @@ -0,0 +1,17 @@ +from pydantic import BaseModel, Field +from pydantic_settings import BaseSettings + + +class PyProjectConfig(BaseModel): + version: str = Field(description="Dify version", default="") + + +class PyProjectTomlConfig(BaseSettings): + """ + configs in api/pyproject.toml + """ + + project: PyProjectConfig = Field( + description="configs in the project section of pyproject.toml", + default=PyProjectConfig(), + ) diff --git a/api/controllers/console/__init__.py b/api/controllers/console/__init__.py index a974c63e35..dbdcdc46ce 100644 --- a/api/controllers/console/__init__.py +++ b/api/controllers/console/__init__.py @@ -63,6 +63,7 @@ from .app import ( statistic, workflow, workflow_app_log, + workflow_draft_variable, workflow_run, workflow_statistic, ) diff --git a/api/controllers/console/admin.py b/api/controllers/console/admin.py index 8cb7ad9f5b..f5257fae79 100644 --- a/api/controllers/console/admin.py +++ b/api/controllers/console/admin.py @@ -56,8 +56,7 @@ class InsertExploreAppListApi(Resource): parser.add_argument("position", type=int, required=True, nullable=False, location="json") args = parser.parse_args() - with Session(db.engine) as session: - app = session.execute(select(App).filter(App.id == args["app_id"])).scalar_one_or_none() + app = db.session.execute(select(App).filter(App.id == args["app_id"])).scalar_one_or_none() if not app: raise NotFound(f"App '{args['app_id']}' is not found") @@ -78,38 +77,38 @@ class InsertExploreAppListApi(Resource): select(RecommendedApp).filter(RecommendedApp.app_id == args["app_id"]) ).scalar_one_or_none() - if not recommended_app: - recommended_app = RecommendedApp( - app_id=app.id, - description=desc, - copyright=copy_right, - privacy_policy=privacy_policy, - custom_disclaimer=custom_disclaimer, - language=args["language"], - category=args["category"], - position=args["position"], - ) - - db.session.add(recommended_app) - - app.is_public = True - db.session.commit() - - return {"result": "success"}, 201 - else: - recommended_app.description = desc - recommended_app.copyright = copy_right - recommended_app.privacy_policy = privacy_policy - recommended_app.custom_disclaimer = custom_disclaimer - recommended_app.language = args["language"] - recommended_app.category = args["category"] - recommended_app.position = args["position"] + if not recommended_app: + recommended_app = RecommendedApp( + app_id=app.id, + description=desc, + copyright=copy_right, + privacy_policy=privacy_policy, + custom_disclaimer=custom_disclaimer, + language=args["language"], + category=args["category"], + position=args["position"], + ) + + db.session.add(recommended_app) + + app.is_public = True + db.session.commit() + + return {"result": "success"}, 201 + else: + recommended_app.description = desc + recommended_app.copyright = copy_right + recommended_app.privacy_policy = privacy_policy + recommended_app.custom_disclaimer = custom_disclaimer + recommended_app.language = args["language"] + recommended_app.category = args["category"] + recommended_app.position = args["position"] - app.is_public = True + app.is_public = True - db.session.commit() + db.session.commit() - return {"result": "success"}, 200 + return {"result": "success"}, 200 class InsertExploreAppApi(Resource): diff --git a/api/controllers/console/app/app_import.py b/api/controllers/console/app/app_import.py index 5dc6515ce0..9ffb94e9f9 100644 --- a/api/controllers/console/app/app_import.py +++ b/api/controllers/console/app/app_import.py @@ -17,6 +17,8 @@ from libs.login import login_required from models import Account from models.model import App from services.app_dsl_service import AppDslService, ImportStatus +from services.enterprise.enterprise_service import EnterpriseService +from services.feature_service import FeatureService class AppImportApi(Resource): @@ -60,7 +62,9 @@ class AppImportApi(Resource): app_id=args.get("app_id"), ) session.commit() - + if result.app_id and FeatureService.get_system_features().webapp_auth.enabled: + # update web app setting as private + EnterpriseService.WebAppAuth.update_app_access_mode(result.app_id, "private") # Return appropriate status code based on result status = result.status if status == ImportStatus.FAILED.value: diff --git a/api/controllers/console/app/audio.py b/api/controllers/console/app/audio.py index 5f2def8d8e..665cf1aede 100644 --- a/api/controllers/console/app/audio.py +++ b/api/controllers/console/app/audio.py @@ -90,23 +90,11 @@ class ChatMessageTextApi(Resource): message_id = args.get("message_id", None) text = args.get("text", None) - if ( - app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value} - and app_model.workflow - and app_model.workflow.features_dict - ): - text_to_speech = app_model.workflow.features_dict.get("text_to_speech") - if text_to_speech is None: - raise ValueError("TTS is not enabled") - voice = args.get("voice") or text_to_speech.get("voice") - else: - try: - if app_model.app_model_config is None: - raise ValueError("AppModelConfig not found") - voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice") - except Exception: - voice = None - response = AudioService.transcript_tts(app_model=app_model, text=text, message_id=message_id, voice=voice) + voice = args.get("voice", None) + + response = AudioService.transcript_tts( + app_model=app_model, text=text, voice=voice, message_id=message_id, is_draft=True + ) return response except services.errors.app_model_config.AppModelConfigBrokenError: logging.exception("App model config broken.") diff --git a/api/controllers/console/app/workflow.py b/api/controllers/console/app/workflow.py index cbbdd324ba..a9f088a276 100644 --- a/api/controllers/console/app/workflow.py +++ b/api/controllers/console/app/workflow.py @@ -1,5 +1,6 @@ import json import logging +from collections.abc import Sequence from typing import cast from flask import abort, request @@ -18,10 +19,12 @@ from controllers.console.app.error import ( from controllers.console.app.wraps import get_app_model from controllers.console.wraps import account_initialization_required, setup_required from controllers.web.error import InvokeRateLimitError as InvokeRateLimitHttpError +from core.app.app_config.features.file_upload.manager import FileUploadConfigManager from core.app.apps.base_app_queue_manager import AppQueueManager from core.app.entities.app_invoke_entities import InvokeFrom +from core.file.models import File from extensions.ext_database import db -from factories import variable_factory +from factories import file_factory, variable_factory from fields.workflow_fields import workflow_fields, workflow_pagination_fields from fields.workflow_run_fields import workflow_run_node_execution_fields from libs import helper @@ -30,6 +33,7 @@ from libs.login import current_user, login_required from models import App from models.account import Account from models.model import AppMode +from models.workflow import Workflow from services.app_generate_service import AppGenerateService from services.errors.app import WorkflowHashNotEqualError from services.errors.llm import InvokeRateLimitError @@ -38,6 +42,24 @@ from services.workflow_service import DraftWorkflowDeletionError, WorkflowInUseE logger = logging.getLogger(__name__) +# TODO(QuantumGhost): Refactor existing node run API to handle file parameter parsing +# at the controller level rather than in the workflow logic. This would improve separation +# of concerns and make the code more maintainable. +def _parse_file(workflow: Workflow, files: list[dict] | None = None) -> Sequence[File]: + files = files or [] + + file_extra_config = FileUploadConfigManager.convert(workflow.features_dict, is_vision=False) + file_objs: Sequence[File] = [] + if file_extra_config is None: + return file_objs + file_objs = file_factory.build_from_mappings( + mappings=files, + tenant_id=workflow.tenant_id, + config=file_extra_config, + ) + return file_objs + + class DraftWorkflowApi(Resource): @setup_required @login_required @@ -402,15 +424,30 @@ class DraftWorkflowNodeRunApi(Resource): parser = reqparse.RequestParser() parser.add_argument("inputs", type=dict, required=True, nullable=False, location="json") + parser.add_argument("query", type=str, required=False, location="json", default="") + parser.add_argument("files", type=list, location="json", default=[]) args = parser.parse_args() - inputs = args.get("inputs") - if inputs == None: + user_inputs = args.get("inputs") + if user_inputs is None: raise ValueError("missing inputs") + workflow_srv = WorkflowService() + # fetch draft workflow by app_model + draft_workflow = workflow_srv.get_draft_workflow(app_model=app_model) + if not draft_workflow: + raise ValueError("Workflow not initialized") + files = _parse_file(draft_workflow, args.get("files")) workflow_service = WorkflowService() + workflow_node_execution = workflow_service.run_draft_workflow_node( - app_model=app_model, node_id=node_id, user_inputs=inputs, account=current_user + app_model=app_model, + draft_workflow=draft_workflow, + node_id=node_id, + user_inputs=user_inputs, + account=current_user, + query=args.get("query", ""), + files=files, ) return workflow_node_execution @@ -731,6 +768,27 @@ class WorkflowByIdApi(Resource): return None, 204 +class DraftWorkflowNodeLastRunApi(Resource): + @setup_required + @login_required + @account_initialization_required + @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW]) + @marshal_with(workflow_run_node_execution_fields) + def get(self, app_model: App, node_id: str): + srv = WorkflowService() + workflow = srv.get_draft_workflow(app_model) + if not workflow: + raise NotFound("Workflow not found") + node_exec = srv.get_node_last_run( + app_model=app_model, + workflow=workflow, + node_id=node_id, + ) + if node_exec is None: + raise NotFound("last run not found") + return node_exec + + api.add_resource( DraftWorkflowApi, "/apps//workflows/draft", @@ -795,3 +853,7 @@ api.add_resource( WorkflowByIdApi, "/apps//workflows/", ) +api.add_resource( + DraftWorkflowNodeLastRunApi, + "/apps//workflows/draft/nodes//last-run", +) diff --git a/api/controllers/console/app/workflow_app_log.py b/api/controllers/console/app/workflow_app_log.py index b9579e2120..310146a5e7 100644 --- a/api/controllers/console/app/workflow_app_log.py +++ b/api/controllers/console/app/workflow_app_log.py @@ -34,6 +34,20 @@ class WorkflowAppLogApi(Resource): parser.add_argument( "created_at__after", type=str, location="args", help="Filter logs created after this timestamp" ) + parser.add_argument( + "created_by_end_user_session_id", + type=str, + location="args", + required=False, + default=None, + ) + parser.add_argument( + "created_by_account", + type=str, + location="args", + required=False, + default=None, + ) parser.add_argument("page", type=int_range(1, 99999), default=1, location="args") parser.add_argument("limit", type=int_range(1, 100), default=20, location="args") args = parser.parse_args() @@ -57,6 +71,8 @@ class WorkflowAppLogApi(Resource): created_at_after=args.created_at__after, page=args.page, limit=args.limit, + created_by_end_user_session_id=args.created_by_end_user_session_id, + created_by_account=args.created_by_account, ) return workflow_app_log_pagination diff --git a/api/controllers/console/app/workflow_draft_variable.py b/api/controllers/console/app/workflow_draft_variable.py new file mode 100644 index 0000000000..00d6fa3cbf --- /dev/null +++ b/api/controllers/console/app/workflow_draft_variable.py @@ -0,0 +1,421 @@ +import logging +from typing import Any, NoReturn + +from flask import Response +from flask_restful import Resource, fields, inputs, marshal, marshal_with, reqparse +from sqlalchemy.orm import Session +from werkzeug.exceptions import Forbidden + +from controllers.console import api +from controllers.console.app.error import ( + DraftWorkflowNotExist, +) +from controllers.console.app.wraps import get_app_model +from controllers.console.wraps import account_initialization_required, setup_required +from controllers.web.error import InvalidArgumentError, NotFoundError +from core.variables.segment_group import SegmentGroup +from core.variables.segments import ArrayFileSegment, FileSegment, Segment +from core.variables.types import SegmentType +from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID +from factories.file_factory import build_from_mapping, build_from_mappings +from factories.variable_factory import build_segment_with_type +from libs.login import current_user, login_required +from models import App, AppMode, db +from models.workflow import WorkflowDraftVariable +from services.workflow_draft_variable_service import WorkflowDraftVariableList, WorkflowDraftVariableService +from services.workflow_service import WorkflowService + +logger = logging.getLogger(__name__) + + +def _convert_values_to_json_serializable_object(value: Segment) -> Any: + if isinstance(value, FileSegment): + return value.value.model_dump() + elif isinstance(value, ArrayFileSegment): + return [i.model_dump() for i in value.value] + elif isinstance(value, SegmentGroup): + return [_convert_values_to_json_serializable_object(i) for i in value.value] + else: + return value.value + + +def _serialize_var_value(variable: WorkflowDraftVariable) -> Any: + value = variable.get_value() + # create a copy of the value to avoid affecting the model cache. + value = value.model_copy(deep=True) + # Refresh the url signature before returning it to client. + if isinstance(value, FileSegment): + file = value.value + file.remote_url = file.generate_url() + elif isinstance(value, ArrayFileSegment): + files = value.value + for file in files: + file.remote_url = file.generate_url() + return _convert_values_to_json_serializable_object(value) + + +def _create_pagination_parser(): + parser = reqparse.RequestParser() + parser.add_argument( + "page", + type=inputs.int_range(1, 100_000), + required=False, + default=1, + location="args", + help="the page of data requested", + ) + parser.add_argument("limit", type=inputs.int_range(1, 100), required=False, default=20, location="args") + return parser + + +_WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS = { + "id": fields.String, + "type": fields.String(attribute=lambda model: model.get_variable_type()), + "name": fields.String, + "description": fields.String, + "selector": fields.List(fields.String, attribute=lambda model: model.get_selector()), + "value_type": fields.String, + "edited": fields.Boolean(attribute=lambda model: model.edited), + "visible": fields.Boolean, +} + +_WORKFLOW_DRAFT_VARIABLE_FIELDS = dict( + _WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS, + value=fields.Raw(attribute=_serialize_var_value), +) + +_WORKFLOW_DRAFT_ENV_VARIABLE_FIELDS = { + "id": fields.String, + "type": fields.String(attribute=lambda _: "env"), + "name": fields.String, + "description": fields.String, + "selector": fields.List(fields.String, attribute=lambda model: model.get_selector()), + "value_type": fields.String, + "edited": fields.Boolean(attribute=lambda model: model.edited), + "visible": fields.Boolean, +} + +_WORKFLOW_DRAFT_ENV_VARIABLE_LIST_FIELDS = { + "items": fields.List(fields.Nested(_WORKFLOW_DRAFT_ENV_VARIABLE_FIELDS)), +} + + +def _get_items(var_list: WorkflowDraftVariableList) -> list[WorkflowDraftVariable]: + return var_list.variables + + +_WORKFLOW_DRAFT_VARIABLE_LIST_WITHOUT_VALUE_FIELDS = { + "items": fields.List(fields.Nested(_WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS), attribute=_get_items), + "total": fields.Raw(), +} + +_WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS = { + "items": fields.List(fields.Nested(_WORKFLOW_DRAFT_VARIABLE_FIELDS), attribute=_get_items), +} + + +def _api_prerequisite(f): + """Common prerequisites for all draft workflow variable APIs. + + It ensures the following conditions are satisfied: + + - Dify has been property setup. + - The request user has logged in and initialized. + - The requested app is a workflow or a chat flow. + - The request user has the edit permission for the app. + """ + + @setup_required + @login_required + @account_initialization_required + @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW]) + def wrapper(*args, **kwargs): + if not current_user.is_editor: + raise Forbidden() + return f(*args, **kwargs) + + return wrapper + + +class WorkflowVariableCollectionApi(Resource): + @_api_prerequisite + @marshal_with(_WORKFLOW_DRAFT_VARIABLE_LIST_WITHOUT_VALUE_FIELDS) + def get(self, app_model: App): + """ + Get draft workflow + """ + parser = _create_pagination_parser() + args = parser.parse_args() + + # fetch draft workflow by app_model + workflow_service = WorkflowService() + workflow_exist = workflow_service.is_workflow_exist(app_model=app_model) + if not workflow_exist: + raise DraftWorkflowNotExist() + + # fetch draft workflow by app_model + with Session(bind=db.engine, expire_on_commit=False) as session: + draft_var_srv = WorkflowDraftVariableService( + session=session, + ) + workflow_vars = draft_var_srv.list_variables_without_values( + app_id=app_model.id, + page=args.page, + limit=args.limit, + ) + + return workflow_vars + + @_api_prerequisite + def delete(self, app_model: App): + draft_var_srv = WorkflowDraftVariableService( + session=db.session(), + ) + draft_var_srv.delete_workflow_variables(app_model.id) + db.session.commit() + return Response("", 204) + + +def validate_node_id(node_id: str) -> NoReturn | None: + if node_id in [ + CONVERSATION_VARIABLE_NODE_ID, + SYSTEM_VARIABLE_NODE_ID, + ]: + # NOTE(QuantumGhost): While we store the system and conversation variables as node variables + # with specific `node_id` in database, we still want to make the API separated. By disallowing + # accessing system and conversation variables in `WorkflowDraftNodeVariableListApi`, + # we mitigate the risk that user of the API depending on the implementation detail of the API. + # + # ref: [Hyrum's Law](https://www.hyrumslaw.com/) + + raise InvalidArgumentError( + f"invalid node_id, please use correspond api for conversation and system variables, node_id={node_id}", + ) + return None + + +class NodeVariableCollectionApi(Resource): + @_api_prerequisite + @marshal_with(_WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS) + def get(self, app_model: App, node_id: str): + validate_node_id(node_id) + with Session(bind=db.engine, expire_on_commit=False) as session: + draft_var_srv = WorkflowDraftVariableService( + session=session, + ) + node_vars = draft_var_srv.list_node_variables(app_model.id, node_id) + + return node_vars + + @_api_prerequisite + def delete(self, app_model: App, node_id: str): + validate_node_id(node_id) + srv = WorkflowDraftVariableService(db.session()) + srv.delete_node_variables(app_model.id, node_id) + db.session.commit() + return Response("", 204) + + +class VariableApi(Resource): + _PATCH_NAME_FIELD = "name" + _PATCH_VALUE_FIELD = "value" + + @_api_prerequisite + @marshal_with(_WORKFLOW_DRAFT_VARIABLE_FIELDS) + def get(self, app_model: App, variable_id: str): + draft_var_srv = WorkflowDraftVariableService( + session=db.session(), + ) + variable = draft_var_srv.get_variable(variable_id=variable_id) + if variable is None: + raise NotFoundError(description=f"variable not found, id={variable_id}") + if variable.app_id != app_model.id: + raise NotFoundError(description=f"variable not found, id={variable_id}") + return variable + + @_api_prerequisite + @marshal_with(_WORKFLOW_DRAFT_VARIABLE_FIELDS) + def patch(self, app_model: App, variable_id: str): + # Request payload for file types: + # + # Local File: + # + # { + # "type": "image", + # "transfer_method": "local_file", + # "url": "", + # "upload_file_id": "daded54f-72c7-4f8e-9d18-9b0abdd9f190" + # } + # + # Remote File: + # + # + # { + # "type": "image", + # "transfer_method": "remote_url", + # "url": "http://127.0.0.1:5001/files/1602650a-4fe4-423c-85a2-af76c083e3c4/file-preview?timestamp=1750041099&nonce=...&sign=...=", + # "upload_file_id": "1602650a-4fe4-423c-85a2-af76c083e3c4" + # } + + parser = reqparse.RequestParser() + parser.add_argument(self._PATCH_NAME_FIELD, type=str, required=False, nullable=True, location="json") + # Parse 'value' field as-is to maintain its original data structure + parser.add_argument(self._PATCH_VALUE_FIELD, type=lambda x: x, required=False, nullable=True, location="json") + + draft_var_srv = WorkflowDraftVariableService( + session=db.session(), + ) + args = parser.parse_args(strict=True) + + variable = draft_var_srv.get_variable(variable_id=variable_id) + if variable is None: + raise NotFoundError(description=f"variable not found, id={variable_id}") + if variable.app_id != app_model.id: + raise NotFoundError(description=f"variable not found, id={variable_id}") + + new_name = args.get(self._PATCH_NAME_FIELD, None) + raw_value = args.get(self._PATCH_VALUE_FIELD, None) + if new_name is None and raw_value is None: + return variable + + new_value = None + if raw_value is not None: + if variable.value_type == SegmentType.FILE: + if not isinstance(raw_value, dict): + raise InvalidArgumentError(description=f"expected dict for file, got {type(raw_value)}") + raw_value = build_from_mapping(mapping=raw_value, tenant_id=app_model.tenant_id) + elif variable.value_type == SegmentType.ARRAY_FILE: + if not isinstance(raw_value, list): + raise InvalidArgumentError(description=f"expected list for files, got {type(raw_value)}") + if len(raw_value) > 0 and not isinstance(raw_value[0], dict): + raise InvalidArgumentError(description=f"expected dict for files[0], got {type(raw_value)}") + raw_value = build_from_mappings(mappings=raw_value, tenant_id=app_model.tenant_id) + new_value = build_segment_with_type(variable.value_type, raw_value) + draft_var_srv.update_variable(variable, name=new_name, value=new_value) + db.session.commit() + return variable + + @_api_prerequisite + def delete(self, app_model: App, variable_id: str): + draft_var_srv = WorkflowDraftVariableService( + session=db.session(), + ) + variable = draft_var_srv.get_variable(variable_id=variable_id) + if variable is None: + raise NotFoundError(description=f"variable not found, id={variable_id}") + if variable.app_id != app_model.id: + raise NotFoundError(description=f"variable not found, id={variable_id}") + draft_var_srv.delete_variable(variable) + db.session.commit() + return Response("", 204) + + +class VariableResetApi(Resource): + @_api_prerequisite + def put(self, app_model: App, variable_id: str): + draft_var_srv = WorkflowDraftVariableService( + session=db.session(), + ) + + workflow_srv = WorkflowService() + draft_workflow = workflow_srv.get_draft_workflow(app_model) + if draft_workflow is None: + raise NotFoundError( + f"Draft workflow not found, app_id={app_model.id}", + ) + variable = draft_var_srv.get_variable(variable_id=variable_id) + if variable is None: + raise NotFoundError(description=f"variable not found, id={variable_id}") + if variable.app_id != app_model.id: + raise NotFoundError(description=f"variable not found, id={variable_id}") + + resetted = draft_var_srv.reset_variable(draft_workflow, variable) + db.session.commit() + if resetted is None: + return Response("", 204) + else: + return marshal(resetted, _WORKFLOW_DRAFT_VARIABLE_FIELDS) + + +def _get_variable_list(app_model: App, node_id) -> WorkflowDraftVariableList: + with Session(bind=db.engine, expire_on_commit=False) as session: + draft_var_srv = WorkflowDraftVariableService( + session=session, + ) + if node_id == CONVERSATION_VARIABLE_NODE_ID: + draft_vars = draft_var_srv.list_conversation_variables(app_model.id) + elif node_id == SYSTEM_VARIABLE_NODE_ID: + draft_vars = draft_var_srv.list_system_variables(app_model.id) + else: + draft_vars = draft_var_srv.list_node_variables(app_id=app_model.id, node_id=node_id) + return draft_vars + + +class ConversationVariableCollectionApi(Resource): + @_api_prerequisite + @marshal_with(_WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS) + def get(self, app_model: App): + # NOTE(QuantumGhost): Prefill conversation variables into the draft variables table + # so their IDs can be returned to the caller. + workflow_srv = WorkflowService() + draft_workflow = workflow_srv.get_draft_workflow(app_model) + if draft_workflow is None: + raise NotFoundError(description=f"draft workflow not found, id={app_model.id}") + draft_var_srv = WorkflowDraftVariableService(db.session()) + draft_var_srv.prefill_conversation_variable_default_values(draft_workflow) + db.session.commit() + return _get_variable_list(app_model, CONVERSATION_VARIABLE_NODE_ID) + + +class SystemVariableCollectionApi(Resource): + @_api_prerequisite + @marshal_with(_WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS) + def get(self, app_model: App): + return _get_variable_list(app_model, SYSTEM_VARIABLE_NODE_ID) + + +class EnvironmentVariableCollectionApi(Resource): + @_api_prerequisite + def get(self, app_model: App): + """ + Get draft workflow + """ + # fetch draft workflow by app_model + workflow_service = WorkflowService() + workflow = workflow_service.get_draft_workflow(app_model=app_model) + if workflow is None: + raise DraftWorkflowNotExist() + + env_vars = workflow.environment_variables + env_vars_list = [] + for v in env_vars: + env_vars_list.append( + { + "id": v.id, + "type": "env", + "name": v.name, + "description": v.description, + "selector": v.selector, + "value_type": v.value_type.value, + "value": v.value, + # Do not track edited for env vars. + "edited": False, + "visible": True, + "editable": True, + } + ) + + return {"items": env_vars_list} + + +api.add_resource( + WorkflowVariableCollectionApi, + "/apps//workflows/draft/variables", +) +api.add_resource(NodeVariableCollectionApi, "/apps//workflows/draft/nodes//variables") +api.add_resource(VariableApi, "/apps//workflows/draft/variables/") +api.add_resource(VariableResetApi, "/apps//workflows/draft/variables//reset") + +api.add_resource(ConversationVariableCollectionApi, "/apps//workflows/draft/conversation-variables") +api.add_resource(SystemVariableCollectionApi, "/apps//workflows/draft/system-variables") +api.add_resource(EnvironmentVariableCollectionApi, "/apps//workflows/draft/environment-variables") diff --git a/api/controllers/console/app/wraps.py b/api/controllers/console/app/wraps.py index 9ad8c15847..03b60610aa 100644 --- a/api/controllers/console/app/wraps.py +++ b/api/controllers/console/app/wraps.py @@ -8,6 +8,15 @@ from libs.login import current_user from models import App, AppMode +def _load_app_model(app_id: str) -> Optional[App]: + app_model = ( + db.session.query(App) + .filter(App.id == app_id, App.tenant_id == current_user.current_tenant_id, App.status == "normal") + .first() + ) + return app_model + + def get_app_model(view: Optional[Callable] = None, *, mode: Union[AppMode, list[AppMode], None] = None): def decorator(view_func): @wraps(view_func) @@ -20,11 +29,7 @@ def get_app_model(view: Optional[Callable] = None, *, mode: Union[AppMode, list[ del kwargs["app_id"] - app_model = ( - db.session.query(App) - .filter(App.id == app_id, App.tenant_id == current_user.current_tenant_id, App.status == "normal") - .first() - ) + app_model = _load_app_model(app_id) if not app_model: raise AppNotFoundError() diff --git a/api/controllers/console/auth/data_source_oauth.py b/api/controllers/console/auth/data_source_oauth.py index 1049f864c3..4c9697cc32 100644 --- a/api/controllers/console/auth/data_source_oauth.py +++ b/api/controllers/console/auth/data_source_oauth.py @@ -41,7 +41,7 @@ class OAuthDataSource(Resource): if not internal_secret: return ({"error": "Internal secret is not set"},) oauth_provider.save_internal_access_token(internal_secret) - return {"data": ""} + return {"data": "internal"} else: auth_url = oauth_provider.get_authorization_url() return {"data": auth_url}, 200 diff --git a/api/controllers/console/datasets/datasets.py b/api/controllers/console/datasets/datasets.py index e68273afa6..1611214cb3 100644 --- a/api/controllers/console/datasets/datasets.py +++ b/api/controllers/console/datasets/datasets.py @@ -686,6 +686,7 @@ class DatasetRetrievalSettingApi(Resource): | VectorType.TABLESTORE | VectorType.HUAWEI_CLOUD | VectorType.TENCENT + | VectorType.MATRIXONE ): return { "retrieval_method": [ @@ -733,6 +734,7 @@ class DatasetRetrievalSettingMockApi(Resource): | VectorType.TABLESTORE | VectorType.TENCENT | VectorType.HUAWEI_CLOUD + | VectorType.MATRIXONE ): return { "retrieval_method": [ diff --git a/api/controllers/console/datasets/datasets_document.py b/api/controllers/console/datasets/datasets_document.py index f7c04102a9..b2fcf3ce7b 100644 --- a/api/controllers/console/datasets/datasets_document.py +++ b/api/controllers/console/datasets/datasets_document.py @@ -5,7 +5,7 @@ from typing import cast from flask import request from flask_login import current_user -from flask_restful import Resource, fields, marshal, marshal_with, reqparse +from flask_restful import Resource, marshal, marshal_with, reqparse from sqlalchemy import asc, desc, select from werkzeug.exceptions import Forbidden, NotFound @@ -43,7 +43,6 @@ from core.model_runtime.errors.invoke import InvokeAuthorizationError from core.plugin.impl.exc import PluginDaemonClientSideError from core.rag.extractor.entity.extract_setting import ExtractSetting from extensions.ext_database import db -from extensions.ext_redis import redis_client from fields.document_fields import ( dataset_and_document_fields, document_fields, @@ -54,8 +53,6 @@ from libs.login import login_required from models import Dataset, DatasetProcessRule, Document, DocumentSegment, UploadFile from services.dataset_service import DatasetService, DocumentService from services.entities.knowledge_entities.knowledge_entities import KnowledgeConfig -from tasks.add_document_to_index_task import add_document_to_index_task -from tasks.remove_document_from_index_task import remove_document_from_index_task class DocumentResource(Resource): @@ -242,12 +239,10 @@ class DatasetDocumentListApi(Resource): return response - documents_and_batch_fields = {"documents": fields.List(fields.Nested(document_fields)), "batch": fields.String} - @setup_required @login_required @account_initialization_required - @marshal_with(documents_and_batch_fields) + @marshal_with(dataset_and_document_fields) @cloud_edition_billing_resource_check("vector_space") @cloud_edition_billing_rate_limit_check("knowledge") def post(self, dataset_id): @@ -293,6 +288,8 @@ class DatasetDocumentListApi(Resource): try: documents, batch = DocumentService.save_document_with_dataset_id(dataset, knowledge_config, current_user) + dataset = DatasetService.get_dataset(dataset_id) + except ProviderTokenNotInitError as ex: raise ProviderNotInitializeError(ex.description) except QuotaExceededError: @@ -300,7 +297,7 @@ class DatasetDocumentListApi(Resource): except ModelCurrentlyNotSupportError: raise ProviderModelCurrentlyNotSupportError() - return {"documents": documents, "batch": batch} + return {"dataset": dataset, "documents": documents, "batch": batch} @setup_required @login_required @@ -862,77 +859,16 @@ class DocumentStatusApi(DocumentResource): DatasetService.check_dataset_permission(dataset, current_user) document_ids = request.args.getlist("document_id") - for document_id in document_ids: - document = self.get_document(dataset_id, document_id) - - indexing_cache_key = "document_{}_indexing".format(document.id) - cache_result = redis_client.get(indexing_cache_key) - if cache_result is not None: - raise InvalidActionError(f"Document:{document.name} is being indexed, please try again later") - - if action == "enable": - if document.enabled: - continue - document.enabled = True - document.disabled_at = None - document.disabled_by = None - document.updated_at = datetime.now(UTC).replace(tzinfo=None) - db.session.commit() - - # Set cache to prevent indexing the same document multiple times - redis_client.setex(indexing_cache_key, 600, 1) - - add_document_to_index_task.delay(document_id) - - elif action == "disable": - if not document.completed_at or document.indexing_status != "completed": - raise InvalidActionError(f"Document: {document.name} is not completed.") - if not document.enabled: - continue - - document.enabled = False - document.disabled_at = datetime.now(UTC).replace(tzinfo=None) - document.disabled_by = current_user.id - document.updated_at = datetime.now(UTC).replace(tzinfo=None) - db.session.commit() - - # Set cache to prevent indexing the same document multiple times - redis_client.setex(indexing_cache_key, 600, 1) - - remove_document_from_index_task.delay(document_id) - - elif action == "archive": - if document.archived: - continue - - document.archived = True - document.archived_at = datetime.now(UTC).replace(tzinfo=None) - document.archived_by = current_user.id - document.updated_at = datetime.now(UTC).replace(tzinfo=None) - db.session.commit() - - if document.enabled: - # Set cache to prevent indexing the same document multiple times - redis_client.setex(indexing_cache_key, 600, 1) - - remove_document_from_index_task.delay(document_id) - - elif action == "un_archive": - if not document.archived: - continue - document.archived = False - document.archived_at = None - document.archived_by = None - document.updated_at = datetime.now(UTC).replace(tzinfo=None) - db.session.commit() - - # Set cache to prevent indexing the same document multiple times - redis_client.setex(indexing_cache_key, 600, 1) - - add_document_to_index_task.delay(document_id) - else: - raise InvalidActionError() + try: + DocumentService.batch_update_document_status(dataset, document_ids, action, current_user) + except services.errors.document.DocumentIndexingError as e: + raise InvalidActionError(str(e)) + except ValueError as e: + raise InvalidActionError(str(e)) + except NotFound as e: + raise NotFound(str(e)) + return {"result": "success"}, 200 diff --git a/api/controllers/console/explore/audio.py b/api/controllers/console/explore/audio.py index 54bc590677..d564a00a76 100644 --- a/api/controllers/console/explore/audio.py +++ b/api/controllers/console/explore/audio.py @@ -18,7 +18,6 @@ from controllers.console.app.error import ( from controllers.console.explore.wraps import InstalledAppResource from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError from core.model_runtime.errors.invoke import InvokeError -from models.model import AppMode from services.audio_service import AudioService from services.errors.audio import ( AudioTooLargeServiceError, @@ -79,19 +78,9 @@ class ChatTextApi(InstalledAppResource): message_id = args.get("message_id", None) text = args.get("text", None) - if ( - app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value} - and app_model.workflow - and app_model.workflow.features_dict - ): - text_to_speech = app_model.workflow.features_dict.get("text_to_speech") - voice = args.get("voice") or text_to_speech.get("voice") - else: - try: - voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice") - except Exception: - voice = None - response = AudioService.transcript_tts(app_model=app_model, message_id=message_id, voice=voice, text=text) + voice = args.get("voice", None) + + response = AudioService.transcript_tts(app_model=app_model, text=text, voice=voice, message_id=message_id) return response except services.errors.app_model_config.AppModelConfigBrokenError: logging.exception("App model config broken.") diff --git a/api/controllers/console/version.py b/api/controllers/console/version.py index 7dea8e554e..447cc358f8 100644 --- a/api/controllers/console/version.py +++ b/api/controllers/console/version.py @@ -18,7 +18,7 @@ class VersionApi(Resource): check_update_url = dify_config.CHECK_UPDATE_URL result = { - "version": dify_config.CURRENT_VERSION, + "version": dify_config.project.version, "release_date": "", "release_notes": "", "can_auto_update": False, diff --git a/api/controllers/console/workspace/load_balancing_config.py b/api/controllers/console/workspace/load_balancing_config.py index ba74e2c074..b4eb5e246b 100644 --- a/api/controllers/console/workspace/load_balancing_config.py +++ b/api/controllers/console/workspace/load_balancing_config.py @@ -15,7 +15,7 @@ class LoadBalancingCredentialsValidateApi(Resource): @login_required @account_initialization_required def post(self, provider: str): - if not TenantAccountRole.is_privileged_role(current_user.current_tenant.current_role): + if not TenantAccountRole.is_privileged_role(current_user.current_role): raise Forbidden() tenant_id = current_user.current_tenant_id @@ -64,7 +64,7 @@ class LoadBalancingConfigCredentialsValidateApi(Resource): @login_required @account_initialization_required def post(self, provider: str, config_id: str): - if not TenantAccountRole.is_privileged_role(current_user.current_tenant.current_role): + if not TenantAccountRole.is_privileged_role(current_user.current_role): raise Forbidden() tenant_id = current_user.current_tenant_id diff --git a/api/controllers/console/workspace/members.py b/api/controllers/console/workspace/members.py index db49da7840..48225ac90d 100644 --- a/api/controllers/console/workspace/members.py +++ b/api/controllers/console/workspace/members.py @@ -85,6 +85,7 @@ class MemberInviteEmailApi(Resource): return { "result": "success", "invitation_results": invitation_results, + "tenant_id": str(current_user.current_tenant.id), }, 201 @@ -110,7 +111,7 @@ class MemberCancelInviteApi(Resource): except Exception as e: raise ValueError(str(e)) - return {"result": "success"}, 204 + return {"result": "success", "tenant_id": str(current_user.current_tenant.id)}, 200 class MemberUpdateRoleApi(Resource): diff --git a/api/controllers/console/workspace/plugin.py b/api/controllers/console/workspace/plugin.py index 9bddbb4b4b..c0a4734828 100644 --- a/api/controllers/console/workspace/plugin.py +++ b/api/controllers/console/workspace/plugin.py @@ -13,6 +13,7 @@ from core.model_runtime.utils.encoders import jsonable_encoder from core.plugin.impl.exc import PluginDaemonClientSideError from libs.login import login_required from models.account import TenantPluginPermission +from services.plugin.plugin_parameter_service import PluginParameterService from services.plugin.plugin_permission_service import PluginPermissionService from services.plugin.plugin_service import PluginService @@ -497,6 +498,42 @@ class PluginFetchPermissionApi(Resource): ) +class PluginFetchDynamicSelectOptionsApi(Resource): + @setup_required + @login_required + @account_initialization_required + def get(self): + # check if the user is admin or owner + if not current_user.is_admin_or_owner: + raise Forbidden() + + tenant_id = current_user.current_tenant_id + user_id = current_user.id + + parser = reqparse.RequestParser() + parser.add_argument("plugin_id", type=str, required=True, location="args") + parser.add_argument("provider", type=str, required=True, location="args") + parser.add_argument("action", type=str, required=True, location="args") + parser.add_argument("parameter", type=str, required=True, location="args") + parser.add_argument("provider_type", type=str, required=True, location="args") + args = parser.parse_args() + + try: + options = PluginParameterService.get_dynamic_select_options( + tenant_id, + user_id, + args["plugin_id"], + args["provider"], + args["action"], + args["parameter"], + args["provider_type"], + ) + except PluginDaemonClientSideError as e: + raise ValueError(e) + + return jsonable_encoder({"options": options}) + + api.add_resource(PluginDebuggingKeyApi, "/workspaces/current/plugin/debugging-key") api.add_resource(PluginListApi, "/workspaces/current/plugin/list") api.add_resource(PluginListLatestVersionsApi, "/workspaces/current/plugin/list/latest-versions") @@ -521,3 +558,5 @@ api.add_resource(PluginFetchMarketplacePkgApi, "/workspaces/current/plugin/marke api.add_resource(PluginChangePermissionApi, "/workspaces/current/plugin/permission/change") api.add_resource(PluginFetchPermissionApi, "/workspaces/current/plugin/permission/fetch") + +api.add_resource(PluginFetchDynamicSelectOptionsApi, "/workspaces/current/plugin/parameters/dynamic-options") diff --git a/api/controllers/files/upload.py b/api/controllers/files/upload.py index f1a15793c7..15f93d2774 100644 --- a/api/controllers/files/upload.py +++ b/api/controllers/files/upload.py @@ -87,7 +87,5 @@ class PluginUploadFileApi(Resource): except services.errors.file.UnsupportedFileTypeError: raise UnsupportedFileTypeError() - return tool_file, 201 - api.add_resource(PluginUploadFileApi, "/files/upload/for-plugin") diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index 41063b35a5..327e9ce834 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -17,6 +17,7 @@ from core.plugin.entities.request import ( RequestInvokeApp, RequestInvokeEncrypt, RequestInvokeLLM, + RequestInvokeLLMWithStructuredOutput, RequestInvokeModeration, RequestInvokeParameterExtractorNode, RequestInvokeQuestionClassifierNode, @@ -47,6 +48,21 @@ class PluginInvokeLLMApi(Resource): return length_prefixed_response(0xF, generator()) +class PluginInvokeLLMWithStructuredOutputApi(Resource): + @setup_required + @plugin_inner_api_only + @get_user_tenant + @plugin_data(payload_type=RequestInvokeLLMWithStructuredOutput) + def post(self, user_model: Account | EndUser, tenant_model: Tenant, payload: RequestInvokeLLMWithStructuredOutput): + def generator(): + response = PluginModelBackwardsInvocation.invoke_llm_with_structured_output( + user_model.id, tenant_model, payload + ) + return PluginModelBackwardsInvocation.convert_to_event_stream(response) + + return length_prefixed_response(0xF, generator()) + + class PluginInvokeTextEmbeddingApi(Resource): @setup_required @plugin_inner_api_only @@ -291,6 +307,7 @@ class PluginFetchAppInfoApi(Resource): api.add_resource(PluginInvokeLLMApi, "/invoke/llm") +api.add_resource(PluginInvokeLLMWithStructuredOutputApi, "/invoke/llm/structured-output") api.add_resource(PluginInvokeTextEmbeddingApi, "/invoke/text-embedding") api.add_resource(PluginInvokeRerankApi, "/invoke/rerank") api.add_resource(PluginInvokeTTSApi, "/invoke/tts") diff --git a/api/controllers/inner_api/workspace/workspace.py b/api/controllers/inner_api/workspace/workspace.py index a2fc2d4675..77568b75f1 100644 --- a/api/controllers/inner_api/workspace/workspace.py +++ b/api/controllers/inner_api/workspace/workspace.py @@ -29,7 +29,19 @@ class EnterpriseWorkspace(Resource): tenant_was_created.send(tenant) - return {"message": "enterprise workspace created."} + resp = { + "id": tenant.id, + "name": tenant.name, + "plan": tenant.plan, + "status": tenant.status, + "created_at": tenant.created_at.isoformat() + "Z" if tenant.created_at else None, + "updated_at": tenant.updated_at.isoformat() + "Z" if tenant.updated_at else None, + } + + return { + "message": "enterprise workspace created.", + "tenant": resp, + } class EnterpriseWorkspaceNoOwnerEmail(Resource): diff --git a/api/controllers/service_api/app/audio.py b/api/controllers/service_api/app/audio.py index 2682c2e7f1..848863cf1b 100644 --- a/api/controllers/service_api/app/audio.py +++ b/api/controllers/service_api/app/audio.py @@ -20,7 +20,7 @@ from controllers.service_api.app.error import ( from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError from core.model_runtime.errors.invoke import InvokeError -from models.model import App, AppMode, EndUser +from models.model import App, EndUser from services.audio_service import AudioService from services.errors.audio import ( AudioTooLargeServiceError, @@ -78,20 +78,9 @@ class TextApi(Resource): message_id = args.get("message_id", None) text = args.get("text", None) - if ( - app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value} - and app_model.workflow - and app_model.workflow.features_dict - ): - text_to_speech = app_model.workflow.features_dict.get("text_to_speech", {}) - voice = args.get("voice") or text_to_speech.get("voice") - else: - try: - voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice") - except Exception: - voice = None + voice = args.get("voice", None) response = AudioService.transcript_tts( - app_model=app_model, message_id=message_id, end_user=end_user.external_user_id, voice=voice, text=text + app_model=app_model, text=text, voice=voice, end_user=end_user.external_user_id, message_id=message_id ) return response diff --git a/api/controllers/service_api/app/workflow.py b/api/controllers/service_api/app/workflow.py index df52b49424..efb4acc5fb 100644 --- a/api/controllers/service_api/app/workflow.py +++ b/api/controllers/service_api/app/workflow.py @@ -135,6 +135,20 @@ class WorkflowAppLogApi(Resource): parser.add_argument("status", type=str, choices=["succeeded", "failed", "stopped"], location="args") parser.add_argument("created_at__before", type=str, location="args") parser.add_argument("created_at__after", type=str, location="args") + parser.add_argument( + "created_by_end_user_session_id", + type=str, + location="args", + required=False, + default=None, + ) + parser.add_argument( + "created_by_account", + type=str, + location="args", + required=False, + default=None, + ) parser.add_argument("page", type=int_range(1, 99999), default=1, location="args") parser.add_argument("limit", type=int_range(1, 100), default=20, location="args") args = parser.parse_args() @@ -158,6 +172,8 @@ class WorkflowAppLogApi(Resource): created_at_after=args.created_at__after, page=args.page, limit=args.limit, + created_by_end_user_session_id=args.created_by_end_user_session_id, + created_by_account=args.created_by_account, ) return workflow_app_log_pagination diff --git a/api/controllers/service_api/dataset/dataset.py b/api/controllers/service_api/dataset/dataset.py index 1467dfb6b3..a499719fc3 100644 --- a/api/controllers/service_api/dataset/dataset.py +++ b/api/controllers/service_api/dataset/dataset.py @@ -4,7 +4,7 @@ from werkzeug.exceptions import Forbidden, NotFound import services.dataset_service from controllers.service_api import api -from controllers.service_api.dataset.error import DatasetInUseError, DatasetNameDuplicateError +from controllers.service_api.dataset.error import DatasetInUseError, DatasetNameDuplicateError, InvalidActionError from controllers.service_api.wraps import ( DatasetApiResource, cloud_edition_billing_rate_limit_check, @@ -17,7 +17,7 @@ from fields.dataset_fields import dataset_detail_fields from fields.tag_fields import tag_fields from libs.login import current_user from models.dataset import Dataset, DatasetPermissionEnum -from services.dataset_service import DatasetPermissionService, DatasetService +from services.dataset_service import DatasetPermissionService, DatasetService, DocumentService from services.entities.knowledge_entities.knowledge_entities import RetrievalModel from services.tag_service import TagService @@ -133,6 +133,22 @@ class DatasetListApi(DatasetApiResource): parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json") args = parser.parse_args() + + if args.get("embedding_model_provider"): + DatasetService.check_embedding_model_setting( + tenant_id, args.get("embedding_model_provider"), args.get("embedding_model") + ) + if ( + args.get("retrieval_model") + and args.get("retrieval_model").get("reranking_model") + and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name") + ): + DatasetService.check_reranking_model_setting( + tenant_id, + args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"), + args.get("retrieval_model").get("reranking_model").get("reranking_model_name"), + ) + try: dataset = DatasetService.create_empty_dataset( tenant_id=tenant_id, @@ -265,10 +281,20 @@ class DatasetApi(DatasetApiResource): data = request.get_json() # check embedding model setting - if data.get("indexing_technique") == "high_quality": + if data.get("indexing_technique") == "high_quality" or data.get("embedding_model_provider"): DatasetService.check_embedding_model_setting( dataset.tenant_id, data.get("embedding_model_provider"), data.get("embedding_model") ) + if ( + data.get("retrieval_model") + and data.get("retrieval_model").get("reranking_model") + and data.get("retrieval_model").get("reranking_model").get("reranking_provider_name") + ): + DatasetService.check_reranking_model_setting( + dataset.tenant_id, + data.get("retrieval_model").get("reranking_model").get("reranking_provider_name"), + data.get("retrieval_model").get("reranking_model").get("reranking_model_name"), + ) # The role of the current user in the ta table must be admin, owner, editor, or dataset_operator DatasetPermissionService.check_permission( @@ -329,6 +355,56 @@ class DatasetApi(DatasetApiResource): raise DatasetInUseError() +class DocumentStatusApi(DatasetApiResource): + """Resource for batch document status operations.""" + + def patch(self, tenant_id, dataset_id, action): + """ + Batch update document status. + + Args: + tenant_id: tenant id + dataset_id: dataset id + action: action to perform (enable, disable, archive, un_archive) + + Returns: + dict: A dictionary with a key 'result' and a value 'success' + int: HTTP status code 200 indicating that the operation was successful. + + Raises: + NotFound: If the dataset with the given ID does not exist. + Forbidden: If the user does not have permission. + InvalidActionError: If the action is invalid or cannot be performed. + """ + dataset_id_str = str(dataset_id) + dataset = DatasetService.get_dataset(dataset_id_str) + + if dataset is None: + raise NotFound("Dataset not found.") + + # Check user's permission + try: + DatasetService.check_dataset_permission(dataset, current_user) + except services.errors.account.NoPermissionError as e: + raise Forbidden(str(e)) + + # Check dataset model setting + DatasetService.check_dataset_model_setting(dataset) + + # Get document IDs from request body + data = request.get_json() + document_ids = data.get("document_ids", []) + + try: + DocumentService.batch_update_document_status(dataset, document_ids, action, current_user) + except services.errors.document.DocumentIndexingError as e: + raise InvalidActionError(str(e)) + except ValueError as e: + raise InvalidActionError(str(e)) + + return {"result": "success"}, 200 + + class DatasetTagsApi(DatasetApiResource): @validate_dataset_token @marshal_with(tag_fields) @@ -457,6 +533,7 @@ class DatasetTagsBindingStatusApi(DatasetApiResource): api.add_resource(DatasetListApi, "/datasets") api.add_resource(DatasetApi, "/datasets/") +api.add_resource(DocumentStatusApi, "/datasets//documents/status/") api.add_resource(DatasetTagsApi, "/datasets/tags") api.add_resource(DatasetTagBindingApi, "/datasets/tags/binding") api.add_resource(DatasetTagUnbindingApi, "/datasets/tags/unbinding") diff --git a/api/controllers/service_api/dataset/document.py b/api/controllers/service_api/dataset/document.py index e4779f3bdf..d571b21a0a 100644 --- a/api/controllers/service_api/dataset/document.py +++ b/api/controllers/service_api/dataset/document.py @@ -3,7 +3,7 @@ import json from flask import request from flask_restful import marshal, reqparse from sqlalchemy import desc, select -from werkzeug.exceptions import NotFound +from werkzeug.exceptions import Forbidden, NotFound import services from controllers.common.errors import FilenameNotExistsError @@ -18,6 +18,7 @@ from controllers.service_api.app.error import ( from controllers.service_api.dataset.error import ( ArchivedDocumentImmutableError, DocumentIndexingError, + InvalidMetadataError, ) from controllers.service_api.wraps import ( DatasetApiResource, @@ -29,7 +30,7 @@ from extensions.ext_database import db from fields.document_fields import document_fields, document_status_fields from libs.login import current_user from models.dataset import Dataset, Document, DocumentSegment -from services.dataset_service import DocumentService +from services.dataset_service import DatasetService, DocumentService from services.entities.knowledge_entities.knowledge_entities import KnowledgeConfig from services.file_service import FileService @@ -59,6 +60,7 @@ class DocumentAddByTextApi(DatasetApiResource): parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json") args = parser.parse_args() + dataset_id = str(dataset_id) tenant_id = str(tenant_id) dataset = db.session.query(Dataset).filter(Dataset.tenant_id == tenant_id, Dataset.id == dataset_id).first() @@ -74,6 +76,21 @@ class DocumentAddByTextApi(DatasetApiResource): if text is None or name is None: raise ValueError("Both 'text' and 'name' must be non-null values.") + if args.get("embedding_model_provider"): + DatasetService.check_embedding_model_setting( + tenant_id, args.get("embedding_model_provider"), args.get("embedding_model") + ) + if ( + args.get("retrieval_model") + and args.get("retrieval_model").get("reranking_model") + and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name") + ): + DatasetService.check_reranking_model_setting( + tenant_id, + args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"), + args.get("retrieval_model").get("reranking_model").get("reranking_model_name"), + ) + upload_file = FileService.upload_text(text=str(text), text_name=str(name)) data_source = { "type": "upload_file", @@ -124,6 +141,17 @@ class DocumentUpdateByTextApi(DatasetApiResource): if not dataset: raise ValueError("Dataset does not exist.") + if ( + args.get("retrieval_model") + and args.get("retrieval_model").get("reranking_model") + and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name") + ): + DatasetService.check_reranking_model_setting( + tenant_id, + args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"), + args.get("retrieval_model").get("reranking_model").get("reranking_model_name"), + ) + # indexing_technique is already set in dataset since this is an update args["indexing_technique"] = dataset.indexing_technique @@ -183,11 +211,29 @@ class DocumentAddByFileApi(DatasetApiResource): if not dataset: raise ValueError("Dataset does not exist.") + if dataset.provider == "external": + raise ValueError("External datasets are not supported.") + indexing_technique = args.get("indexing_technique") or dataset.indexing_technique if not indexing_technique: raise ValueError("indexing_technique is required.") args["indexing_technique"] = indexing_technique + if "embedding_model_provider" in args: + DatasetService.check_embedding_model_setting( + tenant_id, args["embedding_model_provider"], args["embedding_model"] + ) + if ( + "retrieval_model" in args + and args["retrieval_model"].get("reranking_model") + and args["retrieval_model"].get("reranking_model").get("reranking_provider_name") + ): + DatasetService.check_reranking_model_setting( + tenant_id, + args["retrieval_model"].get("reranking_model").get("reranking_provider_name"), + args["retrieval_model"].get("reranking_model").get("reranking_model_name"), + ) + # save file info file = request.files["file"] # check file @@ -258,6 +304,9 @@ class DocumentUpdateByFileApi(DatasetApiResource): if not dataset: raise ValueError("Dataset does not exist.") + if dataset.provider == "external": + raise ValueError("External datasets are not supported.") + # indexing_technique is already set in dataset since this is an update args["indexing_technique"] = dataset.indexing_technique @@ -424,6 +473,101 @@ class DocumentIndexingStatusApi(DatasetApiResource): return data +class DocumentDetailApi(DatasetApiResource): + METADATA_CHOICES = {"all", "only", "without"} + + def get(self, tenant_id, dataset_id, document_id): + dataset_id = str(dataset_id) + document_id = str(document_id) + + dataset = self.get_dataset(dataset_id, tenant_id) + + document = DocumentService.get_document(dataset.id, document_id) + + if not document: + raise NotFound("Document not found.") + + if document.tenant_id != str(tenant_id): + raise Forbidden("No permission.") + + metadata = request.args.get("metadata", "all") + if metadata not in self.METADATA_CHOICES: + raise InvalidMetadataError(f"Invalid metadata value: {metadata}") + + if metadata == "only": + response = {"id": document.id, "doc_type": document.doc_type, "doc_metadata": document.doc_metadata_details} + elif metadata == "without": + dataset_process_rules = DatasetService.get_process_rules(dataset_id) + document_process_rules = document.dataset_process_rule.to_dict() + data_source_info = document.data_source_detail_dict + response = { + "id": document.id, + "position": document.position, + "data_source_type": document.data_source_type, + "data_source_info": data_source_info, + "dataset_process_rule_id": document.dataset_process_rule_id, + "dataset_process_rule": dataset_process_rules, + "document_process_rule": document_process_rules, + "name": document.name, + "created_from": document.created_from, + "created_by": document.created_by, + "created_at": document.created_at.timestamp(), + "tokens": document.tokens, + "indexing_status": document.indexing_status, + "completed_at": int(document.completed_at.timestamp()) if document.completed_at else None, + "updated_at": int(document.updated_at.timestamp()) if document.updated_at else None, + "indexing_latency": document.indexing_latency, + "error": document.error, + "enabled": document.enabled, + "disabled_at": int(document.disabled_at.timestamp()) if document.disabled_at else None, + "disabled_by": document.disabled_by, + "archived": document.archived, + "segment_count": document.segment_count, + "average_segment_length": document.average_segment_length, + "hit_count": document.hit_count, + "display_status": document.display_status, + "doc_form": document.doc_form, + "doc_language": document.doc_language, + } + else: + dataset_process_rules = DatasetService.get_process_rules(dataset_id) + document_process_rules = document.dataset_process_rule.to_dict() + data_source_info = document.data_source_detail_dict + response = { + "id": document.id, + "position": document.position, + "data_source_type": document.data_source_type, + "data_source_info": data_source_info, + "dataset_process_rule_id": document.dataset_process_rule_id, + "dataset_process_rule": dataset_process_rules, + "document_process_rule": document_process_rules, + "name": document.name, + "created_from": document.created_from, + "created_by": document.created_by, + "created_at": document.created_at.timestamp(), + "tokens": document.tokens, + "indexing_status": document.indexing_status, + "completed_at": int(document.completed_at.timestamp()) if document.completed_at else None, + "updated_at": int(document.updated_at.timestamp()) if document.updated_at else None, + "indexing_latency": document.indexing_latency, + "error": document.error, + "enabled": document.enabled, + "disabled_at": int(document.disabled_at.timestamp()) if document.disabled_at else None, + "disabled_by": document.disabled_by, + "archived": document.archived, + "doc_type": document.doc_type, + "doc_metadata": document.doc_metadata_details, + "segment_count": document.segment_count, + "average_segment_length": document.average_segment_length, + "hit_count": document.hit_count, + "display_status": document.display_status, + "doc_form": document.doc_form, + "doc_language": document.doc_language, + } + + return response + + api.add_resource( DocumentAddByTextApi, "/datasets//document/create_by_text", @@ -447,3 +591,4 @@ api.add_resource( api.add_resource(DocumentDeleteApi, "/datasets//documents/") api.add_resource(DocumentListApi, "/datasets//documents") api.add_resource(DocumentIndexingStatusApi, "/datasets//documents//indexing-status") +api.add_resource(DocumentDetailApi, "/datasets//documents/") diff --git a/api/controllers/service_api/index.py b/api/controllers/service_api/index.py index d24c4597e2..9bb5df4c4e 100644 --- a/api/controllers/service_api/index.py +++ b/api/controllers/service_api/index.py @@ -9,7 +9,7 @@ class IndexApi(Resource): return { "welcome": "Dify OpenAPI", "api_version": "v1", - "server_version": dify_config.CURRENT_VERSION, + "server_version": dify_config.project.version, } diff --git a/api/controllers/service_api/wraps.py b/api/controllers/service_api/wraps.py index d3316a5159..5b919a68d4 100644 --- a/api/controllers/service_api/wraps.py +++ b/api/controllers/service_api/wraps.py @@ -11,13 +11,13 @@ from flask_restful import Resource from pydantic import BaseModel from sqlalchemy import select, update from sqlalchemy.orm import Session -from werkzeug.exceptions import Forbidden, Unauthorized +from werkzeug.exceptions import Forbidden, NotFound, Unauthorized from extensions.ext_database import db from extensions.ext_redis import redis_client from libs.login import _get_user from models.account import Account, Tenant, TenantAccountJoin, TenantStatus -from models.dataset import RateLimitLog +from models.dataset import Dataset, RateLimitLog from models.model import ApiToken, App, EndUser from services.feature_service import FeatureService @@ -317,3 +317,11 @@ def create_or_update_end_user_for_user_id(app_model: App, user_id: Optional[str] class DatasetApiResource(Resource): method_decorators = [validate_dataset_token] + + def get_dataset(self, dataset_id: str, tenant_id: str) -> Dataset: + dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id, Dataset.tenant_id == tenant_id).first() + + if not dataset: + raise NotFound("Dataset not found.") + + return dataset diff --git a/api/controllers/web/audio.py b/api/controllers/web/audio.py index 06d9ad7564..2919ca9af4 100644 --- a/api/controllers/web/audio.py +++ b/api/controllers/web/audio.py @@ -19,7 +19,7 @@ from controllers.web.error import ( from controllers.web.wraps import WebApiResource from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError from core.model_runtime.errors.invoke import InvokeError -from models.model import App, AppMode +from models.model import App from services.audio_service import AudioService from services.errors.audio import ( AudioTooLargeServiceError, @@ -77,21 +77,9 @@ class TextApi(WebApiResource): message_id = args.get("message_id", None) text = args.get("text", None) - if ( - app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value} - and app_model.workflow - and app_model.workflow.features_dict - ): - text_to_speech = app_model.workflow.features_dict.get("text_to_speech", {}) - voice = args.get("voice") or text_to_speech.get("voice") - else: - try: - voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice") - except Exception: - voice = None - + voice = args.get("voice", None) response = AudioService.transcript_tts( - app_model=app_model, message_id=message_id, end_user=end_user.external_user_id, voice=voice, text=text + app_model=app_model, text=text, voice=voice, end_user=end_user.external_user_id, message_id=message_id ) return response diff --git a/api/controllers/web/error.py b/api/controllers/web/error.py index 4371e679db..036e11d5c5 100644 --- a/api/controllers/web/error.py +++ b/api/controllers/web/error.py @@ -139,3 +139,13 @@ class InvokeRateLimitError(BaseHTTPException): error_code = "rate_limit_error" description = "Rate Limit Error" code = 429 + + +class NotFoundError(BaseHTTPException): + error_code = "not_found" + code = 404 + + +class InvalidArgumentError(BaseHTTPException): + error_code = "invalid_param" + code = 400 diff --git a/api/core/app/app_config/entities.py b/api/core/app/app_config/entities.py index 3f31b1c3d5..75bd2f677a 100644 --- a/api/core/app/app_config/entities.py +++ b/api/core/app/app_config/entities.py @@ -104,6 +104,7 @@ class VariableEntity(BaseModel): Variable Entity. """ + # `variable` records the name of the variable in user inputs. variable: str label: str description: str = "" diff --git a/api/core/app/apps/advanced_chat/app_generator.py b/api/core/app/apps/advanced_chat/app_generator.py index a8848b9534..7877408cef 100644 --- a/api/core/app/apps/advanced_chat/app_generator.py +++ b/api/core/app/apps/advanced_chat/app_generator.py @@ -27,15 +27,22 @@ from core.ops.ops_trace_manager import TraceQueueManager from core.prompt.utils.get_thread_messages_length import get_thread_messages_length from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository +from core.workflow.repositories.draft_variable_repository import ( + DraftVariableSaverFactory, +) from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository +from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader from extensions.ext_database import db from factories import file_factory from libs.flask_utils import preserve_flask_contexts from models import Account, App, Conversation, EndUser, Message, Workflow, WorkflowNodeExecutionTriggeredFrom from models.enums import WorkflowRunTriggeredFrom from services.conversation_service import ConversationService -from services.errors.message import MessageNotExistsError +from services.workflow_draft_variable_service import ( + DraftVarLoader, + WorkflowDraftVariableService, +) logger = logging.getLogger(__name__) @@ -116,6 +123,11 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): ) # parse files + # TODO(QuantumGhost): Move file parsing logic to the API controller layer + # for better separation of concerns. + # + # For implementation reference, see the `_parse_file` function and + # `DraftWorkflowNodeRunApi` class which handle this properly. files = args["files"] if args.get("files") else [] file_extra_config = FileUploadConfigManager.convert(workflow.features_dict, is_vision=False) if file_extra_config: @@ -261,6 +273,13 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): app_id=application_generate_entity.app_config.app_id, triggered_from=WorkflowNodeExecutionTriggeredFrom.SINGLE_STEP, ) + var_loader = DraftVarLoader( + engine=db.engine, + app_id=application_generate_entity.app_config.app_id, + tenant_id=application_generate_entity.app_config.tenant_id, + ) + draft_var_srv = WorkflowDraftVariableService(db.session()) + draft_var_srv.prefill_conversation_variable_default_values(workflow) return self._generate( workflow=workflow, @@ -271,6 +290,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): workflow_node_execution_repository=workflow_node_execution_repository, conversation=None, stream=streaming, + variable_loader=var_loader, ) def single_loop_generate( @@ -336,6 +356,13 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): app_id=application_generate_entity.app_config.app_id, triggered_from=WorkflowNodeExecutionTriggeredFrom.SINGLE_STEP, ) + var_loader = DraftVarLoader( + engine=db.engine, + app_id=application_generate_entity.app_config.app_id, + tenant_id=application_generate_entity.app_config.tenant_id, + ) + draft_var_srv = WorkflowDraftVariableService(db.session()) + draft_var_srv.prefill_conversation_variable_default_values(workflow) return self._generate( workflow=workflow, @@ -346,6 +373,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): workflow_node_execution_repository=workflow_node_execution_repository, conversation=None, stream=streaming, + variable_loader=var_loader, ) def _generate( @@ -359,6 +387,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): workflow_node_execution_repository: WorkflowNodeExecutionRepository, conversation: Optional[Conversation] = None, stream: bool = True, + variable_loader: VariableLoader = DUMMY_VARIABLE_LOADER, ) -> Mapping[str, Any] | Generator[str | Mapping[str, Any], Any, None]: """ Generate App response. @@ -410,6 +439,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): "conversation_id": conversation.id, "message_id": message.id, "context": context, + "variable_loader": variable_loader, }, ) @@ -426,6 +456,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): workflow_execution_repository=workflow_execution_repository, workflow_node_execution_repository=workflow_node_execution_repository, stream=stream, + draft_var_saver_factory=self._get_draft_var_saver_factory(invoke_from), ) return AdvancedChatAppGenerateResponseConverter.convert(response=response, invoke_from=invoke_from) @@ -438,6 +469,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): conversation_id: str, message_id: str, context: contextvars.Context, + variable_loader: VariableLoader, ) -> None: """ Generate worker in a new thread. @@ -454,8 +486,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): # get conversation and message conversation = self._get_conversation(conversation_id) message = self._get_message(message_id) - if message is None: - raise MessageNotExistsError("Message not exists") # chatbot app runner = AdvancedChatAppRunner( @@ -464,6 +494,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): conversation=conversation, message=message, dialogue_count=self._dialogue_count, + variable_loader=variable_loader, ) runner.run() @@ -497,6 +528,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): user: Union[Account, EndUser], workflow_execution_repository: WorkflowExecutionRepository, workflow_node_execution_repository: WorkflowNodeExecutionRepository, + draft_var_saver_factory: DraftVariableSaverFactory, stream: bool = False, ) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]: """ @@ -523,6 +555,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): workflow_execution_repository=workflow_execution_repository, workflow_node_execution_repository=workflow_node_execution_repository, stream=stream, + draft_var_saver_factory=draft_var_saver_factory, ) try: diff --git a/api/core/app/apps/advanced_chat/app_runner.py b/api/core/app/apps/advanced_chat/app_runner.py index d9b3833862..840a3c9d3b 100644 --- a/api/core/app/apps/advanced_chat/app_runner.py +++ b/api/core/app/apps/advanced_chat/app_runner.py @@ -19,6 +19,7 @@ from core.moderation.base import ModerationError from core.workflow.callbacks import WorkflowCallback, WorkflowLoggingCallback from core.workflow.entities.variable_pool import VariablePool from core.workflow.enums import SystemVariableKey +from core.workflow.variable_loader import VariableLoader from core.workflow.workflow_entry import WorkflowEntry from extensions.ext_database import db from models.enums import UserFrom @@ -40,14 +41,17 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner): conversation: Conversation, message: Message, dialogue_count: int, + variable_loader: VariableLoader, ) -> None: - super().__init__(queue_manager) - + super().__init__(queue_manager, variable_loader) self.application_generate_entity = application_generate_entity self.conversation = conversation self.message = message self._dialogue_count = dialogue_count + def _get_app_id(self) -> str: + return self.application_generate_entity.app_config.app_id + def run(self) -> None: app_config = self.application_generate_entity.app_config app_config = cast(AdvancedChatAppConfig, app_config) diff --git a/api/core/app/apps/advanced_chat/generate_task_pipeline.py b/api/core/app/apps/advanced_chat/generate_task_pipeline.py index 8c5645bbb7..4c52fc3e83 100644 --- a/api/core/app/apps/advanced_chat/generate_task_pipeline.py +++ b/api/core/app/apps/advanced_chat/generate_task_pipeline.py @@ -64,6 +64,7 @@ from core.workflow.entities.workflow_execution import WorkflowExecutionStatus, W from core.workflow.enums import SystemVariableKey from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState from core.workflow.nodes import NodeType +from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository from core.workflow.workflow_cycle_manager import CycleManagerWorkflowInfo, WorkflowCycleManager @@ -94,6 +95,7 @@ class AdvancedChatAppGenerateTaskPipeline: dialogue_count: int, workflow_execution_repository: WorkflowExecutionRepository, workflow_node_execution_repository: WorkflowNodeExecutionRepository, + draft_var_saver_factory: DraftVariableSaverFactory, ) -> None: self._base_task_pipeline = BasedGenerateTaskPipeline( application_generate_entity=application_generate_entity, @@ -153,6 +155,7 @@ class AdvancedChatAppGenerateTaskPipeline: self._conversation_name_generate_thread: Thread | None = None self._recorded_files: list[Mapping[str, Any]] = [] self._workflow_run_id: str = "" + self._draft_var_saver_factory = draft_var_saver_factory def process(self) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]: """ @@ -371,6 +374,7 @@ class AdvancedChatAppGenerateTaskPipeline: workflow_node_execution=workflow_node_execution, ) session.commit() + self._save_output_for_event(event, workflow_node_execution.id) if node_finish_resp: yield node_finish_resp @@ -390,6 +394,8 @@ class AdvancedChatAppGenerateTaskPipeline: task_id=self._application_generate_entity.task_id, workflow_node_execution=workflow_node_execution, ) + if isinstance(event, QueueNodeExceptionEvent): + self._save_output_for_event(event, workflow_node_execution.id) if node_finish_resp: yield node_finish_resp @@ -759,3 +765,15 @@ class AdvancedChatAppGenerateTaskPipeline: if not message: raise ValueError(f"Message not found: {self._message_id}") return message + + def _save_output_for_event(self, event: QueueNodeSucceededEvent | QueueNodeExceptionEvent, node_execution_id: str): + with Session(db.engine) as session, session.begin(): + saver = self._draft_var_saver_factory( + session=session, + app_id=self._application_generate_entity.app_config.app_id, + node_id=event.node_id, + node_type=event.node_type, + node_execution_id=node_execution_id, + enclosing_node_id=event.in_loop_id or event.in_iteration_id, + ) + saver.save(event.process_data, event.outputs) diff --git a/api/core/app/apps/agent_chat/app_generator.py b/api/core/app/apps/agent_chat/app_generator.py index a448bf8a94..edea6199d3 100644 --- a/api/core/app/apps/agent_chat/app_generator.py +++ b/api/core/app/apps/agent_chat/app_generator.py @@ -26,7 +26,6 @@ from factories import file_factory from libs.flask_utils import preserve_flask_contexts from models import Account, App, EndUser from services.conversation_service import ConversationService -from services.errors.message import MessageNotExistsError logger = logging.getLogger(__name__) @@ -124,6 +123,11 @@ class AgentChatAppGenerator(MessageBasedAppGenerator): override_model_config_dict["retriever_resource"] = {"enabled": True} # parse files + # TODO(QuantumGhost): Move file parsing logic to the API controller layer + # for better separation of concerns. + # + # For implementation reference, see the `_parse_file` function and + # `DraftWorkflowNodeRunApi` class which handle this properly. files = args.get("files") or [] file_extra_config = FileUploadConfigManager.convert(override_model_config_dict or app_model_config.to_dict()) if file_extra_config: @@ -233,8 +237,6 @@ class AgentChatAppGenerator(MessageBasedAppGenerator): # get conversation and message conversation = self._get_conversation(conversation_id) message = self._get_message(message_id) - if message is None: - raise MessageNotExistsError("Message not exists") # chatbot app runner = AgentChatAppRunner() diff --git a/api/core/app/apps/base_app_generator.py b/api/core/app/apps/base_app_generator.py index a83b75cc1a..beece1d77e 100644 --- a/api/core/app/apps/base_app_generator.py +++ b/api/core/app/apps/base_app_generator.py @@ -1,10 +1,20 @@ import json from collections.abc import Generator, Mapping, Sequence -from typing import TYPE_CHECKING, Any, Optional, Union +from typing import TYPE_CHECKING, Any, Optional, Union, final + +from sqlalchemy.orm import Session from core.app.app_config.entities import VariableEntityType +from core.app.entities.app_invoke_entities import InvokeFrom from core.file import File, FileUploadConfig +from core.workflow.nodes.enums import NodeType +from core.workflow.repositories.draft_variable_repository import ( + DraftVariableSaver, + DraftVariableSaverFactory, + NoopDraftVariableSaver, +) from factories import file_factory +from services.workflow_draft_variable_service import DraftVariableSaver as DraftVariableSaverImpl if TYPE_CHECKING: from core.app.app_config.entities import VariableEntity @@ -159,3 +169,38 @@ class BaseAppGenerator: yield f"event: {message}\n\n" return gen() + + @final + @staticmethod + def _get_draft_var_saver_factory(invoke_from: InvokeFrom) -> DraftVariableSaverFactory: + if invoke_from == InvokeFrom.DEBUGGER: + + def draft_var_saver_factory( + session: Session, + app_id: str, + node_id: str, + node_type: NodeType, + node_execution_id: str, + enclosing_node_id: str | None = None, + ) -> DraftVariableSaver: + return DraftVariableSaverImpl( + session=session, + app_id=app_id, + node_id=node_id, + node_type=node_type, + node_execution_id=node_execution_id, + enclosing_node_id=enclosing_node_id, + ) + else: + + def draft_var_saver_factory( + session: Session, + app_id: str, + node_id: str, + node_type: NodeType, + node_execution_id: str, + enclosing_node_id: str | None = None, + ) -> DraftVariableSaver: + return NoopDraftVariableSaver() + + return draft_var_saver_factory diff --git a/api/core/app/apps/chat/app_generator.py b/api/core/app/apps/chat/app_generator.py index a1329cb938..a28c106ce9 100644 --- a/api/core/app/apps/chat/app_generator.py +++ b/api/core/app/apps/chat/app_generator.py @@ -25,7 +25,6 @@ from factories import file_factory from models.account import Account from models.model import App, EndUser from services.conversation_service import ConversationService -from services.errors.message import MessageNotExistsError logger = logging.getLogger(__name__) @@ -115,6 +114,11 @@ class ChatAppGenerator(MessageBasedAppGenerator): override_model_config_dict["retriever_resource"] = {"enabled": True} # parse files + # TODO(QuantumGhost): Move file parsing logic to the API controller layer + # for better separation of concerns. + # + # For implementation reference, see the `_parse_file` function and + # `DraftWorkflowNodeRunApi` class which handle this properly. files = args["files"] if args.get("files") else [] file_extra_config = FileUploadConfigManager.convert(override_model_config_dict or app_model_config.to_dict()) if file_extra_config: @@ -219,8 +223,6 @@ class ChatAppGenerator(MessageBasedAppGenerator): # get conversation and message conversation = self._get_conversation(conversation_id) message = self._get_message(message_id) - if message is None: - raise MessageNotExistsError("Message not exists") # chatbot app runner = ChatAppRunner() diff --git a/api/core/app/apps/common/workflow_response_converter.py b/api/core/app/apps/common/workflow_response_converter.py index 6f524a5872..34a1da2227 100644 --- a/api/core/app/apps/common/workflow_response_converter.py +++ b/api/core/app/apps/common/workflow_response_converter.py @@ -44,10 +44,12 @@ from core.app.entities.task_entities import ( ) from core.file import FILE_MODEL_IDENTITY, File from core.tools.tool_manager import ToolManager +from core.variables.segments import ArrayFileSegment, FileSegment, Segment from core.workflow.entities.workflow_execution import WorkflowExecution from core.workflow.entities.workflow_node_execution import WorkflowNodeExecution, WorkflowNodeExecutionStatus from core.workflow.nodes import NodeType from core.workflow.nodes.tool.entities import ToolNodeData +from core.workflow.workflow_type_encoder import WorkflowRuntimeTypeConverter from models import ( Account, CreatorUserRole, @@ -125,7 +127,7 @@ class WorkflowResponseConverter: id=workflow_execution.id_, workflow_id=workflow_execution.workflow_id, status=workflow_execution.status, - outputs=workflow_execution.outputs, + outputs=WorkflowRuntimeTypeConverter().to_json_encodable(workflow_execution.outputs), error=workflow_execution.error_message, elapsed_time=workflow_execution.elapsed_time, total_tokens=workflow_execution.total_tokens, @@ -202,6 +204,8 @@ class WorkflowResponseConverter: if not workflow_node_execution.finished_at: return None + json_converter = WorkflowRuntimeTypeConverter() + return NodeFinishStreamResponse( task_id=task_id, workflow_run_id=workflow_node_execution.workflow_execution_id, @@ -214,7 +218,7 @@ class WorkflowResponseConverter: predecessor_node_id=workflow_node_execution.predecessor_node_id, inputs=workflow_node_execution.inputs, process_data=workflow_node_execution.process_data, - outputs=workflow_node_execution.outputs, + outputs=json_converter.to_json_encodable(workflow_node_execution.outputs), status=workflow_node_execution.status, error=workflow_node_execution.error, elapsed_time=workflow_node_execution.elapsed_time, @@ -245,6 +249,8 @@ class WorkflowResponseConverter: if not workflow_node_execution.finished_at: return None + json_converter = WorkflowRuntimeTypeConverter() + return NodeRetryStreamResponse( task_id=task_id, workflow_run_id=workflow_node_execution.workflow_execution_id, @@ -257,7 +263,7 @@ class WorkflowResponseConverter: predecessor_node_id=workflow_node_execution.predecessor_node_id, inputs=workflow_node_execution.inputs, process_data=workflow_node_execution.process_data, - outputs=workflow_node_execution.outputs, + outputs=json_converter.to_json_encodable(workflow_node_execution.outputs), status=workflow_node_execution.status, error=workflow_node_execution.error, elapsed_time=workflow_node_execution.elapsed_time, @@ -376,6 +382,7 @@ class WorkflowResponseConverter: workflow_execution_id: str, event: QueueIterationCompletedEvent, ) -> IterationNodeCompletedStreamResponse: + json_converter = WorkflowRuntimeTypeConverter() return IterationNodeCompletedStreamResponse( task_id=task_id, workflow_run_id=workflow_execution_id, @@ -384,7 +391,7 @@ class WorkflowResponseConverter: node_id=event.node_id, node_type=event.node_type.value, title=event.node_data.title, - outputs=event.outputs, + outputs=json_converter.to_json_encodable(event.outputs), created_at=int(time.time()), extras={}, inputs=event.inputs or {}, @@ -463,7 +470,7 @@ class WorkflowResponseConverter: node_id=event.node_id, node_type=event.node_type.value, title=event.node_data.title, - outputs=event.outputs, + outputs=WorkflowRuntimeTypeConverter().to_json_encodable(event.outputs), created_at=int(time.time()), extras={}, inputs=event.inputs or {}, @@ -500,7 +507,8 @@ class WorkflowResponseConverter: # Convert to tuple to match Sequence type return tuple(flattened_files) - def _fetch_files_from_variable_value(self, value: Union[dict, list]) -> Sequence[Mapping[str, Any]]: + @classmethod + def _fetch_files_from_variable_value(cls, value: Union[dict, list, Segment]) -> Sequence[Mapping[str, Any]]: """ Fetch files from variable value :param value: variable value @@ -509,20 +517,30 @@ class WorkflowResponseConverter: if not value: return [] - files = [] - if isinstance(value, list): + files: list[Mapping[str, Any]] = [] + if isinstance(value, FileSegment): + files.append(value.value.to_dict()) + elif isinstance(value, ArrayFileSegment): + files.extend([i.to_dict() for i in value.value]) + elif isinstance(value, File): + files.append(value.to_dict()) + elif isinstance(value, list): for item in value: - file = self._get_file_var_from_value(item) + file = cls._get_file_var_from_value(item) if file: files.append(file) - elif isinstance(value, dict): - file = self._get_file_var_from_value(value) + elif isinstance( + value, + dict, + ): + file = cls._get_file_var_from_value(value) if file: files.append(file) return files - def _get_file_var_from_value(self, value: Union[dict, list]) -> Mapping[str, Any] | None: + @classmethod + def _get_file_var_from_value(cls, value: Union[dict, list]) -> Mapping[str, Any] | None: """ Get file var from value :param value: variable value diff --git a/api/core/app/apps/completion/app_generator.py b/api/core/app/apps/completion/app_generator.py index adcbaad3ec..966a6f1d66 100644 --- a/api/core/app/apps/completion/app_generator.py +++ b/api/core/app/apps/completion/app_generator.py @@ -101,6 +101,11 @@ class CompletionAppGenerator(MessageBasedAppGenerator): ) # parse files + # TODO(QuantumGhost): Move file parsing logic to the API controller layer + # for better separation of concerns. + # + # For implementation reference, see the `_parse_file` function and + # `DraftWorkflowNodeRunApi` class which handle this properly. files = args["files"] if args.get("files") else [] file_extra_config = FileUploadConfigManager.convert(override_model_config_dict or app_model_config.to_dict()) if file_extra_config: @@ -196,8 +201,6 @@ class CompletionAppGenerator(MessageBasedAppGenerator): try: # get message message = self._get_message(message_id) - if message is None: - raise MessageNotExistsError() # chatbot app runner = CompletionAppRunner() diff --git a/api/core/app/apps/message_based_app_generator.py b/api/core/app/apps/message_based_app_generator.py index 58b94f4d43..e84d59209d 100644 --- a/api/core/app/apps/message_based_app_generator.py +++ b/api/core/app/apps/message_based_app_generator.py @@ -29,6 +29,7 @@ from models.enums import CreatorUserRole from models.model import App, AppMode, AppModelConfig, Conversation, EndUser, Message, MessageFile from services.errors.app_model_config import AppModelConfigBrokenError from services.errors.conversation import ConversationNotExistsError +from services.errors.message import MessageNotExistsError logger = logging.getLogger(__name__) @@ -251,7 +252,7 @@ class MessageBasedAppGenerator(BaseAppGenerator): return introduction or "" - def _get_conversation(self, conversation_id: str): + def _get_conversation(self, conversation_id: str) -> Conversation: """ Get conversation by conversation id :param conversation_id: conversation id @@ -260,11 +261,11 @@ class MessageBasedAppGenerator(BaseAppGenerator): conversation = db.session.query(Conversation).filter(Conversation.id == conversation_id).first() if not conversation: - raise ConversationNotExistsError() + raise ConversationNotExistsError("Conversation not exists") return conversation - def _get_message(self, message_id: str) -> Optional[Message]: + def _get_message(self, message_id: str) -> Message: """ Get message by message id :param message_id: message id @@ -272,4 +273,7 @@ class MessageBasedAppGenerator(BaseAppGenerator): """ message = db.session.query(Message).filter(Message.id == message_id).first() + if message is None: + raise MessageNotExistsError("Message not exists") + return message diff --git a/api/core/app/apps/workflow/app_generator.py b/api/core/app/apps/workflow/app_generator.py index fd15bd9f50..40a1e272a7 100644 --- a/api/core/app/apps/workflow/app_generator.py +++ b/api/core/app/apps/workflow/app_generator.py @@ -25,13 +25,16 @@ from core.model_runtime.errors.invoke import InvokeAuthorizationError from core.ops.ops_trace_manager import TraceQueueManager from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository +from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository +from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader from extensions.ext_database import db from factories import file_factory from libs.flask_utils import preserve_flask_contexts from models import Account, App, EndUser, Workflow, WorkflowNodeExecutionTriggeredFrom from models.enums import WorkflowRunTriggeredFrom +from services.workflow_draft_variable_service import DraftVarLoader, WorkflowDraftVariableService logger = logging.getLogger(__name__) @@ -94,6 +97,11 @@ class WorkflowAppGenerator(BaseAppGenerator): files: Sequence[Mapping[str, Any]] = args.get("files") or [] # parse files + # TODO(QuantumGhost): Move file parsing logic to the API controller layer + # for better separation of concerns. + # + # For implementation reference, see the `_parse_file` function and + # `DraftWorkflowNodeRunApi` class which handle this properly. file_extra_config = FileUploadConfigManager.convert(workflow.features_dict, is_vision=False) system_files = file_factory.build_from_mappings( mappings=files, @@ -186,6 +194,7 @@ class WorkflowAppGenerator(BaseAppGenerator): workflow_node_execution_repository: WorkflowNodeExecutionRepository, streaming: bool = True, workflow_thread_pool_id: Optional[str] = None, + variable_loader: VariableLoader = DUMMY_VARIABLE_LOADER, ) -> Union[Mapping[str, Any], Generator[str | Mapping[str, Any], None, None]]: """ Generate App response. @@ -211,6 +220,9 @@ class WorkflowAppGenerator(BaseAppGenerator): # new thread with request context and contextvars context = contextvars.copy_context() + # release database connection, because the following new thread operations may take a long time + db.session.close() + worker_thread = threading.Thread( target=self._generate_worker, kwargs={ @@ -219,11 +231,16 @@ class WorkflowAppGenerator(BaseAppGenerator): "queue_manager": queue_manager, "context": context, "workflow_thread_pool_id": workflow_thread_pool_id, + "variable_loader": variable_loader, }, ) worker_thread.start() + draft_var_saver_factory = self._get_draft_var_saver_factory( + invoke_from, + ) + # return response or stream generator response = self._handle_response( application_generate_entity=application_generate_entity, @@ -232,6 +249,7 @@ class WorkflowAppGenerator(BaseAppGenerator): user=user, workflow_execution_repository=workflow_execution_repository, workflow_node_execution_repository=workflow_node_execution_repository, + draft_var_saver_factory=draft_var_saver_factory, stream=streaming, ) @@ -303,6 +321,13 @@ class WorkflowAppGenerator(BaseAppGenerator): app_id=application_generate_entity.app_config.app_id, triggered_from=WorkflowNodeExecutionTriggeredFrom.SINGLE_STEP, ) + draft_var_srv = WorkflowDraftVariableService(db.session()) + draft_var_srv.prefill_conversation_variable_default_values(workflow) + var_loader = DraftVarLoader( + engine=db.engine, + app_id=application_generate_entity.app_config.app_id, + tenant_id=application_generate_entity.app_config.tenant_id, + ) return self._generate( app_model=app_model, @@ -313,6 +338,7 @@ class WorkflowAppGenerator(BaseAppGenerator): workflow_execution_repository=workflow_execution_repository, workflow_node_execution_repository=workflow_node_execution_repository, streaming=streaming, + variable_loader=var_loader, ) def single_loop_generate( @@ -379,7 +405,13 @@ class WorkflowAppGenerator(BaseAppGenerator): app_id=application_generate_entity.app_config.app_id, triggered_from=WorkflowNodeExecutionTriggeredFrom.SINGLE_STEP, ) - + draft_var_srv = WorkflowDraftVariableService(db.session()) + draft_var_srv.prefill_conversation_variable_default_values(workflow) + var_loader = DraftVarLoader( + engine=db.engine, + app_id=application_generate_entity.app_config.app_id, + tenant_id=application_generate_entity.app_config.tenant_id, + ) return self._generate( app_model=app_model, workflow=workflow, @@ -389,6 +421,7 @@ class WorkflowAppGenerator(BaseAppGenerator): workflow_execution_repository=workflow_execution_repository, workflow_node_execution_repository=workflow_node_execution_repository, streaming=streaming, + variable_loader=var_loader, ) def _generate_worker( @@ -397,6 +430,7 @@ class WorkflowAppGenerator(BaseAppGenerator): application_generate_entity: WorkflowAppGenerateEntity, queue_manager: AppQueueManager, context: contextvars.Context, + variable_loader: VariableLoader, workflow_thread_pool_id: Optional[str] = None, ) -> None: """ @@ -415,6 +449,7 @@ class WorkflowAppGenerator(BaseAppGenerator): application_generate_entity=application_generate_entity, queue_manager=queue_manager, workflow_thread_pool_id=workflow_thread_pool_id, + variable_loader=variable_loader, ) runner.run() @@ -445,6 +480,7 @@ class WorkflowAppGenerator(BaseAppGenerator): user: Union[Account, EndUser], workflow_execution_repository: WorkflowExecutionRepository, workflow_node_execution_repository: WorkflowNodeExecutionRepository, + draft_var_saver_factory: DraftVariableSaverFactory, stream: bool = False, ) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]: """ @@ -465,6 +501,7 @@ class WorkflowAppGenerator(BaseAppGenerator): user=user, workflow_execution_repository=workflow_execution_repository, workflow_node_execution_repository=workflow_node_execution_repository, + draft_var_saver_factory=draft_var_saver_factory, stream=stream, ) diff --git a/api/core/app/apps/workflow/app_runner.py b/api/core/app/apps/workflow/app_runner.py index b59e34e222..07aeb57fa3 100644 --- a/api/core/app/apps/workflow/app_runner.py +++ b/api/core/app/apps/workflow/app_runner.py @@ -12,6 +12,7 @@ from core.app.entities.app_invoke_entities import ( from core.workflow.callbacks import WorkflowCallback, WorkflowLoggingCallback from core.workflow.entities.variable_pool import VariablePool from core.workflow.enums import SystemVariableKey +from core.workflow.variable_loader import VariableLoader from core.workflow.workflow_entry import WorkflowEntry from extensions.ext_database import db from models.enums import UserFrom @@ -30,6 +31,7 @@ class WorkflowAppRunner(WorkflowBasedAppRunner): self, application_generate_entity: WorkflowAppGenerateEntity, queue_manager: AppQueueManager, + variable_loader: VariableLoader, workflow_thread_pool_id: Optional[str] = None, ) -> None: """ @@ -37,10 +39,13 @@ class WorkflowAppRunner(WorkflowBasedAppRunner): :param queue_manager: application queue manager :param workflow_thread_pool_id: workflow thread pool id """ + super().__init__(queue_manager, variable_loader) self.application_generate_entity = application_generate_entity - self.queue_manager = queue_manager self.workflow_thread_pool_id = workflow_thread_pool_id + def _get_app_id(self) -> str: + return self.application_generate_entity.app_config.app_id + def run(self) -> None: """ Run application diff --git a/api/core/app/apps/workflow/generate_task_pipeline.py b/api/core/app/apps/workflow/generate_task_pipeline.py index 1734dbb598..2a85cd5e3d 100644 --- a/api/core/app/apps/workflow/generate_task_pipeline.py +++ b/api/core/app/apps/workflow/generate_task_pipeline.py @@ -56,6 +56,7 @@ from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk from core.ops.ops_trace_manager import TraceQueueManager from core.workflow.entities.workflow_execution import WorkflowExecution, WorkflowExecutionStatus, WorkflowType from core.workflow.enums import SystemVariableKey +from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository from core.workflow.workflow_cycle_manager import CycleManagerWorkflowInfo, WorkflowCycleManager @@ -87,6 +88,7 @@ class WorkflowAppGenerateTaskPipeline: stream: bool, workflow_execution_repository: WorkflowExecutionRepository, workflow_node_execution_repository: WorkflowNodeExecutionRepository, + draft_var_saver_factory: DraftVariableSaverFactory, ) -> None: self._base_task_pipeline = BasedGenerateTaskPipeline( application_generate_entity=application_generate_entity, @@ -131,6 +133,8 @@ class WorkflowAppGenerateTaskPipeline: self._application_generate_entity = application_generate_entity self._workflow_features_dict = workflow.features_dict self._workflow_run_id = "" + self._invoke_from = queue_manager._invoke_from + self._draft_var_saver_factory = draft_var_saver_factory def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]: """ @@ -322,6 +326,8 @@ class WorkflowAppGenerateTaskPipeline: workflow_node_execution=workflow_node_execution, ) + self._save_output_for_event(event, workflow_node_execution.id) + if node_success_response: yield node_success_response elif isinstance( @@ -339,6 +345,8 @@ class WorkflowAppGenerateTaskPipeline: task_id=self._application_generate_entity.task_id, workflow_node_execution=workflow_node_execution, ) + if isinstance(event, QueueNodeExceptionEvent): + self._save_output_for_event(event, workflow_node_execution.id) if node_failed_response: yield node_failed_response @@ -593,3 +601,15 @@ class WorkflowAppGenerateTaskPipeline: ) return response + + def _save_output_for_event(self, event: QueueNodeSucceededEvent | QueueNodeExceptionEvent, node_execution_id: str): + with Session(db.engine) as session, session.begin(): + saver = self._draft_var_saver_factory( + session=session, + app_id=self._application_generate_entity.app_config.app_id, + node_id=event.node_id, + node_type=event.node_type, + node_execution_id=node_execution_id, + enclosing_node_id=event.in_loop_id or event.in_iteration_id, + ) + saver.save(event.process_data, event.outputs) diff --git a/api/core/app/apps/workflow_app_runner.py b/api/core/app/apps/workflow_app_runner.py index facc24b4ca..17b9ac5827 100644 --- a/api/core/app/apps/workflow_app_runner.py +++ b/api/core/app/apps/workflow_app_runner.py @@ -62,6 +62,7 @@ from core.workflow.graph_engine.entities.event import ( from core.workflow.graph_engine.entities.graph import Graph from core.workflow.nodes import NodeType from core.workflow.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING +from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader, load_into_variable_pool from core.workflow.workflow_entry import WorkflowEntry from extensions.ext_database import db from models.model import App @@ -69,8 +70,12 @@ from models.workflow import Workflow class WorkflowBasedAppRunner(AppRunner): - def __init__(self, queue_manager: AppQueueManager): + def __init__(self, queue_manager: AppQueueManager, variable_loader: VariableLoader = DUMMY_VARIABLE_LOADER) -> None: self.queue_manager = queue_manager + self._variable_loader = variable_loader + + def _get_app_id(self) -> str: + raise NotImplementedError("not implemented") def _init_graph(self, graph_config: Mapping[str, Any]) -> Graph: """ @@ -173,6 +178,13 @@ class WorkflowBasedAppRunner(AppRunner): except NotImplementedError: variable_mapping = {} + load_into_variable_pool( + variable_loader=self._variable_loader, + variable_pool=variable_pool, + variable_mapping=variable_mapping, + user_inputs=user_inputs, + ) + WorkflowEntry.mapping_user_inputs_to_variable_pool( variable_mapping=variable_mapping, user_inputs=user_inputs, @@ -262,6 +274,12 @@ class WorkflowBasedAppRunner(AppRunner): ) except NotImplementedError: variable_mapping = {} + load_into_variable_pool( + self._variable_loader, + variable_pool=variable_pool, + variable_mapping=variable_mapping, + user_inputs=user_inputs, + ) WorkflowEntry.mapping_user_inputs_to_variable_pool( variable_mapping=variable_mapping, @@ -376,6 +394,7 @@ class WorkflowBasedAppRunner(AppRunner): in_loop_id=event.in_loop_id, ) ) + elif isinstance(event, NodeRunFailedEvent): self._publish_event( QueueNodeFailedEvent( @@ -438,6 +457,7 @@ class WorkflowBasedAppRunner(AppRunner): in_loop_id=event.in_loop_id, ) ) + elif isinstance(event, NodeInIterationFailedEvent): self._publish_event( QueueNodeInIterationFailedEvent( diff --git a/api/core/app/entities/app_invoke_entities.py b/api/core/app/entities/app_invoke_entities.py index c0d99693b0..65ed267959 100644 --- a/api/core/app/entities/app_invoke_entities.py +++ b/api/core/app/entities/app_invoke_entities.py @@ -17,9 +17,24 @@ class InvokeFrom(Enum): Invoke From. """ + # SERVICE_API indicates that this invocation is from an API call to Dify app. + # + # Description of service api in Dify docs: + # https://docs.dify.ai/en/guides/application-publishing/developing-with-apis SERVICE_API = "service-api" + + # WEB_APP indicates that this invocation is from + # the web app of the workflow (or chatflow). + # + # Description of web app in Dify docs: + # https://docs.dify.ai/en/guides/application-publishing/launch-your-webapp-quickly/README WEB_APP = "web-app" + + # EXPLORE indicates that this invocation is from + # the workflow (or chatflow) explore page. EXPLORE = "explore" + # DEBUGGER indicates that this invocation is from + # the workflow (or chatflow) edit page. DEBUGGER = "debugger" @classmethod diff --git a/api/core/app/task_pipeline/based_generate_task_pipeline.py b/api/core/app/task_pipeline/based_generate_task_pipeline.py index 5331c0cc94..3ed0c3352f 100644 --- a/api/core/app/task_pipeline/based_generate_task_pipeline.py +++ b/api/core/app/task_pipeline/based_generate_task_pipeline.py @@ -19,6 +19,7 @@ from core.app.entities.task_entities import ( from core.errors.error import QuotaExceededError from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError from core.moderation.output_moderation import ModerationRule, OutputModeration +from models.enums import MessageStatus from models.model import Message logger = logging.getLogger(__name__) @@ -62,7 +63,7 @@ class BasedGenerateTaskPipeline: return err err_desc = self._error_to_desc(err) - message.status = "error" + message.status = MessageStatus.ERROR message.error = err_desc return err diff --git a/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py b/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py index d535e1f835..3c8c7bb5a2 100644 --- a/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py +++ b/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py @@ -395,6 +395,7 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline): message.provider_response_latency = time.perf_counter() - self._start_at message.total_price = usage.total_price message.currency = usage.currency + self._task_state.llm_result.usage.latency = message.provider_response_latency message.message_metadata = self._task_state.metadata.model_dump_json() if trace_manager: diff --git a/api/core/entities/parameter_entities.py b/api/core/entities/parameter_entities.py index 36800bc263..b071bfa5b1 100644 --- a/api/core/entities/parameter_entities.py +++ b/api/core/entities/parameter_entities.py @@ -15,6 +15,11 @@ class CommonParameterType(StrEnum): MODEL_SELECTOR = "model-selector" TOOLS_SELECTOR = "array[tools]" + # Dynamic select parameter + # Once you are not sure about the available options until authorization is done + # eg: Select a Slack channel from a Slack workspace + DYNAMIC_SELECT = "dynamic-select" + # TOOL_SELECTOR = "tool-selector" diff --git a/api/core/file/constants.py b/api/core/file/constants.py index ce1d238e93..0665ed7e0d 100644 --- a/api/core/file/constants.py +++ b/api/core/file/constants.py @@ -1 +1,11 @@ +from typing import Any + +# TODO(QuantumGhost): Refactor variable type identification. Instead of directly +# comparing `dify_model_identity` with constants throughout the codebase, extract +# this logic into a dedicated function. This would encapsulate the implementation +# details of how different variable types are identified. FILE_MODEL_IDENTITY = "__dify__file__" + + +def maybe_file_object(o: Any) -> bool: + return isinstance(o, dict) and o.get("dify_model_identity") == FILE_MODEL_IDENTITY diff --git a/api/core/file/models.py b/api/core/file/models.py index aa3b5f629c..f61334e7bc 100644 --- a/api/core/file/models.py +++ b/api/core/file/models.py @@ -51,7 +51,7 @@ class File(BaseModel): # It should be set to `ToolFile.id` when `transfer_method` is `tool_file`. related_id: Optional[str] = None filename: Optional[str] = None - extension: Optional[str] = Field(default=None, description="File extension, should contains dot") + extension: Optional[str] = Field(default=None, description="File extension, should contain dot") mime_type: Optional[str] = None size: int = -1 diff --git a/api/core/file/upload_file_parser.py b/api/core/file/upload_file_parser.py deleted file mode 100644 index 96b2884811..0000000000 --- a/api/core/file/upload_file_parser.py +++ /dev/null @@ -1,67 +0,0 @@ -import base64 -import logging -import time -from typing import Optional - -from configs import dify_config -from constants import IMAGE_EXTENSIONS -from core.helper.url_signer import UrlSigner -from extensions.ext_storage import storage - - -class UploadFileParser: - @classmethod - def get_image_data(cls, upload_file, force_url: bool = False) -> Optional[str]: - if not upload_file: - return None - - if upload_file.extension not in IMAGE_EXTENSIONS: - return None - - if dify_config.MULTIMODAL_SEND_FORMAT == "url" or force_url: - return cls.get_signed_temp_image_url(upload_file.id) - else: - # get image file base64 - try: - data = storage.load(upload_file.key) - except FileNotFoundError: - logging.exception(f"File not found: {upload_file.key}") - return None - - encoded_string = base64.b64encode(data).decode("utf-8") - return f"data:{upload_file.mime_type};base64,{encoded_string}" - - @classmethod - def get_signed_temp_image_url(cls, upload_file_id) -> str: - """ - get signed url from upload file - - :param upload_file_id: the id of UploadFile object - :return: - """ - base_url = dify_config.FILES_URL - image_preview_url = f"{base_url}/files/{upload_file_id}/image-preview" - - return UrlSigner.get_signed_url(url=image_preview_url, sign_key=upload_file_id, prefix="image-preview") - - @classmethod - def verify_image_file_signature(cls, upload_file_id: str, timestamp: str, nonce: str, sign: str) -> bool: - """ - verify signature - - :param upload_file_id: file id - :param timestamp: timestamp - :param nonce: nonce - :param sign: signature - :return: - """ - result = UrlSigner.verify( - sign_key=upload_file_id, timestamp=timestamp, nonce=nonce, sign=sign, prefix="image-preview" - ) - - # verify signature - if not result: - return False - - current_time = int(time.time()) - return current_time - int(timestamp) <= dify_config.FILES_ACCESS_TIMEOUT diff --git a/api/core/helper/code_executor/template_transformer.py b/api/core/helper/code_executor/template_transformer.py index baa792b5bc..84f212a9c1 100644 --- a/api/core/helper/code_executor/template_transformer.py +++ b/api/core/helper/code_executor/template_transformer.py @@ -28,7 +28,7 @@ class TemplateTransformer(ABC): def extract_result_str_from_response(cls, response: str): result = re.search(rf"{cls._result_tag}(.*){cls._result_tag}", response, re.DOTALL) if not result: - raise ValueError("Failed to parse result") + raise ValueError(f"Failed to parse result: no result tag found in response. Response: {response[:200]}...") return result.group(1) @classmethod @@ -38,16 +38,53 @@ class TemplateTransformer(ABC): :param response: response :return: """ + try: - result = json.loads(cls.extract_result_str_from_response(response)) - except json.JSONDecodeError: - raise ValueError("failed to parse response") + result_str = cls.extract_result_str_from_response(response) + result = json.loads(result_str) + except json.JSONDecodeError as e: + raise ValueError(f"Failed to parse JSON response: {str(e)}. Response content: {result_str[:200]}...") + except ValueError as e: + # Re-raise ValueError from extract_result_str_from_response + raise e + except Exception as e: + raise ValueError(f"Unexpected error during response transformation: {str(e)}") + + # Check if the result contains an error + if isinstance(result, dict) and "error" in result: + raise ValueError(f"JavaScript execution error: {result['error']}") + if not isinstance(result, dict): - raise ValueError("result must be a dict") + raise ValueError(f"Result must be a dict, got {type(result).__name__}") if not all(isinstance(k, str) for k in result): - raise ValueError("result keys must be strings") + raise ValueError("Result keys must be strings") + + # Post-process the result to convert scientific notation strings back to numbers + result = cls._post_process_result(result) return result + @classmethod + def _post_process_result(cls, result: dict[Any, Any]) -> dict[Any, Any]: + """ + Post-process the result to convert scientific notation strings back to numbers + """ + + def convert_scientific_notation(value): + if isinstance(value, str): + # Check if the string looks like scientific notation + if re.match(r"^-?\d+\.?\d*e[+-]\d+$", value, re.IGNORECASE): + try: + return float(value) + except ValueError: + pass + elif isinstance(value, dict): + return {k: convert_scientific_notation(v) for k, v in value.items()} + elif isinstance(value, list): + return [convert_scientific_notation(v) for v in value] + return value + + return convert_scientific_notation(result) # type: ignore[no-any-return] + @classmethod @abstractmethod def get_runner_script(cls) -> str: diff --git a/api/core/helper/lru_cache.py b/api/core/helper/lru_cache.py deleted file mode 100644 index 81501d2e4e..0000000000 --- a/api/core/helper/lru_cache.py +++ /dev/null @@ -1,22 +0,0 @@ -from collections import OrderedDict -from typing import Any - - -class LRUCache: - def __init__(self, capacity: int): - self.cache: OrderedDict[Any, Any] = OrderedDict() - self.capacity = capacity - - def get(self, key: Any) -> Any: - if key not in self.cache: - return None - else: - self.cache.move_to_end(key) # move the key to the end of the OrderedDict - return self.cache[key] - - def put(self, key: Any, value: Any) -> None: - if key in self.cache: - self.cache.move_to_end(key) - self.cache[key] = value - if len(self.cache) > self.capacity: - self.cache.popitem(last=False) # pop the first item diff --git a/api/core/indexing_runner.py b/api/core/indexing_runner.py index 848d897779..305a9190d5 100644 --- a/api/core/indexing_runner.py +++ b/api/core/indexing_runner.py @@ -317,9 +317,10 @@ class IndexingRunner: image_upload_file_ids = get_image_upload_file_ids(document.page_content) for upload_file_id in image_upload_file_ids: image_file = db.session.query(UploadFile).filter(UploadFile.id == upload_file_id).first() + if image_file is None: + continue try: - if image_file: - storage.delete(image_file.key) + storage.delete(image_file.key) except Exception: logging.exception( "Delete image_files failed while indexing_estimate, \ @@ -534,7 +535,7 @@ class IndexingRunner: # chunk nodes by chunk size indexing_start_at = time.perf_counter() tokens = 0 - if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX: + if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX and dataset.indexing_technique == "economy": # create keyword index create_keyword_thread = threading.Thread( target=self._process_keyword_index, @@ -572,7 +573,7 @@ class IndexingRunner: for future in futures: tokens += future.result() - if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX: + if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX and dataset.indexing_technique == "economy": create_keyword_thread.join() indexing_end_at = time.perf_counter() diff --git a/api/core/llm_generator/output_parser/structured_output.py b/api/core/llm_generator/output_parser/structured_output.py new file mode 100644 index 0000000000..151cef1bc3 --- /dev/null +++ b/api/core/llm_generator/output_parser/structured_output.py @@ -0,0 +1,380 @@ +import json +from collections.abc import Generator, Mapping, Sequence +from copy import deepcopy +from enum import StrEnum +from typing import Any, Literal, Optional, cast, overload + +import json_repair +from pydantic import TypeAdapter, ValidationError + +from core.llm_generator.output_parser.errors import OutputParserError +from core.llm_generator.prompts import STRUCTURED_OUTPUT_PROMPT +from core.model_manager import ModelInstance +from core.model_runtime.callbacks.base_callback import Callback +from core.model_runtime.entities.llm_entities import ( + LLMResult, + LLMResultChunk, + LLMResultChunkDelta, + LLMResultChunkWithStructuredOutput, + LLMResultWithStructuredOutput, +) +from core.model_runtime.entities.message_entities import ( + AssistantPromptMessage, + PromptMessage, + PromptMessageTool, + SystemPromptMessage, + TextPromptMessageContent, +) +from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule + + +class ResponseFormat(StrEnum): + """Constants for model response formats""" + + JSON_SCHEMA = "json_schema" # model's structured output mode. some model like gemini, gpt-4o, support this mode. + JSON = "JSON" # model's json mode. some model like claude support this mode. + JSON_OBJECT = "json_object" # json mode's another alias. some model like deepseek-chat, qwen use this alias. + + +class SpecialModelType(StrEnum): + """Constants for identifying model types""" + + GEMINI = "gemini" + OLLAMA = "ollama" + + +@overload +def invoke_llm_with_structured_output( + provider: str, + model_schema: AIModelEntity, + model_instance: ModelInstance, + prompt_messages: Sequence[PromptMessage], + json_schema: Mapping[str, Any], + model_parameters: Optional[Mapping] = None, + tools: Sequence[PromptMessageTool] | None = None, + stop: Optional[list[str]] = None, + stream: Literal[True] = True, + user: Optional[str] = None, + callbacks: Optional[list[Callback]] = None, +) -> Generator[LLMResultChunkWithStructuredOutput, None, None]: ... + + +@overload +def invoke_llm_with_structured_output( + provider: str, + model_schema: AIModelEntity, + model_instance: ModelInstance, + prompt_messages: Sequence[PromptMessage], + json_schema: Mapping[str, Any], + model_parameters: Optional[Mapping] = None, + tools: Sequence[PromptMessageTool] | None = None, + stop: Optional[list[str]] = None, + stream: Literal[False] = False, + user: Optional[str] = None, + callbacks: Optional[list[Callback]] = None, +) -> LLMResultWithStructuredOutput: ... + + +@overload +def invoke_llm_with_structured_output( + provider: str, + model_schema: AIModelEntity, + model_instance: ModelInstance, + prompt_messages: Sequence[PromptMessage], + json_schema: Mapping[str, Any], + model_parameters: Optional[Mapping] = None, + tools: Sequence[PromptMessageTool] | None = None, + stop: Optional[list[str]] = None, + stream: bool = True, + user: Optional[str] = None, + callbacks: Optional[list[Callback]] = None, +) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]: ... + + +def invoke_llm_with_structured_output( + provider: str, + model_schema: AIModelEntity, + model_instance: ModelInstance, + prompt_messages: Sequence[PromptMessage], + json_schema: Mapping[str, Any], + model_parameters: Optional[Mapping] = None, + tools: Sequence[PromptMessageTool] | None = None, + stop: Optional[list[str]] = None, + stream: bool = True, + user: Optional[str] = None, + callbacks: Optional[list[Callback]] = None, +) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]: + """ + Invoke large language model with structured output + 1. This method invokes model_instance.invoke_llm with json_schema + 2. Try to parse the result as structured output + + :param prompt_messages: prompt messages + :param json_schema: json schema + :param model_parameters: model parameters + :param tools: tools for tool calling + :param stop: stop words + :param stream: is stream response + :param user: unique user id + :param callbacks: callbacks + :return: full response or stream response chunk generator result + """ + + # handle native json schema + model_parameters_with_json_schema: dict[str, Any] = { + **(model_parameters or {}), + } + + if model_schema.support_structure_output: + model_parameters = _handle_native_json_schema( + provider, model_schema, json_schema, model_parameters_with_json_schema, model_schema.parameter_rules + ) + else: + # Set appropriate response format based on model capabilities + _set_response_format(model_parameters_with_json_schema, model_schema.parameter_rules) + + # handle prompt based schema + prompt_messages = _handle_prompt_based_schema( + prompt_messages=prompt_messages, + structured_output_schema=json_schema, + ) + + llm_result = model_instance.invoke_llm( + prompt_messages=list(prompt_messages), + model_parameters=model_parameters_with_json_schema, + tools=tools, + stop=stop, + stream=stream, + user=user, + callbacks=callbacks, + ) + + if isinstance(llm_result, LLMResult): + if not isinstance(llm_result.message.content, str): + raise OutputParserError( + f"Failed to parse structured output, LLM result is not a string: {llm_result.message.content}" + ) + + return LLMResultWithStructuredOutput( + structured_output=_parse_structured_output(llm_result.message.content), + model=llm_result.model, + message=llm_result.message, + usage=llm_result.usage, + system_fingerprint=llm_result.system_fingerprint, + prompt_messages=llm_result.prompt_messages, + ) + else: + + def generator() -> Generator[LLMResultChunkWithStructuredOutput, None, None]: + result_text: str = "" + prompt_messages: Sequence[PromptMessage] = [] + system_fingerprint: Optional[str] = None + for event in llm_result: + if isinstance(event, LLMResultChunk): + prompt_messages = event.prompt_messages + system_fingerprint = event.system_fingerprint + + if isinstance(event.delta.message.content, str): + result_text += event.delta.message.content + elif isinstance(event.delta.message.content, list): + for item in event.delta.message.content: + if isinstance(item, TextPromptMessageContent): + result_text += item.data + + yield LLMResultChunkWithStructuredOutput( + model=model_schema.model, + prompt_messages=prompt_messages, + system_fingerprint=system_fingerprint, + delta=event.delta, + ) + + yield LLMResultChunkWithStructuredOutput( + structured_output=_parse_structured_output(result_text), + model=model_schema.model, + prompt_messages=prompt_messages, + system_fingerprint=system_fingerprint, + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage(content=""), + usage=None, + finish_reason=None, + ), + ) + + return generator() + + +def _handle_native_json_schema( + provider: str, + model_schema: AIModelEntity, + structured_output_schema: Mapping, + model_parameters: dict, + rules: list[ParameterRule], +) -> dict: + """ + Handle structured output for models with native JSON schema support. + + :param model_parameters: Model parameters to update + :param rules: Model parameter rules + :return: Updated model parameters with JSON schema configuration + """ + # Process schema according to model requirements + schema_json = _prepare_schema_for_model(provider, model_schema, structured_output_schema) + + # Set JSON schema in parameters + model_parameters["json_schema"] = json.dumps(schema_json, ensure_ascii=False) + + # Set appropriate response format if required by the model + for rule in rules: + if rule.name == "response_format" and ResponseFormat.JSON_SCHEMA.value in rule.options: + model_parameters["response_format"] = ResponseFormat.JSON_SCHEMA.value + + return model_parameters + + +def _set_response_format(model_parameters: dict, rules: list) -> None: + """ + Set the appropriate response format parameter based on model rules. + + :param model_parameters: Model parameters to update + :param rules: Model parameter rules + """ + for rule in rules: + if rule.name == "response_format": + if ResponseFormat.JSON.value in rule.options: + model_parameters["response_format"] = ResponseFormat.JSON.value + elif ResponseFormat.JSON_OBJECT.value in rule.options: + model_parameters["response_format"] = ResponseFormat.JSON_OBJECT.value + + +def _handle_prompt_based_schema( + prompt_messages: Sequence[PromptMessage], structured_output_schema: Mapping +) -> list[PromptMessage]: + """ + Handle structured output for models without native JSON schema support. + This function modifies the prompt messages to include schema-based output requirements. + + Args: + prompt_messages: Original sequence of prompt messages + + Returns: + list[PromptMessage]: Updated prompt messages with structured output requirements + """ + # Convert schema to string format + schema_str = json.dumps(structured_output_schema, ensure_ascii=False) + + # Find existing system prompt with schema placeholder + system_prompt = next( + (prompt for prompt in prompt_messages if isinstance(prompt, SystemPromptMessage)), + None, + ) + structured_output_prompt = STRUCTURED_OUTPUT_PROMPT.replace("{{schema}}", schema_str) + # Prepare system prompt content + system_prompt_content = ( + structured_output_prompt + "\n\n" + system_prompt.content + if system_prompt and isinstance(system_prompt.content, str) + else structured_output_prompt + ) + system_prompt = SystemPromptMessage(content=system_prompt_content) + + # Extract content from the last user message + + filtered_prompts = [prompt for prompt in prompt_messages if not isinstance(prompt, SystemPromptMessage)] + updated_prompt = [system_prompt] + filtered_prompts + + return updated_prompt + + +def _parse_structured_output(result_text: str) -> Mapping[str, Any]: + structured_output: Mapping[str, Any] = {} + parsed: Mapping[str, Any] = {} + try: + parsed = TypeAdapter(Mapping).validate_json(result_text) + if not isinstance(parsed, dict): + raise OutputParserError(f"Failed to parse structured output: {result_text}") + structured_output = parsed + except ValidationError: + # if the result_text is not a valid json, try to repair it + temp_parsed = json_repair.loads(result_text) + if not isinstance(temp_parsed, dict): + # handle reasoning model like deepseek-r1 got '\n\n\n' prefix + if isinstance(temp_parsed, list): + temp_parsed = next((item for item in temp_parsed if isinstance(item, dict)), {}) + else: + raise OutputParserError(f"Failed to parse structured output: {result_text}") + structured_output = cast(dict, temp_parsed) + return structured_output + + +def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema: Mapping) -> dict: + """ + Prepare JSON schema based on model requirements. + + Different models have different requirements for JSON schema formatting. + This function handles these differences. + + :param schema: The original JSON schema + :return: Processed schema compatible with the current model + """ + + # Deep copy to avoid modifying the original schema + processed_schema = dict(deepcopy(schema)) + + # Convert boolean types to string types (common requirement) + convert_boolean_to_string(processed_schema) + + # Apply model-specific transformations + if SpecialModelType.GEMINI in model_schema.model: + remove_additional_properties(processed_schema) + return processed_schema + elif SpecialModelType.OLLAMA in provider: + return processed_schema + else: + # Default format with name field + return {"schema": processed_schema, "name": "llm_response"} + + +def remove_additional_properties(schema: dict) -> None: + """ + Remove additionalProperties fields from JSON schema. + Used for models like Gemini that don't support this property. + + :param schema: JSON schema to modify in-place + """ + if not isinstance(schema, dict): + return + + # Remove additionalProperties at current level + schema.pop("additionalProperties", None) + + # Process nested structures recursively + for value in schema.values(): + if isinstance(value, dict): + remove_additional_properties(value) + elif isinstance(value, list): + for item in value: + if isinstance(item, dict): + remove_additional_properties(item) + + +def convert_boolean_to_string(schema: dict) -> None: + """ + Convert boolean type specifications to string in JSON schema. + + :param schema: JSON schema to modify in-place + """ + if not isinstance(schema, dict): + return + + # Check for boolean type at current level + if schema.get("type") == "boolean": + schema["type"] = "string" + + # Process nested dictionaries and lists recursively + for value in schema.values(): + if isinstance(value, dict): + convert_boolean_to_string(value) + elif isinstance(value, list): + for item in value: + if isinstance(item, dict): + convert_boolean_to_string(item) diff --git a/api/core/llm_generator/prompts.py b/api/core/llm_generator/prompts.py index ddfa1e7a66..ef81e38dc5 100644 --- a/api/core/llm_generator/prompts.py +++ b/api/core/llm_generator/prompts.py @@ -291,3 +291,21 @@ Your task is to convert simple user descriptions into properly formatted JSON Sc Now, generate a JSON Schema based on my description """ # noqa: E501 + +STRUCTURED_OUTPUT_PROMPT = """You’re a helpful AI assistant. You could answer questions and output in JSON format. +constraints: + - You must output in JSON format. + - Do not output boolean value, use string type instead. + - Do not output integer or float value, use number type instead. +eg: + Here is the JSON schema: + {"additionalProperties": false, "properties": {"age": {"type": "number"}, "name": {"type": "string"}}, "required": ["name", "age"], "type": "object"} + + Here is the user's question: + My name is John Doe and I am 30 years old. + + output: + {"name": "John Doe", "age": 30} +Here is the JSON schema: +{{schema}} +""" # noqa: E501 diff --git a/api/core/model_runtime/entities/llm_entities.py b/api/core/model_runtime/entities/llm_entities.py index de5a748d4f..ace2c1f770 100644 --- a/api/core/model_runtime/entities/llm_entities.py +++ b/api/core/model_runtime/entities/llm_entities.py @@ -1,7 +1,7 @@ -from collections.abc import Sequence +from collections.abc import Mapping, Sequence from decimal import Decimal from enum import StrEnum -from typing import Optional +from typing import Any, Optional from pydantic import BaseModel, Field @@ -53,6 +53,37 @@ class LLMUsage(ModelUsage): latency=0.0, ) + @classmethod + def from_metadata(cls, metadata: dict) -> "LLMUsage": + """ + Create LLMUsage instance from metadata dictionary with default values. + + Args: + metadata: Dictionary containing usage metadata + + Returns: + LLMUsage instance with values from metadata or defaults + """ + total_tokens = metadata.get("total_tokens", 0) + completion_tokens = metadata.get("completion_tokens", 0) + if total_tokens > 0 and completion_tokens == 0: + completion_tokens = total_tokens + + return cls( + prompt_tokens=metadata.get("prompt_tokens", 0), + completion_tokens=completion_tokens, + total_tokens=total_tokens, + prompt_unit_price=Decimal(str(metadata.get("prompt_unit_price", 0))), + completion_unit_price=Decimal(str(metadata.get("completion_unit_price", 0))), + total_price=Decimal(str(metadata.get("total_price", 0))), + currency=metadata.get("currency", "USD"), + prompt_price_unit=Decimal(str(metadata.get("prompt_price_unit", 0))), + completion_price_unit=Decimal(str(metadata.get("completion_price_unit", 0))), + prompt_price=Decimal(str(metadata.get("prompt_price", 0))), + completion_price=Decimal(str(metadata.get("completion_price", 0))), + latency=metadata.get("latency", 0.0), + ) + def plus(self, other: "LLMUsage") -> "LLMUsage": """ Add two LLMUsage instances together. @@ -101,6 +132,20 @@ class LLMResult(BaseModel): system_fingerprint: Optional[str] = None +class LLMStructuredOutput(BaseModel): + """ + Model class for llm structured output. + """ + + structured_output: Optional[Mapping[str, Any]] = None + + +class LLMResultWithStructuredOutput(LLMResult, LLMStructuredOutput): + """ + Model class for llm result with structured output. + """ + + class LLMResultChunkDelta(BaseModel): """ Model class for llm result chunk delta. @@ -123,6 +168,12 @@ class LLMResultChunk(BaseModel): delta: LLMResultChunkDelta +class LLMResultChunkWithStructuredOutput(LLMResultChunk, LLMStructuredOutput): + """ + Model class for llm result chunk with structured output. + """ + + class NumTokensResult(PriceInfo): """ Model class for number of tokens result. diff --git a/api/core/ops/aliyun_trace/__init__.py b/api/core/ops/aliyun_trace/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/core/ops/aliyun_trace/aliyun_trace.py b/api/core/ops/aliyun_trace/aliyun_trace.py new file mode 100644 index 0000000000..b18a6905fe --- /dev/null +++ b/api/core/ops/aliyun_trace/aliyun_trace.py @@ -0,0 +1,487 @@ +import json +import logging +from collections.abc import Sequence +from typing import Optional +from urllib.parse import urljoin + +from opentelemetry.trace import Status, StatusCode +from sqlalchemy.orm import Session, sessionmaker + +from core.ops.aliyun_trace.data_exporter.traceclient import ( + TraceClient, + convert_datetime_to_nanoseconds, + convert_to_span_id, + convert_to_trace_id, + generate_span_id, +) +from core.ops.aliyun_trace.entities.aliyun_trace_entity import SpanData +from core.ops.aliyun_trace.entities.semconv import ( + GEN_AI_COMPLETION, + GEN_AI_FRAMEWORK, + GEN_AI_MODEL_NAME, + GEN_AI_PROMPT, + GEN_AI_PROMPT_TEMPLATE_TEMPLATE, + GEN_AI_PROMPT_TEMPLATE_VARIABLE, + GEN_AI_RESPONSE_FINISH_REASON, + GEN_AI_SESSION_ID, + GEN_AI_SPAN_KIND, + GEN_AI_SYSTEM, + GEN_AI_USAGE_INPUT_TOKENS, + GEN_AI_USAGE_OUTPUT_TOKENS, + GEN_AI_USAGE_TOTAL_TOKENS, + GEN_AI_USER_ID, + INPUT_VALUE, + OUTPUT_VALUE, + RETRIEVAL_DOCUMENT, + RETRIEVAL_QUERY, + TOOL_DESCRIPTION, + TOOL_NAME, + TOOL_PARAMETERS, + GenAISpanKind, +) +from core.ops.base_trace_instance import BaseTraceInstance +from core.ops.entities.config_entity import AliyunConfig +from core.ops.entities.trace_entity import ( + BaseTraceInfo, + DatasetRetrievalTraceInfo, + GenerateNameTraceInfo, + MessageTraceInfo, + ModerationTraceInfo, + SuggestedQuestionTraceInfo, + ToolTraceInfo, + WorkflowTraceInfo, +) +from core.rag.models.document import Document +from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository +from core.workflow.entities.workflow_node_execution import ( + WorkflowNodeExecution, + WorkflowNodeExecutionMetadataKey, + WorkflowNodeExecutionStatus, +) +from core.workflow.nodes import NodeType +from models import Account, App, EndUser, TenantAccountJoin, WorkflowNodeExecutionTriggeredFrom, db + +logger = logging.getLogger(__name__) + + +class AliyunDataTrace(BaseTraceInstance): + def __init__( + self, + aliyun_config: AliyunConfig, + ): + super().__init__(aliyun_config) + base_url = aliyun_config.endpoint.rstrip("/") + endpoint = urljoin(base_url, f"adapt_{aliyun_config.license_key}/api/otlp/traces") + self.trace_client = TraceClient(service_name=aliyun_config.app_name, endpoint=endpoint) + + def trace(self, trace_info: BaseTraceInfo): + if isinstance(trace_info, WorkflowTraceInfo): + self.workflow_trace(trace_info) + if isinstance(trace_info, MessageTraceInfo): + self.message_trace(trace_info) + if isinstance(trace_info, ModerationTraceInfo): + pass + if isinstance(trace_info, SuggestedQuestionTraceInfo): + self.suggested_question_trace(trace_info) + if isinstance(trace_info, DatasetRetrievalTraceInfo): + self.dataset_retrieval_trace(trace_info) + if isinstance(trace_info, ToolTraceInfo): + self.tool_trace(trace_info) + if isinstance(trace_info, GenerateNameTraceInfo): + pass + + def api_check(self): + return self.trace_client.api_check() + + def get_project_url(self): + try: + return self.trace_client.get_project_url() + except Exception as e: + logger.info(f"Aliyun get run url failed: {str(e)}", exc_info=True) + raise ValueError(f"Aliyun get run url failed: {str(e)}") + + def workflow_trace(self, trace_info: WorkflowTraceInfo): + trace_id = convert_to_trace_id(trace_info.workflow_run_id) + workflow_span_id = convert_to_span_id(trace_info.workflow_run_id, "workflow") + self.add_workflow_span(trace_id, workflow_span_id, trace_info) + + workflow_node_executions = self.get_workflow_node_executions(trace_info) + for node_execution in workflow_node_executions: + node_span = self.build_workflow_node_span(node_execution, trace_id, trace_info, workflow_span_id) + self.trace_client.add_span(node_span) + + def message_trace(self, trace_info: MessageTraceInfo): + message_data = trace_info.message_data + if message_data is None: + return + message_id = trace_info.message_id + + user_id = message_data.from_account_id + if message_data.from_end_user_id: + end_user_data: Optional[EndUser] = ( + db.session.query(EndUser).filter(EndUser.id == message_data.from_end_user_id).first() + ) + if end_user_data is not None: + user_id = end_user_data.session_id + + status: Status = Status(StatusCode.OK) + if trace_info.error: + status = Status(StatusCode.ERROR, trace_info.error) + + trace_id = convert_to_trace_id(message_id) + message_span_id = convert_to_span_id(message_id, "message") + message_span = SpanData( + trace_id=trace_id, + parent_span_id=None, + span_id=message_span_id, + name="message", + start_time=convert_datetime_to_nanoseconds(trace_info.start_time), + end_time=convert_datetime_to_nanoseconds(trace_info.end_time), + attributes={ + GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id", ""), + GEN_AI_USER_ID: str(user_id), + GEN_AI_SPAN_KIND: GenAISpanKind.CHAIN.value, + GEN_AI_FRAMEWORK: "dify", + INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + OUTPUT_VALUE: str(trace_info.outputs), + }, + status=status, + ) + self.trace_client.add_span(message_span) + + app_model_config = getattr(trace_info.message_data, "app_model_config", {}) + pre_prompt = getattr(app_model_config, "pre_prompt", "") + inputs_data = getattr(trace_info.message_data, "inputs", {}) + llm_span = SpanData( + trace_id=trace_id, + parent_span_id=message_span_id, + span_id=convert_to_span_id(message_id, "llm"), + name="llm", + start_time=convert_datetime_to_nanoseconds(trace_info.start_time), + end_time=convert_datetime_to_nanoseconds(trace_info.end_time), + attributes={ + GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id", ""), + GEN_AI_USER_ID: str(user_id), + GEN_AI_SPAN_KIND: GenAISpanKind.LLM.value, + GEN_AI_FRAMEWORK: "dify", + GEN_AI_MODEL_NAME: trace_info.metadata.get("ls_model_name", ""), + GEN_AI_SYSTEM: trace_info.metadata.get("ls_provider", ""), + GEN_AI_USAGE_INPUT_TOKENS: str(trace_info.message_tokens), + GEN_AI_USAGE_OUTPUT_TOKENS: str(trace_info.answer_tokens), + GEN_AI_USAGE_TOTAL_TOKENS: str(trace_info.total_tokens), + GEN_AI_PROMPT_TEMPLATE_VARIABLE: json.dumps(inputs_data, ensure_ascii=False), + GEN_AI_PROMPT_TEMPLATE_TEMPLATE: pre_prompt, + GEN_AI_PROMPT: json.dumps(trace_info.inputs, ensure_ascii=False), + GEN_AI_COMPLETION: str(trace_info.outputs), + INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + OUTPUT_VALUE: str(trace_info.outputs), + }, + status=status, + ) + self.trace_client.add_span(llm_span) + + def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo): + if trace_info.message_data is None: + return + message_id = trace_info.message_id + + documents_data = extract_retrieval_documents(trace_info.documents) + dataset_retrieval_span = SpanData( + trace_id=convert_to_trace_id(message_id), + parent_span_id=convert_to_span_id(message_id, "message"), + span_id=generate_span_id(), + name="dataset_retrieval", + start_time=convert_datetime_to_nanoseconds(trace_info.start_time), + end_time=convert_datetime_to_nanoseconds(trace_info.end_time), + attributes={ + GEN_AI_SPAN_KIND: GenAISpanKind.RETRIEVER.value, + GEN_AI_FRAMEWORK: "dify", + RETRIEVAL_QUERY: str(trace_info.inputs), + RETRIEVAL_DOCUMENT: json.dumps(documents_data, ensure_ascii=False), + INPUT_VALUE: str(trace_info.inputs), + OUTPUT_VALUE: json.dumps(documents_data, ensure_ascii=False), + }, + ) + self.trace_client.add_span(dataset_retrieval_span) + + def tool_trace(self, trace_info: ToolTraceInfo): + if trace_info.message_data is None: + return + message_id = trace_info.message_id + + status: Status = Status(StatusCode.OK) + if trace_info.error: + status = Status(StatusCode.ERROR, trace_info.error) + + tool_span = SpanData( + trace_id=convert_to_trace_id(message_id), + parent_span_id=convert_to_span_id(message_id, "message"), + span_id=generate_span_id(), + name=trace_info.tool_name, + start_time=convert_datetime_to_nanoseconds(trace_info.start_time), + end_time=convert_datetime_to_nanoseconds(trace_info.end_time), + attributes={ + GEN_AI_SPAN_KIND: GenAISpanKind.TOOL.value, + GEN_AI_FRAMEWORK: "dify", + TOOL_NAME: trace_info.tool_name, + TOOL_DESCRIPTION: json.dumps(trace_info.tool_config, ensure_ascii=False), + TOOL_PARAMETERS: json.dumps(trace_info.tool_inputs, ensure_ascii=False), + INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + OUTPUT_VALUE: str(trace_info.tool_outputs), + }, + status=status, + ) + self.trace_client.add_span(tool_span) + + def get_workflow_node_executions(self, trace_info: WorkflowTraceInfo) -> Sequence[WorkflowNodeExecution]: + # through workflow_run_id get all_nodes_execution using repository + session_factory = sessionmaker(bind=db.engine) + # Find the app's creator account + with Session(db.engine, expire_on_commit=False) as session: + # Get the app to find its creator + app_id = trace_info.metadata.get("app_id") + if not app_id: + raise ValueError("No app_id found in trace_info metadata") + + app = session.query(App).filter(App.id == app_id).first() + if not app: + raise ValueError(f"App with id {app_id} not found") + + if not app.created_by: + raise ValueError(f"App with id {app_id} has no creator (created_by is None)") + + service_account = session.query(Account).filter(Account.id == app.created_by).first() + if not service_account: + raise ValueError(f"Creator account with id {app.created_by} not found for app {app_id}") + current_tenant = ( + session.query(TenantAccountJoin).filter_by(account_id=service_account.id, current=True).first() + ) + if not current_tenant: + raise ValueError(f"Current tenant not found for account {service_account.id}") + service_account.set_tenant_id(current_tenant.tenant_id) + workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository( + session_factory=session_factory, + user=service_account, + app_id=trace_info.metadata.get("app_id"), + triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN, + ) + # Get all executions for this workflow run + workflow_node_executions = workflow_node_execution_repository.get_by_workflow_run( + workflow_run_id=trace_info.workflow_run_id + ) + return workflow_node_executions + + def build_workflow_node_span( + self, node_execution: WorkflowNodeExecution, trace_id: int, trace_info: WorkflowTraceInfo, workflow_span_id: int + ): + try: + if node_execution.node_type == NodeType.LLM: + node_span = self.build_workflow_llm_span(trace_id, workflow_span_id, trace_info, node_execution) + elif node_execution.node_type == NodeType.KNOWLEDGE_RETRIEVAL: + node_span = self.build_workflow_retrieval_span(trace_id, workflow_span_id, trace_info, node_execution) + elif node_execution.node_type == NodeType.TOOL: + node_span = self.build_workflow_tool_span(trace_id, workflow_span_id, trace_info, node_execution) + else: + node_span = self.build_workflow_task_span(trace_id, workflow_span_id, trace_info, node_execution) + return node_span + except Exception: + return None + + def get_workflow_node_status(self, node_execution: WorkflowNodeExecution) -> Status: + span_status: Status = Status(StatusCode.UNSET) + if node_execution.status == WorkflowNodeExecutionStatus.SUCCEEDED: + span_status = Status(StatusCode.OK) + elif node_execution.status in [WorkflowNodeExecutionStatus.FAILED, WorkflowNodeExecutionStatus.EXCEPTION]: + span_status = Status(StatusCode.ERROR, str(node_execution.error)) + return span_status + + def build_workflow_task_span( + self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo, node_execution: WorkflowNodeExecution + ) -> SpanData: + return SpanData( + trace_id=trace_id, + parent_span_id=workflow_span_id, + span_id=convert_to_span_id(node_execution.id, "node"), + name=node_execution.title, + start_time=convert_datetime_to_nanoseconds(node_execution.created_at), + end_time=convert_datetime_to_nanoseconds(node_execution.finished_at), + attributes={ + GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id", ""), + GEN_AI_SPAN_KIND: GenAISpanKind.TASK.value, + GEN_AI_FRAMEWORK: "dify", + INPUT_VALUE: json.dumps(node_execution.inputs, ensure_ascii=False), + OUTPUT_VALUE: json.dumps(node_execution.outputs, ensure_ascii=False), + }, + status=self.get_workflow_node_status(node_execution), + ) + + def build_workflow_tool_span( + self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo, node_execution: WorkflowNodeExecution + ) -> SpanData: + tool_des = {} + if node_execution.metadata: + tool_des = node_execution.metadata.get(WorkflowNodeExecutionMetadataKey.TOOL_INFO, {}) + return SpanData( + trace_id=trace_id, + parent_span_id=workflow_span_id, + span_id=convert_to_span_id(node_execution.id, "node"), + name=node_execution.title, + start_time=convert_datetime_to_nanoseconds(node_execution.created_at), + end_time=convert_datetime_to_nanoseconds(node_execution.finished_at), + attributes={ + GEN_AI_SPAN_KIND: GenAISpanKind.TOOL.value, + GEN_AI_FRAMEWORK: "dify", + TOOL_NAME: node_execution.title, + TOOL_DESCRIPTION: json.dumps(tool_des, ensure_ascii=False), + TOOL_PARAMETERS: json.dumps(node_execution.inputs if node_execution.inputs else {}, ensure_ascii=False), + INPUT_VALUE: json.dumps(node_execution.inputs if node_execution.inputs else {}, ensure_ascii=False), + OUTPUT_VALUE: json.dumps(node_execution.outputs, ensure_ascii=False), + }, + status=self.get_workflow_node_status(node_execution), + ) + + def build_workflow_retrieval_span( + self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo, node_execution: WorkflowNodeExecution + ) -> SpanData: + input_value = "" + if node_execution.inputs: + input_value = str(node_execution.inputs.get("query", "")) + output_value = "" + if node_execution.outputs: + output_value = json.dumps(node_execution.outputs.get("result", []), ensure_ascii=False) + return SpanData( + trace_id=trace_id, + parent_span_id=workflow_span_id, + span_id=convert_to_span_id(node_execution.id, "node"), + name=node_execution.title, + start_time=convert_datetime_to_nanoseconds(node_execution.created_at), + end_time=convert_datetime_to_nanoseconds(node_execution.finished_at), + attributes={ + GEN_AI_SPAN_KIND: GenAISpanKind.RETRIEVER.value, + GEN_AI_FRAMEWORK: "dify", + RETRIEVAL_QUERY: input_value, + RETRIEVAL_DOCUMENT: output_value, + INPUT_VALUE: input_value, + OUTPUT_VALUE: output_value, + }, + status=self.get_workflow_node_status(node_execution), + ) + + def build_workflow_llm_span( + self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo, node_execution: WorkflowNodeExecution + ) -> SpanData: + process_data = node_execution.process_data or {} + outputs = node_execution.outputs or {} + usage_data = process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {}) + return SpanData( + trace_id=trace_id, + parent_span_id=workflow_span_id, + span_id=convert_to_span_id(node_execution.id, "node"), + name=node_execution.title, + start_time=convert_datetime_to_nanoseconds(node_execution.created_at), + end_time=convert_datetime_to_nanoseconds(node_execution.finished_at), + attributes={ + GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id", ""), + GEN_AI_SPAN_KIND: GenAISpanKind.LLM.value, + GEN_AI_FRAMEWORK: "dify", + GEN_AI_MODEL_NAME: process_data.get("model_name", ""), + GEN_AI_SYSTEM: process_data.get("model_provider", ""), + GEN_AI_USAGE_INPUT_TOKENS: str(usage_data.get("prompt_tokens", 0)), + GEN_AI_USAGE_OUTPUT_TOKENS: str(usage_data.get("completion_tokens", 0)), + GEN_AI_USAGE_TOTAL_TOKENS: str(usage_data.get("total_tokens", 0)), + GEN_AI_PROMPT: json.dumps(process_data.get("prompts", []), ensure_ascii=False), + GEN_AI_COMPLETION: str(outputs.get("text", "")), + GEN_AI_RESPONSE_FINISH_REASON: outputs.get("finish_reason", ""), + INPUT_VALUE: json.dumps(process_data.get("prompts", []), ensure_ascii=False), + OUTPUT_VALUE: str(outputs.get("text", "")), + }, + status=self.get_workflow_node_status(node_execution), + ) + + def add_workflow_span(self, trace_id: int, workflow_span_id: int, trace_info: WorkflowTraceInfo): + message_span_id = None + if trace_info.message_id: + message_span_id = convert_to_span_id(trace_info.message_id, "message") + user_id = trace_info.metadata.get("user_id") + status: Status = Status(StatusCode.OK) + if trace_info.error: + status = Status(StatusCode.ERROR, trace_info.error) + if message_span_id: # chatflow + message_span = SpanData( + trace_id=trace_id, + parent_span_id=None, + span_id=message_span_id, + name="message", + start_time=convert_datetime_to_nanoseconds(trace_info.start_time), + end_time=convert_datetime_to_nanoseconds(trace_info.end_time), + attributes={ + GEN_AI_SESSION_ID: trace_info.metadata.get("conversation_id", ""), + GEN_AI_USER_ID: str(user_id), + GEN_AI_SPAN_KIND: GenAISpanKind.CHAIN.value, + GEN_AI_FRAMEWORK: "dify", + INPUT_VALUE: trace_info.workflow_run_inputs.get("sys.query", ""), + OUTPUT_VALUE: json.dumps(trace_info.workflow_run_outputs, ensure_ascii=False), + }, + status=status, + ) + self.trace_client.add_span(message_span) + + workflow_span = SpanData( + trace_id=trace_id, + parent_span_id=message_span_id, + span_id=workflow_span_id, + name="workflow", + start_time=convert_datetime_to_nanoseconds(trace_info.start_time), + end_time=convert_datetime_to_nanoseconds(trace_info.end_time), + attributes={ + GEN_AI_USER_ID: str(user_id), + GEN_AI_SPAN_KIND: GenAISpanKind.CHAIN.value, + GEN_AI_FRAMEWORK: "dify", + INPUT_VALUE: json.dumps(trace_info.workflow_run_inputs, ensure_ascii=False), + OUTPUT_VALUE: json.dumps(trace_info.workflow_run_outputs, ensure_ascii=False), + }, + status=status, + ) + self.trace_client.add_span(workflow_span) + + def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo): + message_id = trace_info.message_id + status: Status = Status(StatusCode.OK) + if trace_info.error: + status = Status(StatusCode.ERROR, trace_info.error) + suggested_question_span = SpanData( + trace_id=convert_to_trace_id(message_id), + parent_span_id=convert_to_span_id(message_id, "message"), + span_id=convert_to_span_id(message_id, "suggested_question"), + name="suggested_question", + start_time=convert_datetime_to_nanoseconds(trace_info.start_time), + end_time=convert_datetime_to_nanoseconds(trace_info.end_time), + attributes={ + GEN_AI_SPAN_KIND: GenAISpanKind.LLM.value, + GEN_AI_FRAMEWORK: "dify", + GEN_AI_MODEL_NAME: trace_info.metadata.get("ls_model_name", ""), + GEN_AI_SYSTEM: trace_info.metadata.get("ls_provider", ""), + GEN_AI_PROMPT: json.dumps(trace_info.inputs, ensure_ascii=False), + GEN_AI_COMPLETION: json.dumps(trace_info.suggested_question, ensure_ascii=False), + INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + OUTPUT_VALUE: json.dumps(trace_info.suggested_question, ensure_ascii=False), + }, + status=status, + ) + self.trace_client.add_span(suggested_question_span) + + +def extract_retrieval_documents(documents: list[Document]): + documents_data = [] + for document in documents: + document_data = { + "content": document.page_content, + "metadata": { + "dataset_id": document.metadata.get("dataset_id"), + "doc_id": document.metadata.get("doc_id"), + "document_id": document.metadata.get("document_id"), + }, + "score": document.metadata.get("score"), + } + documents_data.append(document_data) + return documents_data diff --git a/api/core/ops/aliyun_trace/data_exporter/__init__.py b/api/core/ops/aliyun_trace/data_exporter/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/core/ops/aliyun_trace/data_exporter/traceclient.py b/api/core/ops/aliyun_trace/data_exporter/traceclient.py new file mode 100644 index 0000000000..ba5ac3f420 --- /dev/null +++ b/api/core/ops/aliyun_trace/data_exporter/traceclient.py @@ -0,0 +1,200 @@ +import hashlib +import logging +import random +import socket +import threading +import uuid +from collections import deque +from collections.abc import Sequence +from datetime import datetime +from typing import Optional + +import requests +from opentelemetry import trace as trace_api +from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter +from opentelemetry.sdk.resources import Resource +from opentelemetry.sdk.trace import ReadableSpan +from opentelemetry.sdk.util.instrumentation import InstrumentationScope +from opentelemetry.semconv.resource import ResourceAttributes + +from configs import dify_config +from core.ops.aliyun_trace.entities.aliyun_trace_entity import SpanData + +INVALID_SPAN_ID = 0x0000000000000000 +INVALID_TRACE_ID = 0x00000000000000000000000000000000 + +logger = logging.getLogger(__name__) + + +class TraceClient: + def __init__( + self, + service_name: str, + endpoint: str, + max_queue_size: int = 1000, + schedule_delay_sec: int = 5, + max_export_batch_size: int = 50, + ): + self.endpoint = endpoint + self.resource = Resource( + attributes={ + ResourceAttributes.SERVICE_NAME: service_name, + ResourceAttributes.SERVICE_VERSION: f"dify-{dify_config.project.version}-{dify_config.COMMIT_SHA}", + ResourceAttributes.DEPLOYMENT_ENVIRONMENT: f"{dify_config.DEPLOY_ENV}-{dify_config.EDITION}", + ResourceAttributes.HOST_NAME: socket.gethostname(), + } + ) + self.span_builder = SpanBuilder(self.resource) + self.exporter = OTLPSpanExporter(endpoint=endpoint) + + self.max_queue_size = max_queue_size + self.schedule_delay_sec = schedule_delay_sec + self.max_export_batch_size = max_export_batch_size + + self.queue: deque = deque(maxlen=max_queue_size) + self.condition = threading.Condition(threading.Lock()) + self.done = False + + self.worker_thread = threading.Thread(target=self._worker, daemon=True) + self.worker_thread.start() + + self._spans_dropped = False + + def export(self, spans: Sequence[ReadableSpan]): + self.exporter.export(spans) + + def api_check(self): + try: + response = requests.head(self.endpoint, timeout=5) + if response.status_code == 405: + return True + else: + logger.debug(f"AliyunTrace API check failed: Unexpected status code: {response.status_code}") + return False + except requests.exceptions.RequestException as e: + logger.debug(f"AliyunTrace API check failed: {str(e)}") + raise ValueError(f"AliyunTrace API check failed: {str(e)}") + + def get_project_url(self): + return "https://arms.console.aliyun.com/#/llm" + + def add_span(self, span_data: SpanData): + if span_data is None: + return + span: ReadableSpan = self.span_builder.build_span(span_data) + with self.condition: + if len(self.queue) == self.max_queue_size: + if not self._spans_dropped: + logger.warning("Queue is full, likely spans will be dropped.") + self._spans_dropped = True + + self.queue.appendleft(span) + if len(self.queue) >= self.max_export_batch_size: + self.condition.notify() + + def _worker(self): + while not self.done: + with self.condition: + if len(self.queue) < self.max_export_batch_size and not self.done: + self.condition.wait(timeout=self.schedule_delay_sec) + self._export_batch() + + def _export_batch(self): + spans_to_export: list[ReadableSpan] = [] + with self.condition: + while len(spans_to_export) < self.max_export_batch_size and self.queue: + spans_to_export.append(self.queue.pop()) + + if spans_to_export: + try: + self.exporter.export(spans_to_export) + except Exception as e: + logger.debug(f"Error exporting spans: {e}") + + def shutdown(self): + with self.condition: + self.done = True + self.condition.notify_all() + self.worker_thread.join() + self._export_batch() + self.exporter.shutdown() + + +class SpanBuilder: + def __init__(self, resource): + self.resource = resource + self.instrumentation_scope = InstrumentationScope( + __name__, + "", + None, + None, + ) + + def build_span(self, span_data: SpanData) -> ReadableSpan: + span_context = trace_api.SpanContext( + trace_id=span_data.trace_id, + span_id=span_data.span_id, + is_remote=False, + trace_flags=trace_api.TraceFlags(trace_api.TraceFlags.SAMPLED), + trace_state=None, + ) + + parent_span_context = None + if span_data.parent_span_id is not None: + parent_span_context = trace_api.SpanContext( + trace_id=span_data.trace_id, + span_id=span_data.parent_span_id, + is_remote=False, + trace_flags=trace_api.TraceFlags(trace_api.TraceFlags.SAMPLED), + trace_state=None, + ) + + span = ReadableSpan( + name=span_data.name, + context=span_context, + parent=parent_span_context, + resource=self.resource, + attributes=span_data.attributes, + events=span_data.events, + links=span_data.links, + kind=trace_api.SpanKind.INTERNAL, + status=span_data.status, + start_time=span_data.start_time, + end_time=span_data.end_time, + instrumentation_scope=self.instrumentation_scope, + ) + return span + + +def generate_span_id() -> int: + span_id = random.getrandbits(64) + while span_id == INVALID_SPAN_ID: + span_id = random.getrandbits(64) + return span_id + + +def convert_to_trace_id(uuid_v4: Optional[str]) -> int: + try: + uuid_obj = uuid.UUID(uuid_v4) + return uuid_obj.int + except Exception as e: + raise ValueError(f"Invalid UUID input: {e}") + + +def convert_to_span_id(uuid_v4: Optional[str], span_type: str) -> int: + try: + uuid_obj = uuid.UUID(uuid_v4) + except Exception as e: + raise ValueError(f"Invalid UUID input: {e}") + combined_key = f"{uuid_obj.hex}-{span_type}" + hash_bytes = hashlib.sha256(combined_key.encode("utf-8")).digest() + span_id = int.from_bytes(hash_bytes[:8], byteorder="big", signed=False) + return span_id + + +def convert_datetime_to_nanoseconds(start_time_a: Optional[datetime]) -> Optional[int]: + if start_time_a is None: + return None + timestamp_in_seconds = start_time_a.timestamp() + timestamp_in_nanoseconds = int(timestamp_in_seconds * 1e9) + return timestamp_in_nanoseconds diff --git a/api/core/ops/aliyun_trace/entities/__init__.py b/api/core/ops/aliyun_trace/entities/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/core/ops/aliyun_trace/entities/aliyun_trace_entity.py b/api/core/ops/aliyun_trace/entities/aliyun_trace_entity.py new file mode 100644 index 0000000000..1caa822cd0 --- /dev/null +++ b/api/core/ops/aliyun_trace/entities/aliyun_trace_entity.py @@ -0,0 +1,21 @@ +from collections.abc import Sequence +from typing import Optional + +from opentelemetry import trace as trace_api +from opentelemetry.sdk.trace import Event, Status, StatusCode +from pydantic import BaseModel, Field + + +class SpanData(BaseModel): + model_config = {"arbitrary_types_allowed": True} + + trace_id: int = Field(..., description="The unique identifier for the trace.") + parent_span_id: Optional[int] = Field(None, description="The ID of the parent span, if any.") + span_id: int = Field(..., description="The unique identifier for this span.") + name: str = Field(..., description="The name of the span.") + attributes: dict[str, str] = Field(default_factory=dict, description="Attributes associated with the span.") + events: Sequence[Event] = Field(default_factory=list, description="Events recorded in the span.") + links: Sequence[trace_api.Link] = Field(default_factory=list, description="Links to other spans.") + status: Status = Field(default=Status(StatusCode.UNSET), description="The status of the span.") + start_time: Optional[int] = Field(..., description="The start time of the span in nanoseconds.") + end_time: Optional[int] = Field(..., description="The end time of the span in nanoseconds.") diff --git a/api/core/ops/aliyun_trace/entities/semconv.py b/api/core/ops/aliyun_trace/entities/semconv.py new file mode 100644 index 0000000000..5d70264320 --- /dev/null +++ b/api/core/ops/aliyun_trace/entities/semconv.py @@ -0,0 +1,64 @@ +from enum import Enum + +# public +GEN_AI_SESSION_ID = "gen_ai.session.id" + +GEN_AI_USER_ID = "gen_ai.user.id" + +GEN_AI_USER_NAME = "gen_ai.user.name" + +GEN_AI_SPAN_KIND = "gen_ai.span.kind" + +GEN_AI_FRAMEWORK = "gen_ai.framework" + + +# Chain +INPUT_VALUE = "input.value" + +OUTPUT_VALUE = "output.value" + + +# Retriever +RETRIEVAL_QUERY = "retrieval.query" + +RETRIEVAL_DOCUMENT = "retrieval.document" + + +# LLM +GEN_AI_MODEL_NAME = "gen_ai.model_name" + +GEN_AI_SYSTEM = "gen_ai.system" + +GEN_AI_USAGE_INPUT_TOKENS = "gen_ai.usage.input_tokens" + +GEN_AI_USAGE_OUTPUT_TOKENS = "gen_ai.usage.output_tokens" + +GEN_AI_USAGE_TOTAL_TOKENS = "gen_ai.usage.total_tokens" + +GEN_AI_PROMPT_TEMPLATE_TEMPLATE = "gen_ai.prompt_template.template" + +GEN_AI_PROMPT_TEMPLATE_VARIABLE = "gen_ai.prompt_template.variable" + +GEN_AI_PROMPT = "gen_ai.prompt" + +GEN_AI_COMPLETION = "gen_ai.completion" + +GEN_AI_RESPONSE_FINISH_REASON = "gen_ai.response.finish_reason" + +# Tool +TOOL_NAME = "tool.name" + +TOOL_DESCRIPTION = "tool.description" + +TOOL_PARAMETERS = "tool.parameters" + + +class GenAISpanKind(Enum): + CHAIN = "CHAIN" + RETRIEVER = "RETRIEVER" + RERANKER = "RERANKER" + LLM = "LLM" + EMBEDDING = "EMBEDDING" + TOOL = "TOOL" + AGENT = "AGENT" + TASK = "TASK" diff --git a/api/core/ops/arize_phoenix_trace/__init__.py b/api/core/ops/arize_phoenix_trace/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py b/api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py new file mode 100644 index 0000000000..ffda0885d4 --- /dev/null +++ b/api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py @@ -0,0 +1,726 @@ +import hashlib +import json +import logging +import os +from datetime import datetime, timedelta +from typing import Optional, Union, cast + +from openinference.semconv.trace import OpenInferenceSpanKindValues, SpanAttributes +from opentelemetry import trace +from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter as GrpcOTLPSpanExporter +from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter as HttpOTLPSpanExporter +from opentelemetry.sdk import trace as trace_sdk +from opentelemetry.sdk.resources import Resource +from opentelemetry.sdk.trace.export import SimpleSpanProcessor +from opentelemetry.sdk.trace.id_generator import RandomIdGenerator +from opentelemetry.trace import SpanContext, TraceFlags, TraceState + +from core.ops.base_trace_instance import BaseTraceInstance +from core.ops.entities.config_entity import ArizeConfig, PhoenixConfig +from core.ops.entities.trace_entity import ( + BaseTraceInfo, + DatasetRetrievalTraceInfo, + GenerateNameTraceInfo, + MessageTraceInfo, + ModerationTraceInfo, + SuggestedQuestionTraceInfo, + ToolTraceInfo, + TraceTaskName, + WorkflowTraceInfo, +) +from extensions.ext_database import db +from models.model import EndUser, MessageFile +from models.workflow import WorkflowNodeExecutionModel + +logger = logging.getLogger(__name__) + + +def setup_tracer(arize_phoenix_config: ArizeConfig | PhoenixConfig) -> tuple[trace_sdk.Tracer, SimpleSpanProcessor]: + """Configure OpenTelemetry tracer with OTLP exporter for Arize/Phoenix.""" + try: + # Choose the appropriate exporter based on config type + exporter: Union[GrpcOTLPSpanExporter, HttpOTLPSpanExporter] + if isinstance(arize_phoenix_config, ArizeConfig): + arize_endpoint = f"{arize_phoenix_config.endpoint}/v1" + arize_headers = { + "api_key": arize_phoenix_config.api_key or "", + "space_id": arize_phoenix_config.space_id or "", + "authorization": f"Bearer {arize_phoenix_config.api_key or ''}", + } + exporter = GrpcOTLPSpanExporter( + endpoint=arize_endpoint, + headers=arize_headers, + timeout=30, + ) + else: + phoenix_endpoint = f"{arize_phoenix_config.endpoint}/v1/traces" + phoenix_headers = { + "api_key": arize_phoenix_config.api_key or "", + "authorization": f"Bearer {arize_phoenix_config.api_key or ''}", + } + exporter = HttpOTLPSpanExporter( + endpoint=phoenix_endpoint, + headers=phoenix_headers, + timeout=30, + ) + + attributes = { + "openinference.project.name": arize_phoenix_config.project or "", + "model_id": arize_phoenix_config.project or "", + } + resource = Resource(attributes=attributes) + provider = trace_sdk.TracerProvider(resource=resource) + processor = SimpleSpanProcessor( + exporter, + ) + provider.add_span_processor(processor) + + # Create a named tracer instead of setting the global provider + tracer_name = f"arize_phoenix_tracer_{arize_phoenix_config.project}" + logger.info(f"[Arize/Phoenix] Created tracer with name: {tracer_name}") + return cast(trace_sdk.Tracer, provider.get_tracer(tracer_name)), processor + except Exception as e: + logger.error(f"[Arize/Phoenix] Failed to setup the tracer: {str(e)}", exc_info=True) + raise + + +def datetime_to_nanos(dt: Optional[datetime]) -> int: + """Convert datetime to nanoseconds since epoch. If None, use current time.""" + if dt is None: + dt = datetime.now() + return int(dt.timestamp() * 1_000_000_000) + + +def uuid_to_trace_id(string: Optional[str]) -> int: + """Convert UUID string to a valid trace ID (16-byte integer).""" + if string is None: + string = "" + hash_object = hashlib.sha256(string.encode()) + + # Take the first 16 bytes (128 bits) of the hash + digest = hash_object.digest()[:16] + + # Convert to integer (128 bits) + return int.from_bytes(digest, byteorder="big") + + +class ArizePhoenixDataTrace(BaseTraceInstance): + def __init__( + self, + arize_phoenix_config: ArizeConfig | PhoenixConfig, + ): + super().__init__(arize_phoenix_config) + import logging + + logging.basicConfig() + logging.getLogger().setLevel(logging.DEBUG) + self.arize_phoenix_config = arize_phoenix_config + self.tracer, self.processor = setup_tracer(arize_phoenix_config) + self.project = arize_phoenix_config.project + self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001") + + def trace(self, trace_info: BaseTraceInfo): + logger.info(f"[Arize/Phoenix] Trace: {trace_info}") + try: + if isinstance(trace_info, WorkflowTraceInfo): + self.workflow_trace(trace_info) + if isinstance(trace_info, MessageTraceInfo): + self.message_trace(trace_info) + if isinstance(trace_info, ModerationTraceInfo): + self.moderation_trace(trace_info) + if isinstance(trace_info, SuggestedQuestionTraceInfo): + self.suggested_question_trace(trace_info) + if isinstance(trace_info, DatasetRetrievalTraceInfo): + self.dataset_retrieval_trace(trace_info) + if isinstance(trace_info, ToolTraceInfo): + self.tool_trace(trace_info) + if isinstance(trace_info, GenerateNameTraceInfo): + self.generate_name_trace(trace_info) + + except Exception as e: + logger.error(f"[Arize/Phoenix] Error in the trace: {str(e)}", exc_info=True) + raise + + def workflow_trace(self, trace_info: WorkflowTraceInfo): + if trace_info.message_data is None: + return + + workflow_metadata = { + "workflow_id": trace_info.workflow_run_id or "", + "message_id": trace_info.message_id or "", + "workflow_app_log_id": trace_info.workflow_app_log_id or "", + "status": trace_info.workflow_run_status or "", + "status_message": trace_info.error or "", + "level": "ERROR" if trace_info.error else "DEFAULT", + "total_tokens": trace_info.total_tokens or 0, + } + workflow_metadata.update(trace_info.metadata) + + trace_id = uuid_to_trace_id(trace_info.message_id) + span_id = RandomIdGenerator().generate_span_id() + context = SpanContext( + trace_id=trace_id, + span_id=span_id, + is_remote=False, + trace_flags=TraceFlags(TraceFlags.SAMPLED), + trace_state=TraceState(), + ) + + workflow_span = self.tracer.start_span( + name=TraceTaskName.WORKFLOW_TRACE.value, + attributes={ + SpanAttributes.INPUT_VALUE: json.dumps(trace_info.workflow_run_inputs, ensure_ascii=False), + SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.workflow_run_outputs, ensure_ascii=False), + SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value, + SpanAttributes.METADATA: json.dumps(workflow_metadata, ensure_ascii=False), + SpanAttributes.SESSION_ID: trace_info.conversation_id or "", + }, + start_time=datetime_to_nanos(trace_info.start_time), + context=trace.set_span_in_context(trace.NonRecordingSpan(context)), + ) + + try: + # Process workflow nodes + for node_execution in self._get_workflow_nodes(trace_info.workflow_run_id): + created_at = node_execution.created_at or datetime.now() + elapsed_time = node_execution.elapsed_time + finished_at = created_at + timedelta(seconds=elapsed_time) + + process_data = json.loads(node_execution.process_data) if node_execution.process_data else {} + + node_metadata = { + "node_id": node_execution.id, + "node_type": node_execution.node_type, + "node_status": node_execution.status, + "tenant_id": node_execution.tenant_id, + "app_id": node_execution.app_id, + "app_name": node_execution.title, + "status": node_execution.status, + "level": "ERROR" if node_execution.status != "succeeded" else "DEFAULT", + } + + if node_execution.execution_metadata: + node_metadata.update(json.loads(node_execution.execution_metadata)) + + # Determine the correct span kind based on node type + span_kind = OpenInferenceSpanKindValues.CHAIN.value + if node_execution.node_type == "llm": + span_kind = OpenInferenceSpanKindValues.LLM.value + provider = process_data.get("model_provider") + model = process_data.get("model_name") + if provider: + node_metadata["ls_provider"] = provider + if model: + node_metadata["ls_model_name"] = model + + outputs = json.loads(node_execution.outputs).get("usage", {}) + usage_data = process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {}) + if usage_data: + node_metadata["total_tokens"] = usage_data.get("total_tokens", 0) + node_metadata["prompt_tokens"] = usage_data.get("prompt_tokens", 0) + node_metadata["completion_tokens"] = usage_data.get("completion_tokens", 0) + elif node_execution.node_type == "dataset_retrieval": + span_kind = OpenInferenceSpanKindValues.RETRIEVER.value + elif node_execution.node_type == "tool": + span_kind = OpenInferenceSpanKindValues.TOOL.value + else: + span_kind = OpenInferenceSpanKindValues.CHAIN.value + + node_span = self.tracer.start_span( + name=node_execution.node_type, + attributes={ + SpanAttributes.INPUT_VALUE: node_execution.inputs or "{}", + SpanAttributes.OUTPUT_VALUE: node_execution.outputs or "{}", + SpanAttributes.OPENINFERENCE_SPAN_KIND: span_kind, + SpanAttributes.METADATA: json.dumps(node_metadata, ensure_ascii=False), + SpanAttributes.SESSION_ID: trace_info.conversation_id or "", + }, + start_time=datetime_to_nanos(created_at), + ) + + try: + if node_execution.node_type == "llm": + provider = process_data.get("model_provider") + model = process_data.get("model_name") + if provider: + node_span.set_attribute(SpanAttributes.LLM_PROVIDER, provider) + if model: + node_span.set_attribute(SpanAttributes.LLM_MODEL_NAME, model) + + outputs = json.loads(node_execution.outputs).get("usage", {}) + usage_data = ( + process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {}) + ) + if usage_data: + node_span.set_attribute( + SpanAttributes.LLM_TOKEN_COUNT_TOTAL, usage_data.get("total_tokens", 0) + ) + node_span.set_attribute( + SpanAttributes.LLM_TOKEN_COUNT_PROMPT, usage_data.get("prompt_tokens", 0) + ) + node_span.set_attribute( + SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, usage_data.get("completion_tokens", 0) + ) + finally: + node_span.end(end_time=datetime_to_nanos(finished_at)) + finally: + workflow_span.end(end_time=datetime_to_nanos(trace_info.end_time)) + + def message_trace(self, trace_info: MessageTraceInfo): + if trace_info.message_data is None: + return + + file_list = cast(list[str], trace_info.file_list) or [] + message_file_data: Optional[MessageFile] = trace_info.message_file_data + + if message_file_data is not None: + file_url = f"{self.file_base_url}/{message_file_data.url}" if message_file_data else "" + file_list.append(file_url) + + message_metadata = { + "message_id": trace_info.message_id or "", + "conversation_mode": str(trace_info.conversation_mode or ""), + "user_id": trace_info.message_data.from_account_id or "", + "file_list": json.dumps(file_list), + "status": trace_info.message_data.status or "", + "status_message": trace_info.error or "", + "level": "ERROR" if trace_info.error else "DEFAULT", + "total_tokens": trace_info.total_tokens or 0, + "prompt_tokens": trace_info.message_tokens or 0, + "completion_tokens": trace_info.answer_tokens or 0, + "ls_provider": trace_info.message_data.model_provider or "", + "ls_model_name": trace_info.message_data.model_id or "", + } + message_metadata.update(trace_info.metadata) + + # Add end user data if available + if trace_info.message_data.from_end_user_id: + end_user_data: Optional[EndUser] = ( + db.session.query(EndUser).filter(EndUser.id == trace_info.message_data.from_end_user_id).first() + ) + if end_user_data is not None: + message_metadata["end_user_id"] = end_user_data.session_id + + attributes = { + SpanAttributes.INPUT_VALUE: trace_info.message_data.query, + SpanAttributes.OUTPUT_VALUE: trace_info.message_data.answer, + SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value, + SpanAttributes.METADATA: json.dumps(message_metadata, ensure_ascii=False), + SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id, + } + + trace_id = uuid_to_trace_id(trace_info.message_id) + message_span_id = RandomIdGenerator().generate_span_id() + span_context = SpanContext( + trace_id=trace_id, + span_id=message_span_id, + is_remote=False, + trace_flags=TraceFlags(TraceFlags.SAMPLED), + trace_state=TraceState(), + ) + + message_span = self.tracer.start_span( + name=TraceTaskName.MESSAGE_TRACE.value, + attributes=attributes, + start_time=datetime_to_nanos(trace_info.start_time), + context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)), + ) + + try: + if trace_info.error: + message_span.add_event( + "exception", + attributes={ + "exception.message": trace_info.error, + "exception.type": "Error", + "exception.stacktrace": trace_info.error, + }, + ) + + # Convert outputs to string based on type + if isinstance(trace_info.outputs, dict | list): + outputs_str = json.dumps(trace_info.outputs, ensure_ascii=False) + elif isinstance(trace_info.outputs, str): + outputs_str = trace_info.outputs + else: + outputs_str = str(trace_info.outputs) + + llm_attributes = { + SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.LLM.value, + SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + SpanAttributes.OUTPUT_VALUE: outputs_str, + SpanAttributes.METADATA: json.dumps(message_metadata, ensure_ascii=False), + SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id, + } + + if isinstance(trace_info.inputs, list): + for i, msg in enumerate(trace_info.inputs): + if isinstance(msg, dict): + llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.{i}.message.content"] = msg.get("text", "") + llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.{i}.message.role"] = msg.get( + "role", "user" + ) + # todo: handle assistant and tool role messages, as they don't always + # have a text field, but may have a tool_calls field instead + # e.g. 'tool_calls': [{'id': '98af3a29-b066-45a5-b4b1-46c74ddafc58', + # 'type': 'function', 'function': {'name': 'current_time', 'arguments': '{}'}}]} + elif isinstance(trace_info.inputs, dict): + llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.content"] = json.dumps(trace_info.inputs) + llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.role"] = "user" + elif isinstance(trace_info.inputs, str): + llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.content"] = trace_info.inputs + llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.role"] = "user" + + if trace_info.total_tokens is not None and trace_info.total_tokens > 0: + llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_TOTAL] = trace_info.total_tokens + if trace_info.message_tokens is not None and trace_info.message_tokens > 0: + llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_PROMPT] = trace_info.message_tokens + if trace_info.answer_tokens is not None and trace_info.answer_tokens > 0: + llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_COMPLETION] = trace_info.answer_tokens + + if trace_info.message_data.model_id is not None: + llm_attributes[SpanAttributes.LLM_MODEL_NAME] = trace_info.message_data.model_id + if trace_info.message_data.model_provider is not None: + llm_attributes[SpanAttributes.LLM_PROVIDER] = trace_info.message_data.model_provider + + if trace_info.message_data and trace_info.message_data.message_metadata: + metadata_dict = json.loads(trace_info.message_data.message_metadata) + if model_params := metadata_dict.get("model_parameters"): + llm_attributes[SpanAttributes.LLM_INVOCATION_PARAMETERS] = json.dumps(model_params) + + llm_span = self.tracer.start_span( + name="llm", + attributes=llm_attributes, + start_time=datetime_to_nanos(trace_info.start_time), + context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)), + ) + + try: + if trace_info.error: + llm_span.add_event( + "exception", + attributes={ + "exception.message": trace_info.error, + "exception.type": "Error", + "exception.stacktrace": trace_info.error, + }, + ) + finally: + llm_span.end(end_time=datetime_to_nanos(trace_info.end_time)) + finally: + message_span.end(end_time=datetime_to_nanos(trace_info.end_time)) + + def moderation_trace(self, trace_info: ModerationTraceInfo): + if trace_info.message_data is None: + return + + metadata = { + "message_id": trace_info.message_id, + "tool_name": "moderation", + "status": trace_info.message_data.status, + "status_message": trace_info.message_data.error or "", + "level": "ERROR" if trace_info.message_data.error else "DEFAULT", + } + metadata.update(trace_info.metadata) + + trace_id = uuid_to_trace_id(trace_info.message_id) + span_id = RandomIdGenerator().generate_span_id() + context = SpanContext( + trace_id=trace_id, + span_id=span_id, + is_remote=False, + trace_flags=TraceFlags(TraceFlags.SAMPLED), + trace_state=TraceState(), + ) + + span = self.tracer.start_span( + name=TraceTaskName.MODERATION_TRACE.value, + attributes={ + SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + SpanAttributes.OUTPUT_VALUE: json.dumps( + { + "action": trace_info.action, + "flagged": trace_info.flagged, + "preset_response": trace_info.preset_response, + "inputs": trace_info.inputs, + }, + ensure_ascii=False, + ), + SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value, + SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False), + }, + start_time=datetime_to_nanos(trace_info.start_time), + context=trace.set_span_in_context(trace.NonRecordingSpan(context)), + ) + + try: + if trace_info.message_data.error: + span.add_event( + "exception", + attributes={ + "exception.message": trace_info.message_data.error, + "exception.type": "Error", + "exception.stacktrace": trace_info.message_data.error, + }, + ) + finally: + span.end(end_time=datetime_to_nanos(trace_info.end_time)) + + def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo): + if trace_info.message_data is None: + return + + start_time = trace_info.start_time or trace_info.message_data.created_at + end_time = trace_info.end_time or trace_info.message_data.updated_at + + metadata = { + "message_id": trace_info.message_id, + "tool_name": "suggested_question", + "status": trace_info.status, + "status_message": trace_info.error or "", + "level": "ERROR" if trace_info.error else "DEFAULT", + "total_tokens": trace_info.total_tokens, + "ls_provider": trace_info.model_provider or "", + "ls_model_name": trace_info.model_id or "", + } + metadata.update(trace_info.metadata) + + trace_id = uuid_to_trace_id(trace_info.message_id) + span_id = RandomIdGenerator().generate_span_id() + context = SpanContext( + trace_id=trace_id, + span_id=span_id, + is_remote=False, + trace_flags=TraceFlags(TraceFlags.SAMPLED), + trace_state=TraceState(), + ) + + span = self.tracer.start_span( + name=TraceTaskName.SUGGESTED_QUESTION_TRACE.value, + attributes={ + SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.suggested_question, ensure_ascii=False), + SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value, + SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False), + }, + start_time=datetime_to_nanos(start_time), + context=trace.set_span_in_context(trace.NonRecordingSpan(context)), + ) + + try: + if trace_info.error: + span.add_event( + "exception", + attributes={ + "exception.message": trace_info.error, + "exception.type": "Error", + "exception.stacktrace": trace_info.error, + }, + ) + finally: + span.end(end_time=datetime_to_nanos(end_time)) + + def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo): + if trace_info.message_data is None: + return + + start_time = trace_info.start_time or trace_info.message_data.created_at + end_time = trace_info.end_time or trace_info.message_data.updated_at + + metadata = { + "message_id": trace_info.message_id, + "tool_name": "dataset_retrieval", + "status": trace_info.message_data.status, + "status_message": trace_info.message_data.error or "", + "level": "ERROR" if trace_info.message_data.error else "DEFAULT", + "ls_provider": trace_info.message_data.model_provider or "", + "ls_model_name": trace_info.message_data.model_id or "", + } + metadata.update(trace_info.metadata) + + trace_id = uuid_to_trace_id(trace_info.message_id) + span_id = RandomIdGenerator().generate_span_id() + context = SpanContext( + trace_id=trace_id, + span_id=span_id, + is_remote=False, + trace_flags=TraceFlags(TraceFlags.SAMPLED), + trace_state=TraceState(), + ) + + span = self.tracer.start_span( + name=TraceTaskName.DATASET_RETRIEVAL_TRACE.value, + attributes={ + SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + SpanAttributes.OUTPUT_VALUE: json.dumps({"documents": trace_info.documents}, ensure_ascii=False), + SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.RETRIEVER.value, + SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False), + "start_time": start_time.isoformat() if start_time else "", + "end_time": end_time.isoformat() if end_time else "", + }, + start_time=datetime_to_nanos(start_time), + context=trace.set_span_in_context(trace.NonRecordingSpan(context)), + ) + + try: + if trace_info.message_data.error: + span.add_event( + "exception", + attributes={ + "exception.message": trace_info.message_data.error, + "exception.type": "Error", + "exception.stacktrace": trace_info.message_data.error, + }, + ) + finally: + span.end(end_time=datetime_to_nanos(end_time)) + + def tool_trace(self, trace_info: ToolTraceInfo): + if trace_info.message_data is None: + logger.warning("[Arize/Phoenix] Message data is None, skipping tool trace.") + return + + metadata = { + "message_id": trace_info.message_id, + "tool_config": json.dumps(trace_info.tool_config, ensure_ascii=False), + } + + trace_id = uuid_to_trace_id(trace_info.message_id) + tool_span_id = RandomIdGenerator().generate_span_id() + logger.info(f"[Arize/Phoenix] Creating tool trace with trace_id: {trace_id}, span_id: {tool_span_id}") + + # Create span context with the same trace_id as the parent + # todo: Create with the appropriate parent span context, so that the tool span is + # a child of the appropriate span (e.g. message span) + span_context = SpanContext( + trace_id=trace_id, + span_id=tool_span_id, + is_remote=False, + trace_flags=TraceFlags(TraceFlags.SAMPLED), + trace_state=TraceState(), + ) + + tool_params_str = ( + json.dumps(trace_info.tool_parameters, ensure_ascii=False) + if isinstance(trace_info.tool_parameters, dict) + else str(trace_info.tool_parameters) + ) + + span = self.tracer.start_span( + name=trace_info.tool_name, + attributes={ + SpanAttributes.INPUT_VALUE: json.dumps(trace_info.tool_inputs, ensure_ascii=False), + SpanAttributes.OUTPUT_VALUE: trace_info.tool_outputs, + SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.TOOL.value, + SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False), + SpanAttributes.TOOL_NAME: trace_info.tool_name, + SpanAttributes.TOOL_PARAMETERS: tool_params_str, + }, + start_time=datetime_to_nanos(trace_info.start_time), + context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)), + ) + + try: + if trace_info.error: + span.add_event( + "exception", + attributes={ + "exception.message": trace_info.error, + "exception.type": "Error", + "exception.stacktrace": trace_info.error, + }, + ) + finally: + span.end(end_time=datetime_to_nanos(trace_info.end_time)) + + def generate_name_trace(self, trace_info: GenerateNameTraceInfo): + if trace_info.message_data is None: + return + + metadata = { + "project_name": self.project, + "message_id": trace_info.message_id, + "status": trace_info.message_data.status, + "status_message": trace_info.message_data.error or "", + "level": "ERROR" if trace_info.message_data.error else "DEFAULT", + } + metadata.update(trace_info.metadata) + + trace_id = uuid_to_trace_id(trace_info.message_id) + span_id = RandomIdGenerator().generate_span_id() + context = SpanContext( + trace_id=trace_id, + span_id=span_id, + is_remote=False, + trace_flags=TraceFlags(TraceFlags.SAMPLED), + trace_state=TraceState(), + ) + + span = self.tracer.start_span( + name=TraceTaskName.GENERATE_NAME_TRACE.value, + attributes={ + SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False), + SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.outputs, ensure_ascii=False), + SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value, + SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False), + SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id, + "start_time": trace_info.start_time.isoformat() if trace_info.start_time else "", + "end_time": trace_info.end_time.isoformat() if trace_info.end_time else "", + }, + start_time=datetime_to_nanos(trace_info.start_time), + context=trace.set_span_in_context(trace.NonRecordingSpan(context)), + ) + + try: + if trace_info.message_data.error: + span.add_event( + "exception", + attributes={ + "exception.message": trace_info.message_data.error, + "exception.type": "Error", + "exception.stacktrace": trace_info.message_data.error, + }, + ) + finally: + span.end(end_time=datetime_to_nanos(trace_info.end_time)) + + def api_check(self): + try: + with self.tracer.start_span("api_check") as span: + span.set_attribute("test", "true") + return True + except Exception as e: + logger.info(f"[Arize/Phoenix] API check failed: {str(e)}", exc_info=True) + raise ValueError(f"[Arize/Phoenix] API check failed: {str(e)}") + + def get_project_url(self): + try: + if self.arize_phoenix_config.endpoint == "https://otlp.arize.com": + return "https://app.arize.com/" + else: + return f"{self.arize_phoenix_config.endpoint}/projects/" + except Exception as e: + logger.info(f"[Arize/Phoenix] Get run url failed: {str(e)}", exc_info=True) + raise ValueError(f"[Arize/Phoenix] Get run url failed: {str(e)}") + + def _get_workflow_nodes(self, workflow_run_id: str): + """Helper method to get workflow nodes""" + workflow_nodes = ( + db.session.query( + WorkflowNodeExecutionModel.id, + WorkflowNodeExecutionModel.tenant_id, + WorkflowNodeExecutionModel.app_id, + WorkflowNodeExecutionModel.title, + WorkflowNodeExecutionModel.node_type, + WorkflowNodeExecutionModel.status, + WorkflowNodeExecutionModel.inputs, + WorkflowNodeExecutionModel.outputs, + WorkflowNodeExecutionModel.created_at, + WorkflowNodeExecutionModel.elapsed_time, + WorkflowNodeExecutionModel.process_data, + WorkflowNodeExecutionModel.execution_metadata, + ) + .filter(WorkflowNodeExecutionModel.workflow_run_id == workflow_run_id) + .all() + ) + return workflow_nodes diff --git a/api/core/ops/entities/config_entity.py b/api/core/ops/entities/config_entity.py index c988bf48d1..89ff0cfded 100644 --- a/api/core/ops/entities/config_entity.py +++ b/api/core/ops/entities/config_entity.py @@ -2,20 +2,92 @@ from enum import StrEnum from pydantic import BaseModel, ValidationInfo, field_validator +from core.ops.utils import validate_project_name, validate_url, validate_url_with_path + class TracingProviderEnum(StrEnum): + ARIZE = "arize" + PHOENIX = "phoenix" LANGFUSE = "langfuse" LANGSMITH = "langsmith" OPIK = "opik" WEAVE = "weave" + ALIYUN = "aliyun" class BaseTracingConfig(BaseModel): """ - Base model class for tracing + Base model class for tracing configurations """ - ... + @classmethod + def validate_endpoint_url(cls, v: str, default_url: str) -> str: + """ + Common endpoint URL validation logic + + Args: + v: URL value to validate + default_url: Default URL to use if input is None or empty + + Returns: + Validated and normalized URL + """ + return validate_url(v, default_url) + + @classmethod + def validate_project_field(cls, v: str, default_name: str) -> str: + """ + Common project name validation logic + + Args: + v: Project name to validate + default_name: Default name to use if input is None or empty + + Returns: + Validated project name + """ + return validate_project_name(v, default_name) + + +class ArizeConfig(BaseTracingConfig): + """ + Model class for Arize tracing config. + """ + + api_key: str | None = None + space_id: str | None = None + project: str | None = None + endpoint: str = "https://otlp.arize.com" + + @field_validator("project") + @classmethod + def project_validator(cls, v, info: ValidationInfo): + return cls.validate_project_field(v, "default") + + @field_validator("endpoint") + @classmethod + def endpoint_validator(cls, v, info: ValidationInfo): + return cls.validate_endpoint_url(v, "https://otlp.arize.com") + + +class PhoenixConfig(BaseTracingConfig): + """ + Model class for Phoenix tracing config. + """ + + api_key: str | None = None + project: str | None = None + endpoint: str = "https://app.phoenix.arize.com" + + @field_validator("project") + @classmethod + def project_validator(cls, v, info: ValidationInfo): + return cls.validate_project_field(v, "default") + + @field_validator("endpoint") + @classmethod + def endpoint_validator(cls, v, info: ValidationInfo): + return cls.validate_endpoint_url(v, "https://app.phoenix.arize.com") class LangfuseConfig(BaseTracingConfig): @@ -29,13 +101,8 @@ class LangfuseConfig(BaseTracingConfig): @field_validator("host") @classmethod - def set_value(cls, v, info: ValidationInfo): - if v is None or v == "": - v = "https://api.langfuse.com" - if not v.startswith("https://") and not v.startswith("http://"): - raise ValueError("host must start with https:// or http://") - - return v + def host_validator(cls, v, info: ValidationInfo): + return cls.validate_endpoint_url(v, "https://api.langfuse.com") class LangSmithConfig(BaseTracingConfig): @@ -49,13 +116,9 @@ class LangSmithConfig(BaseTracingConfig): @field_validator("endpoint") @classmethod - def set_value(cls, v, info: ValidationInfo): - if v is None or v == "": - v = "https://api.smith.langchain.com" - if not v.startswith("https://"): - raise ValueError("endpoint must start with https://") - - return v + def endpoint_validator(cls, v, info: ValidationInfo): + # LangSmith only allows HTTPS + return validate_url(v, "https://api.smith.langchain.com", allowed_schemes=("https",)) class OpikConfig(BaseTracingConfig): @@ -71,22 +134,12 @@ class OpikConfig(BaseTracingConfig): @field_validator("project") @classmethod def project_validator(cls, v, info: ValidationInfo): - if v is None or v == "": - v = "Default Project" - - return v + return cls.validate_project_field(v, "Default Project") @field_validator("url") @classmethod def url_validator(cls, v, info: ValidationInfo): - if v is None or v == "": - v = "https://www.comet.com/opik/api/" - if not v.startswith(("https://", "http://")): - raise ValueError("url must start with https:// or http://") - if not v.endswith("/api/"): - raise ValueError("url should ends with /api/") - - return v + return validate_url_with_path(v, "https://www.comet.com/opik/api/", required_suffix="/api/") class WeaveConfig(BaseTracingConfig): @@ -102,22 +155,44 @@ class WeaveConfig(BaseTracingConfig): @field_validator("endpoint") @classmethod - def set_value(cls, v, info: ValidationInfo): - if v is None or v == "": - v = "https://trace.wandb.ai" - if not v.startswith("https://"): - raise ValueError("endpoint must start with https://") + def endpoint_validator(cls, v, info: ValidationInfo): + # Weave only allows HTTPS for endpoint + return validate_url(v, "https://trace.wandb.ai", allowed_schemes=("https",)) + @field_validator("host") + @classmethod + def host_validator(cls, v, info: ValidationInfo): + if v is not None and v.strip() != "": + return validate_url(v, v, allowed_schemes=("https", "http")) return v - @field_validator("host") + +class AliyunConfig(BaseTracingConfig): + """ + Model class for Aliyun tracing config. + """ + + app_name: str = "dify_app" + license_key: str + endpoint: str + + @field_validator("app_name") + @classmethod + def app_name_validator(cls, v, info: ValidationInfo): + return cls.validate_project_field(v, "dify_app") + + @field_validator("license_key") @classmethod - def validate_host(cls, v, info: ValidationInfo): - if v is not None and v != "": - if not v.startswith(("https://", "http://")): - raise ValueError("host must start with https:// or http://") + def license_key_validator(cls, v, info: ValidationInfo): + if not v or v.strip() == "": + raise ValueError("License key cannot be empty") return v + @field_validator("endpoint") + @classmethod + def endpoint_validator(cls, v, info: ValidationInfo): + return cls.validate_endpoint_url(v, "https://tracing-analysis-dc-hz.aliyuncs.com") + OPS_FILE_PATH = "ops_trace/" OPS_TRACE_FAILED_KEY = "FAILED_OPS_TRACE" diff --git a/api/core/ops/langfuse_trace/langfuse_trace.py b/api/core/ops/langfuse_trace/langfuse_trace.py index 0ea74e9ef0..a3dbce0e59 100644 --- a/api/core/ops/langfuse_trace/langfuse_trace.py +++ b/api/core/ops/langfuse_trace/langfuse_trace.py @@ -32,6 +32,7 @@ from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository from core.workflow.nodes.enums import NodeType from extensions.ext_database import db from models import EndUser, WorkflowNodeExecutionTriggeredFrom +from models.enums import MessageStatus logger = logging.getLogger(__name__) @@ -83,6 +84,7 @@ class LangFuseDataTrace(BaseTraceInstance): metadata=metadata, session_id=trace_info.conversation_id, tags=["message", "workflow"], + version=trace_info.workflow_run_version, ) self.add_trace(langfuse_trace_data=trace_data) workflow_span_data = LangfuseSpan( @@ -108,6 +110,7 @@ class LangFuseDataTrace(BaseTraceInstance): metadata=metadata, session_id=trace_info.conversation_id, tags=["workflow"], + version=trace_info.workflow_run_version, ) self.add_trace(langfuse_trace_data=trace_data) @@ -172,48 +175,15 @@ class LangFuseDataTrace(BaseTraceInstance): } ) - # add span - if trace_info.message_id: - span_data = LangfuseSpan( - id=node_execution_id, - name=node_type, - input=inputs, - output=outputs, - trace_id=trace_id, - start_time=created_at, - end_time=finished_at, - metadata=metadata, - level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR), - status_message=trace_info.error or "", - parent_observation_id=trace_info.workflow_run_id, - ) - else: - span_data = LangfuseSpan( - id=node_execution_id, - name=node_type, - input=inputs, - output=outputs, - trace_id=trace_id, - start_time=created_at, - end_time=finished_at, - metadata=metadata, - level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR), - status_message=trace_info.error or "", - ) - - self.add_span(langfuse_span_data=span_data) - + # add generation span if process_data and process_data.get("model_mode") == "chat": total_token = metadata.get("total_tokens", 0) prompt_tokens = 0 completion_tokens = 0 try: - if outputs.get("usage"): - prompt_tokens = outputs.get("usage", {}).get("prompt_tokens", 0) - completion_tokens = outputs.get("usage", {}).get("completion_tokens", 0) - else: - prompt_tokens = process_data.get("usage", {}).get("prompt_tokens", 0) - completion_tokens = process_data.get("usage", {}).get("completion_tokens", 0) + usage_data = process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {}) + prompt_tokens = usage_data.get("prompt_tokens", 0) + completion_tokens = usage_data.get("completion_tokens", 0) except Exception: logger.error("Failed to extract usage", exc_info=True) @@ -226,10 +196,10 @@ class LangFuseDataTrace(BaseTraceInstance): ) node_generation_data = LangfuseGeneration( - name="llm", + id=node_execution_id, + name=node_name, trace_id=trace_id, model=process_data.get("model_name"), - parent_observation_id=node_execution_id, start_time=created_at, end_time=finished_at, input=inputs, @@ -237,11 +207,30 @@ class LangFuseDataTrace(BaseTraceInstance): metadata=metadata, level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR), status_message=trace_info.error or "", + parent_observation_id=trace_info.workflow_run_id if trace_info.message_id else None, usage=generation_usage, ) self.add_generation(langfuse_generation_data=node_generation_data) + # add normal span + else: + span_data = LangfuseSpan( + id=node_execution_id, + name=node_name, + input=inputs, + output=outputs, + trace_id=trace_id, + start_time=created_at, + end_time=finished_at, + metadata=metadata, + level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR), + status_message=trace_info.error or "", + parent_observation_id=trace_info.workflow_run_id if trace_info.message_id else None, + ) + + self.add_span(langfuse_span_data=span_data) + def message_trace(self, trace_info: MessageTraceInfo, **kwargs): # get message file data file_list = trace_info.file_list @@ -284,7 +273,7 @@ class LangFuseDataTrace(BaseTraceInstance): ) self.add_trace(langfuse_trace_data=trace_data) - # start add span + # add generation generation_usage = GenerationUsage( input=trace_info.message_tokens, output=trace_info.answer_tokens, @@ -302,7 +291,7 @@ class LangFuseDataTrace(BaseTraceInstance): input=trace_info.inputs, output=message_data.answer, metadata=metadata, - level=(LevelEnum.DEFAULT if message_data.status != "error" else LevelEnum.ERROR), + level=(LevelEnum.DEFAULT if message_data.status != MessageStatus.ERROR else LevelEnum.ERROR), status_message=message_data.error or "", usage=generation_usage, ) @@ -348,7 +337,7 @@ class LangFuseDataTrace(BaseTraceInstance): start_time=trace_info.start_time, end_time=trace_info.end_time, metadata=trace_info.metadata, - level=(LevelEnum.DEFAULT if message_data.status != "error" else LevelEnum.ERROR), + level=(LevelEnum.DEFAULT if message_data.status != MessageStatus.ERROR else LevelEnum.ERROR), status_message=message_data.error or "", usage=generation_usage, ) diff --git a/api/core/ops/langsmith_trace/langsmith_trace.py b/api/core/ops/langsmith_trace/langsmith_trace.py index 8a392940db..f94e5e49d7 100644 --- a/api/core/ops/langsmith_trace/langsmith_trace.py +++ b/api/core/ops/langsmith_trace/langsmith_trace.py @@ -206,12 +206,9 @@ class LangSmithDataTrace(BaseTraceInstance): prompt_tokens = 0 completion_tokens = 0 try: - if outputs.get("usage"): - prompt_tokens = outputs.get("usage", {}).get("prompt_tokens", 0) - completion_tokens = outputs.get("usage", {}).get("completion_tokens", 0) - else: - prompt_tokens = process_data.get("usage", {}).get("prompt_tokens", 0) - completion_tokens = process_data.get("usage", {}).get("completion_tokens", 0) + usage_data = process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {}) + prompt_tokens = usage_data.get("prompt_tokens", 0) + completion_tokens = usage_data.get("completion_tokens", 0) except Exception: logger.error("Failed to extract usage", exc_info=True) diff --git a/api/core/ops/opik_trace/opik_trace.py b/api/core/ops/opik_trace/opik_trace.py index f4d2760ba5..8bedea20fb 100644 --- a/api/core/ops/opik_trace/opik_trace.py +++ b/api/core/ops/opik_trace/opik_trace.py @@ -222,10 +222,10 @@ class OpikDataTrace(BaseTraceInstance): ) try: - if outputs.get("usage"): - total_tokens = outputs["usage"].get("total_tokens", 0) - prompt_tokens = outputs["usage"].get("prompt_tokens", 0) - completion_tokens = outputs["usage"].get("completion_tokens", 0) + usage_data = process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {}) + total_tokens = usage_data.get("total_tokens", 0) + prompt_tokens = usage_data.get("prompt_tokens", 0) + completion_tokens = usage_data.get("completion_tokens", 0) except Exception: logger.error("Failed to extract usage", exc_info=True) diff --git a/api/core/ops/ops_trace_manager.py b/api/core/ops/ops_trace_manager.py index a98904102c..5c9b9d27b7 100644 --- a/api/core/ops/ops_trace_manager.py +++ b/api/core/ops/ops_trace_manager.py @@ -84,6 +84,36 @@ class OpsTraceProviderConfigMap(dict[str, dict[str, Any]]): "other_keys": ["project", "entity", "endpoint", "host"], "trace_instance": WeaveDataTrace, } + case TracingProviderEnum.ARIZE: + from core.ops.arize_phoenix_trace.arize_phoenix_trace import ArizePhoenixDataTrace + from core.ops.entities.config_entity import ArizeConfig + + return { + "config_class": ArizeConfig, + "secret_keys": ["api_key", "space_id"], + "other_keys": ["project", "endpoint"], + "trace_instance": ArizePhoenixDataTrace, + } + case TracingProviderEnum.PHOENIX: + from core.ops.arize_phoenix_trace.arize_phoenix_trace import ArizePhoenixDataTrace + from core.ops.entities.config_entity import PhoenixConfig + + return { + "config_class": PhoenixConfig, + "secret_keys": ["api_key"], + "other_keys": ["project", "endpoint"], + "trace_instance": ArizePhoenixDataTrace, + } + case TracingProviderEnum.ALIYUN: + from core.ops.aliyun_trace.aliyun_trace import AliyunDataTrace + from core.ops.entities.config_entity import AliyunConfig + + return { + "config_class": AliyunConfig, + "secret_keys": ["license_key"], + "other_keys": ["endpoint", "app_name"], + "trace_instance": AliyunDataTrace, + } case _: raise KeyError(f"Unsupported tracing provider: {provider}") diff --git a/api/core/ops/utils.py b/api/core/ops/utils.py index 8b06df1930..36d060afd2 100644 --- a/api/core/ops/utils.py +++ b/api/core/ops/utils.py @@ -1,6 +1,7 @@ from contextlib import contextmanager from datetime import datetime from typing import Optional, Union +from urllib.parse import urlparse from extensions.ext_database import db from models.model import Message @@ -60,3 +61,83 @@ def generate_dotted_order( return current_segment return f"{parent_dotted_order}.{current_segment}" + + +def validate_url(url: str, default_url: str, allowed_schemes: tuple = ("https", "http")) -> str: + """ + Validate and normalize URL with proper error handling + + Args: + url: The URL to validate + default_url: Default URL to use if input is None or empty + allowed_schemes: Tuple of allowed URL schemes (default: https, http) + + Returns: + Normalized URL string + + Raises: + ValueError: If URL format is invalid or scheme not allowed + """ + if not url or url.strip() == "": + return default_url + + # Parse URL to validate format + parsed = urlparse(url) + + # Check if scheme is allowed + if parsed.scheme not in allowed_schemes: + raise ValueError(f"URL scheme must be one of: {', '.join(allowed_schemes)}") + + # Reconstruct URL with only scheme, netloc (removing path, query, fragment) + normalized_url = f"{parsed.scheme}://{parsed.netloc}" + + return normalized_url + + +def validate_url_with_path(url: str, default_url: str, required_suffix: str | None = None) -> str: + """ + Validate URL that may include path components + + Args: + url: The URL to validate + default_url: Default URL to use if input is None or empty + required_suffix: Optional suffix that URL must end with + + Returns: + Validated URL string + + Raises: + ValueError: If URL format is invalid or doesn't match required suffix + """ + if not url or url.strip() == "": + return default_url + + # Parse URL to validate format + parsed = urlparse(url) + + # Check if scheme is allowed + if parsed.scheme not in ("https", "http"): + raise ValueError("URL must start with https:// or http://") + + # Check required suffix if specified + if required_suffix and not url.endswith(required_suffix): + raise ValueError(f"URL should end with {required_suffix}") + + return url + + +def validate_project_name(project: str, default_name: str) -> str: + """ + Validate and normalize project name + + Args: + project: Project name to validate + default_name: Default name to use if input is None or empty + + Returns: + Normalized project name + """ + if not project or project.strip() == "": + return default_name + + return project.strip() diff --git a/api/core/plugin/backwards_invocation/model.py b/api/core/plugin/backwards_invocation/model.py index 072644e53b..d07ab3d0c4 100644 --- a/api/core/plugin/backwards_invocation/model.py +++ b/api/core/plugin/backwards_invocation/model.py @@ -2,8 +2,15 @@ import tempfile from binascii import hexlify, unhexlify from collections.abc import Generator +from core.llm_generator.output_parser.structured_output import invoke_llm_with_structured_output from core.model_manager import ModelManager -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta +from core.model_runtime.entities.llm_entities import ( + LLMResult, + LLMResultChunk, + LLMResultChunkDelta, + LLMResultChunkWithStructuredOutput, + LLMResultWithStructuredOutput, +) from core.model_runtime.entities.message_entities import ( PromptMessage, SystemPromptMessage, @@ -12,6 +19,7 @@ from core.model_runtime.entities.message_entities import ( from core.plugin.backwards_invocation.base import BaseBackwardsInvocation from core.plugin.entities.request import ( RequestInvokeLLM, + RequestInvokeLLMWithStructuredOutput, RequestInvokeModeration, RequestInvokeRerank, RequestInvokeSpeech2Text, @@ -81,6 +89,72 @@ class PluginModelBackwardsInvocation(BaseBackwardsInvocation): return handle_non_streaming(response) + @classmethod + def invoke_llm_with_structured_output( + cls, user_id: str, tenant: Tenant, payload: RequestInvokeLLMWithStructuredOutput + ): + """ + invoke llm with structured output + """ + model_instance = ModelManager().get_model_instance( + tenant_id=tenant.id, + provider=payload.provider, + model_type=payload.model_type, + model=payload.model, + ) + + model_schema = model_instance.model_type_instance.get_model_schema(payload.model, model_instance.credentials) + + if not model_schema: + raise ValueError(f"Model schema not found for {payload.model}") + + response = invoke_llm_with_structured_output( + provider=payload.provider, + model_schema=model_schema, + model_instance=model_instance, + prompt_messages=payload.prompt_messages, + json_schema=payload.structured_output_schema, + tools=payload.tools, + stop=payload.stop, + stream=True if payload.stream is None else payload.stream, + user=user_id, + model_parameters=payload.completion_params, + ) + + if isinstance(response, Generator): + + def handle() -> Generator[LLMResultChunkWithStructuredOutput, None, None]: + for chunk in response: + if chunk.delta.usage: + llm_utils.deduct_llm_quota( + tenant_id=tenant.id, model_instance=model_instance, usage=chunk.delta.usage + ) + chunk.prompt_messages = [] + yield chunk + + return handle() + else: + if response.usage: + llm_utils.deduct_llm_quota(tenant_id=tenant.id, model_instance=model_instance, usage=response.usage) + + def handle_non_streaming( + response: LLMResultWithStructuredOutput, + ) -> Generator[LLMResultChunkWithStructuredOutput, None, None]: + yield LLMResultChunkWithStructuredOutput( + model=response.model, + prompt_messages=[], + system_fingerprint=response.system_fingerprint, + structured_output=response.structured_output, + delta=LLMResultChunkDelta( + index=0, + message=response.message, + usage=response.usage, + finish_reason="", + ), + ) + + return handle_non_streaming(response) + @classmethod def invoke_text_embedding(cls, user_id: str, tenant: Tenant, payload: RequestInvokeTextEmbedding): """ diff --git a/api/core/plugin/entities/parameters.py b/api/core/plugin/entities/parameters.py index 895dd0d0fc..2b438a3c33 100644 --- a/api/core/plugin/entities/parameters.py +++ b/api/core/plugin/entities/parameters.py @@ -10,6 +10,9 @@ from core.tools.entities.common_entities import I18nObject class PluginParameterOption(BaseModel): value: str = Field(..., description="The value of the option") label: I18nObject = Field(..., description="The label of the option") + icon: Optional[str] = Field( + default=None, description="The icon of the option, can be a url or a base64 encoded image" + ) @field_validator("value", mode="before") @classmethod @@ -35,6 +38,7 @@ class PluginParameterType(enum.StrEnum): APP_SELECTOR = CommonParameterType.APP_SELECTOR.value MODEL_SELECTOR = CommonParameterType.MODEL_SELECTOR.value TOOLS_SELECTOR = CommonParameterType.TOOLS_SELECTOR.value + DYNAMIC_SELECT = CommonParameterType.DYNAMIC_SELECT.value # deprecated, should not use. SYSTEM_FILES = CommonParameterType.SYSTEM_FILES.value diff --git a/api/core/plugin/entities/plugin_daemon.py b/api/core/plugin/entities/plugin_daemon.py index e0d2857e97..592b42c0da 100644 --- a/api/core/plugin/entities/plugin_daemon.py +++ b/api/core/plugin/entities/plugin_daemon.py @@ -1,4 +1,4 @@ -from collections.abc import Mapping +from collections.abc import Mapping, Sequence from datetime import datetime from enum import StrEnum from typing import Any, Generic, Optional, TypeVar @@ -9,6 +9,7 @@ from core.agent.plugin_entities import AgentProviderEntityWithPlugin from core.model_runtime.entities.model_entities import AIModelEntity from core.model_runtime.entities.provider_entities import ProviderEntity from core.plugin.entities.base import BasePluginEntity +from core.plugin.entities.parameters import PluginParameterOption from core.plugin.entities.plugin import PluginDeclaration, PluginEntity from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ToolProviderEntityWithPlugin @@ -186,3 +187,7 @@ class PluginOAuthCredentialsResponse(BaseModel): class PluginListResponse(BaseModel): list: list[PluginEntity] total: int + + +class PluginDynamicSelectOptionsResponse(BaseModel): + options: Sequence[PluginParameterOption] = Field(description="The options of the dynamic select.") diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 1692020ec8..f9c81ed4d5 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -82,6 +82,16 @@ class RequestInvokeLLM(BaseRequestInvokeModel): return v +class RequestInvokeLLMWithStructuredOutput(RequestInvokeLLM): + """ + Request to invoke LLM with structured output + """ + + structured_output_schema: dict[str, Any] = Field( + default_factory=dict, description="The schema of the structured output in JSON schema format" + ) + + class RequestInvokeTextEmbedding(BaseRequestInvokeModel): """ Request to invoke text embedding diff --git a/api/core/plugin/impl/dynamic_select.py b/api/core/plugin/impl/dynamic_select.py new file mode 100644 index 0000000000..004412afd7 --- /dev/null +++ b/api/core/plugin/impl/dynamic_select.py @@ -0,0 +1,45 @@ +from collections.abc import Mapping +from typing import Any + +from core.plugin.entities.plugin import GenericProviderID +from core.plugin.entities.plugin_daemon import PluginDynamicSelectOptionsResponse +from core.plugin.impl.base import BasePluginClient + + +class DynamicSelectClient(BasePluginClient): + def fetch_dynamic_select_options( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + action: str, + credentials: Mapping[str, Any], + parameter: str, + ) -> PluginDynamicSelectOptionsResponse: + """ + Fetch dynamic select options for a plugin parameter. + """ + response = self._request_with_plugin_daemon_response_stream( + "POST", + f"plugin/{tenant_id}/dispatch/dynamic_select/fetch_parameter_options", + PluginDynamicSelectOptionsResponse, + data={ + "user_id": user_id, + "data": { + "provider": GenericProviderID(provider).provider_name, + "credentials": credentials, + "provider_action": action, + "parameter": parameter, + }, + }, + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for options in response: + return options + + raise ValueError(f"Plugin service returned no options for parameter '{parameter}' in provider '{provider}'") diff --git a/api/core/plugin/impl/oauth.py b/api/core/plugin/impl/oauth.py index 91774984c8..b006bf1d4b 100644 --- a/api/core/plugin/impl/oauth.py +++ b/api/core/plugin/impl/oauth.py @@ -1,3 +1,4 @@ +import binascii from collections.abc import Mapping from typing import Any @@ -16,7 +17,7 @@ class OAuthHandler(BasePluginClient): provider: str, system_credentials: Mapping[str, Any], ) -> PluginOAuthAuthorizationUrlResponse: - return self._request_with_plugin_daemon_response( + response = self._request_with_plugin_daemon_response_stream( "POST", f"plugin/{tenant_id}/dispatch/oauth/get_authorization_url", PluginOAuthAuthorizationUrlResponse, @@ -32,6 +33,9 @@ class OAuthHandler(BasePluginClient): "Content-Type": "application/json", }, ) + for resp in response: + return resp + raise ValueError("No response received from plugin daemon for authorization URL request.") def get_credentials( self, @@ -49,7 +53,7 @@ class OAuthHandler(BasePluginClient): # encode request to raw http request raw_request_bytes = self._convert_request_to_raw_data(request) - return self._request_with_plugin_daemon_response( + response = self._request_with_plugin_daemon_response_stream( "POST", f"plugin/{tenant_id}/dispatch/oauth/get_credentials", PluginOAuthCredentialsResponse, @@ -58,7 +62,8 @@ class OAuthHandler(BasePluginClient): "data": { "provider": provider, "system_credentials": system_credentials, - "raw_request_bytes": raw_request_bytes, + # for json serialization + "raw_http_request": binascii.hexlify(raw_request_bytes).decode(), }, }, headers={ @@ -66,6 +71,9 @@ class OAuthHandler(BasePluginClient): "Content-Type": "application/json", }, ) + for resp in response: + return resp + raise ValueError("No response received from plugin daemon for authorization URL request.") def _convert_request_to_raw_data(self, request: Request) -> bytes: """ @@ -79,7 +87,7 @@ class OAuthHandler(BasePluginClient): """ # Start with the request line method = request.method - path = request.path + path = request.full_path protocol = request.headers.get("HTTP_VERSION", "HTTP/1.1") raw_data = f"{method} {path} {protocol}\r\n".encode() diff --git a/api/core/rag/datasource/vdb/matrixone/__init__.py b/api/core/rag/datasource/vdb/matrixone/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/core/rag/datasource/vdb/matrixone/matrixone_vector.py b/api/core/rag/datasource/vdb/matrixone/matrixone_vector.py new file mode 100644 index 0000000000..4894957382 --- /dev/null +++ b/api/core/rag/datasource/vdb/matrixone/matrixone_vector.py @@ -0,0 +1,233 @@ +import json +import logging +import uuid +from functools import wraps +from typing import Any, Optional + +from mo_vector.client import MoVectorClient # type: ignore +from pydantic import BaseModel, model_validator + +from configs import dify_config +from core.rag.datasource.vdb.vector_base import BaseVector +from core.rag.datasource.vdb.vector_factory import AbstractVectorFactory +from core.rag.datasource.vdb.vector_type import VectorType +from core.rag.embedding.embedding_base import Embeddings +from core.rag.models.document import Document +from extensions.ext_redis import redis_client +from models.dataset import Dataset + +logger = logging.getLogger(__name__) + + +class MatrixoneConfig(BaseModel): + host: str = "localhost" + port: int = 6001 + user: str = "dump" + password: str = "111" + database: str = "dify" + metric: str = "l2" + + @model_validator(mode="before") + @classmethod + def validate_config(cls, values: dict) -> dict: + if not values["host"]: + raise ValueError("config host is required") + if not values["port"]: + raise ValueError("config port is required") + if not values["user"]: + raise ValueError("config user is required") + if not values["password"]: + raise ValueError("config password is required") + if not values["database"]: + raise ValueError("config database is required") + return values + + +def ensure_client(func): + @wraps(func) + def wrapper(self, *args, **kwargs): + if self.client is None: + self.client = self._get_client(None, False) + return func(self, *args, **kwargs) + + return wrapper + + +class MatrixoneVector(BaseVector): + """ + Matrixone vector storage implementation. + """ + + def __init__(self, collection_name: str, config: MatrixoneConfig): + super().__init__(collection_name) + self.config = config + self.collection_name = collection_name.lower() + self.client = None + + @property + def collection_name(self): + return self._collection_name + + @collection_name.setter + def collection_name(self, value): + self._collection_name = value + + def get_type(self) -> str: + return VectorType.MATRIXONE + + def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs): + if self.client is None: + self.client = self._get_client(len(embeddings[0]), True) + return self.add_texts(texts, embeddings) + + def _get_client(self, dimension: Optional[int] = None, create_table: bool = False) -> MoVectorClient: + """ + Create a new client for the collection. + + The collection will be created if it doesn't exist. + """ + lock_name = f"vector_indexing_lock_{self._collection_name}" + with redis_client.lock(lock_name, timeout=20): + client = MoVectorClient( + connection_string=f"mysql+pymysql://{self.config.user}:{self.config.password}@{self.config.host}:{self.config.port}/{self.config.database}", + table_name=self.collection_name, + vector_dimension=dimension, + create_table=create_table, + ) + collection_exist_cache_key = f"vector_indexing_{self._collection_name}" + if redis_client.get(collection_exist_cache_key): + return client + try: + client.create_full_text_index() + except Exception as e: + logger.exception("Failed to create full text index") + redis_client.set(collection_exist_cache_key, 1, ex=3600) + return client + + def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs): + if self.client is None: + self.client = self._get_client(len(embeddings[0]), True) + assert self.client is not None + ids = [] + for _, doc in enumerate(documents): + if doc.metadata is not None: + doc_id = doc.metadata.get("doc_id", str(uuid.uuid4())) + ids.append(doc_id) + self.client.insert( + texts=[doc.page_content for doc in documents], + embeddings=embeddings, + metadatas=[doc.metadata for doc in documents], + ids=ids, + ) + return ids + + @ensure_client + def text_exists(self, id: str) -> bool: + assert self.client is not None + result = self.client.get(ids=[id]) + return len(result) > 0 + + @ensure_client + def delete_by_ids(self, ids: list[str]) -> None: + assert self.client is not None + if not ids: + return + self.client.delete(ids=ids) + + @ensure_client + def get_ids_by_metadata_field(self, key: str, value: str): + assert self.client is not None + results = self.client.query_by_metadata(filter={key: value}) + return [result.id for result in results] + + @ensure_client + def delete_by_metadata_field(self, key: str, value: str) -> None: + assert self.client is not None + self.client.delete(filter={key: value}) + + @ensure_client + def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]: + assert self.client is not None + top_k = kwargs.get("top_k", 5) + document_ids_filter = kwargs.get("document_ids_filter") + filter = None + if document_ids_filter: + filter = {"document_id": {"$in": document_ids_filter}} + + results = self.client.query( + query_vector=query_vector, + k=top_k, + filter=filter, + ) + + docs = [] + # TODO: add the score threshold to the query + for result in results: + metadata = result.metadata + docs.append( + Document( + page_content=result.document, + metadata=metadata, + ) + ) + return docs + + @ensure_client + def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]: + assert self.client is not None + top_k = kwargs.get("top_k", 5) + document_ids_filter = kwargs.get("document_ids_filter") + filter = None + if document_ids_filter: + filter = {"document_id": {"$in": document_ids_filter}} + score_threshold = float(kwargs.get("score_threshold", 0.0)) + + results = self.client.full_text_query( + keywords=[query], + k=top_k, + filter=filter, + ) + + docs = [] + for result in results: + metadata = result.metadata + if isinstance(metadata, str): + import json + + metadata = json.loads(metadata) + score = 1 - result.distance + if score >= score_threshold: + metadata["score"] = score + docs.append( + Document( + page_content=result.document, + metadata=metadata, + ) + ) + return docs + + @ensure_client + def delete(self) -> None: + assert self.client is not None + self.client.delete() + + +class MatrixoneVectorFactory(AbstractVectorFactory): + def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> MatrixoneVector: + if dataset.index_struct_dict: + class_prefix: str = dataset.index_struct_dict["vector_store"]["class_prefix"] + collection_name = class_prefix + else: + dataset_id = dataset.id + collection_name = Dataset.gen_collection_name_by_id(dataset_id) + dataset.index_struct = json.dumps(self.gen_index_struct_dict(VectorType.MATRIXONE, collection_name)) + + config = MatrixoneConfig( + host=dify_config.MATRIXONE_HOST or "localhost", + port=dify_config.MATRIXONE_PORT or 6001, + user=dify_config.MATRIXONE_USER or "dump", + password=dify_config.MATRIXONE_PASSWORD or "111", + database=dify_config.MATRIXONE_DATABASE or "dify", + metric=dify_config.MATRIXONE_METRIC or "l2", + ) + return MatrixoneVector(collection_name=collection_name, config=config) diff --git a/api/core/rag/datasource/vdb/tencent/tencent_vector.py b/api/core/rag/datasource/vdb/tencent/tencent_vector.py index d2bf3eb92a..75afe0cdb8 100644 --- a/api/core/rag/datasource/vdb/tencent/tencent_vector.py +++ b/api/core/rag/datasource/vdb/tencent/tencent_vector.py @@ -122,7 +122,6 @@ class TencentVector(BaseVector): metric_type, params, ) - index_text = vdb_index.FilterIndex(self.field_text, enum.FieldType.String, enum.IndexType.FILTER) index_metadate = vdb_index.FilterIndex(self.field_metadata, enum.FieldType.Json, enum.IndexType.FILTER) index_sparse_vector = vdb_index.SparseIndex( name="sparse_vector", @@ -130,7 +129,7 @@ class TencentVector(BaseVector): index_type=enum.IndexType.SPARSE_INVERTED, metric_type=enum.MetricType.IP, ) - indexes = [index_id, index_vector, index_text, index_metadate] + indexes = [index_id, index_vector, index_metadate] if self._enable_hybrid_search: indexes.append(index_sparse_vector) try: @@ -149,7 +148,7 @@ class TencentVector(BaseVector): index_metadate = vdb_index.FilterIndex( self.field_metadata, enum.FieldType.String, enum.IndexType.FILTER ) - indexes = [index_id, index_vector, index_text, index_metadate] + indexes = [index_id, index_vector, index_metadate] if self._enable_hybrid_search: indexes.append(index_sparse_vector) self._client.create_collection( diff --git a/api/core/rag/datasource/vdb/vector_factory.py b/api/core/rag/datasource/vdb/vector_factory.py index 66e002312a..67a4a515b1 100644 --- a/api/core/rag/datasource/vdb/vector_factory.py +++ b/api/core/rag/datasource/vdb/vector_factory.py @@ -164,6 +164,10 @@ class Vector: from core.rag.datasource.vdb.huawei.huawei_cloud_vector import HuaweiCloudVectorFactory return HuaweiCloudVectorFactory + case VectorType.MATRIXONE: + from core.rag.datasource.vdb.matrixone.matrixone_vector import MatrixoneVectorFactory + + return MatrixoneVectorFactory case _: raise ValueError(f"Vector store {vector_type} is not supported.") diff --git a/api/core/rag/datasource/vdb/vector_type.py b/api/core/rag/datasource/vdb/vector_type.py index 7a81565e37..0d70947b72 100644 --- a/api/core/rag/datasource/vdb/vector_type.py +++ b/api/core/rag/datasource/vdb/vector_type.py @@ -29,3 +29,4 @@ class VectorType(StrEnum): OPENGAUSS = "opengauss" TABLESTORE = "tablestore" HUAWEI_CLOUD = "huawei_cloud" + MATRIXONE = "matrixone" diff --git a/api/core/rag/datasource/vdb/weaviate/weaviate_vector.py b/api/core/rag/datasource/vdb/weaviate/weaviate_vector.py index c6cf0d2b27..7a8efb4068 100644 --- a/api/core/rag/datasource/vdb/weaviate/weaviate_vector.py +++ b/api/core/rag/datasource/vdb/weaviate/weaviate_vector.py @@ -45,7 +45,8 @@ class WeaviateVector(BaseVector): # by changing the connection timeout to pypi.org from 1 second to 0.001 seconds. # TODO: This can be removed once weaviate-client is updated to 3.26.7 or higher, # which does not contain the deprecation check. - weaviate.connect.connection.PYPI_TIMEOUT = 0.001 + if hasattr(weaviate.connect.connection, "PYPI_TIMEOUT"): + weaviate.connect.connection.PYPI_TIMEOUT = 0.001 try: client = weaviate.Client( diff --git a/api/core/rag/extractor/helpers.py b/api/core/rag/extractor/helpers.py index 69ca9d5d63..3d2fb55d9a 100644 --- a/api/core/rag/extractor/helpers.py +++ b/api/core/rag/extractor/helpers.py @@ -1,7 +1,6 @@ """Document loader helpers.""" import concurrent.futures -from pathlib import Path from typing import NamedTuple, Optional, cast @@ -16,7 +15,7 @@ class FileEncoding(NamedTuple): """The language of the file.""" -def detect_file_encodings(file_path: str, timeout: int = 5) -> list[FileEncoding]: +def detect_file_encodings(file_path: str, timeout: int = 5, sample_size: int = 1024 * 1024) -> list[FileEncoding]: """Try to detect the file encoding. Returns a list of `FileEncoding` tuples with the detected encodings ordered @@ -25,11 +24,16 @@ def detect_file_encodings(file_path: str, timeout: int = 5) -> list[FileEncoding Args: file_path: The path to the file to detect the encoding for. timeout: The timeout in seconds for the encoding detection. + sample_size: The number of bytes to read for encoding detection. Default is 1MB. + For large files, reading only a sample is sufficient and prevents timeout. """ import chardet def read_and_detect(file_path: str) -> list[dict]: - rawdata = Path(file_path).read_bytes() + with open(file_path, "rb") as f: + # Read only a sample of the file for encoding detection + # This prevents timeout on large files while still providing accurate encoding detection + rawdata = f.read(sample_size) return cast(list[dict], chardet.detect_all(rawdata)) with concurrent.futures.ThreadPoolExecutor() as executor: diff --git a/api/core/rag/extractor/markdown_extractor.py b/api/core/rag/extractor/markdown_extractor.py index 849852ac23..c97765b1dc 100644 --- a/api/core/rag/extractor/markdown_extractor.py +++ b/api/core/rag/extractor/markdown_extractor.py @@ -68,22 +68,17 @@ class MarkdownExtractor(BaseExtractor): continue header_match = re.match(r"^#+\s", line) if header_match: - if current_header is not None: - markdown_tups.append((current_header, current_text)) - + markdown_tups.append((current_header, current_text)) current_header = line current_text = "" else: current_text += line + "\n" markdown_tups.append((current_header, current_text)) - if current_header is not None: - # pass linting, assert keys are defined - markdown_tups = [ - (re.sub(r"#", "", cast(str, key)).strip(), re.sub(r"<.*?>", "", value)) for key, value in markdown_tups - ] - else: - markdown_tups = [(key, re.sub("\n", "", value)) for key, value in markdown_tups] + markdown_tups = [ + (re.sub(r"#", "", cast(str, key)).strip() if key else None, re.sub(r"<.*?>", "", value)) + for key, value in markdown_tups + ] return markdown_tups diff --git a/api/core/rag/extractor/text_extractor.py b/api/core/rag/extractor/text_extractor.py index b2b51d71d7..a00d328cb1 100644 --- a/api/core/rag/extractor/text_extractor.py +++ b/api/core/rag/extractor/text_extractor.py @@ -36,8 +36,12 @@ class TextExtractor(BaseExtractor): break except UnicodeDecodeError: continue + else: + raise RuntimeError( + f"Decode failed: {self._file_path}, all detected encodings failed. Original error: {e}" + ) else: - raise RuntimeError(f"Error loading {self._file_path}") from e + raise RuntimeError(f"Decode failed: {self._file_path}, specified encoding failed. Original error: {e}") except Exception as e: raise RuntimeError(f"Error loading {self._file_path}") from e diff --git a/api/core/rag/index_processor/processor/paragraph_index_processor.py b/api/core/rag/index_processor/processor/paragraph_index_processor.py index dca84b9041..9b90bd2bb3 100644 --- a/api/core/rag/index_processor/processor/paragraph_index_processor.py +++ b/api/core/rag/index_processor/processor/paragraph_index_processor.py @@ -76,6 +76,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor): if dataset.indexing_technique == "high_quality": vector = Vector(dataset) vector.create(documents) + with_keywords = False if with_keywords: keywords_list = kwargs.get("keywords_list") keyword = Keyword(dataset) @@ -91,6 +92,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor): vector.delete_by_ids(node_ids) else: vector.delete() + with_keywords = False if with_keywords: keyword = Keyword(dataset) if node_ids: diff --git a/api/core/rag/retrieval/dataset_retrieval.py b/api/core/rag/retrieval/dataset_retrieval.py index 38c0b540d5..3fca48be22 100644 --- a/api/core/rag/retrieval/dataset_retrieval.py +++ b/api/core/rag/retrieval/dataset_retrieval.py @@ -1010,6 +1010,9 @@ class DatasetRetrieval: def _process_metadata_filter_func( self, sequence: int, condition: str, metadata_name: str, value: Optional[Any], filters: list ): + if value is None: + return + key = f"{metadata_name}_{sequence}" key_value = f"{metadata_name}_{sequence}_value" match condition: diff --git a/api/core/repositories/sqlalchemy_workflow_execution_repository.py b/api/core/repositories/sqlalchemy_workflow_execution_repository.py index f82562a498..cdec92aee7 100644 --- a/api/core/repositories/sqlalchemy_workflow_execution_repository.py +++ b/api/core/repositories/sqlalchemy_workflow_execution_repository.py @@ -6,7 +6,7 @@ import json import logging from typing import Optional, Union -from sqlalchemy import func, select +from sqlalchemy import select from sqlalchemy.engine import Engine from sqlalchemy.orm import sessionmaker @@ -16,6 +16,7 @@ from core.workflow.entities.workflow_execution import ( WorkflowType, ) from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository +from core.workflow.workflow_type_encoder import WorkflowRuntimeTypeConverter from models import ( Account, CreatorUserRole, @@ -146,31 +147,17 @@ class SQLAlchemyWorkflowExecutionRepository(WorkflowExecutionRepository): db_model.workflow_id = domain_model.workflow_id db_model.triggered_from = self._triggered_from - # Check if this is a new record - with self._session_factory() as session: - existing = session.scalar(select(WorkflowRun).where(WorkflowRun.id == domain_model.id_)) - if not existing: - # For new records, get the next sequence number - # in case multiple executions are created concurrently, use for update - stmt = ( - select(func.coalesce(func.max(WorkflowRun.sequence_number), 0) + 1) - .where( - WorkflowRun.app_id == self._app_id, - WorkflowRun.tenant_id == self._tenant_id, - ) - .with_for_update() - ) - next_seq = session.scalar(stmt) - db_model.sequence_number = int(next_seq) if next_seq is not None else 1 - else: - # For updates, keep the existing sequence number - db_model.sequence_number = existing.sequence_number + # No sequence number generation needed anymore db_model.type = domain_model.workflow_type db_model.version = domain_model.workflow_version db_model.graph = json.dumps(domain_model.graph) if domain_model.graph else None db_model.inputs = json.dumps(domain_model.inputs) if domain_model.inputs else None - db_model.outputs = json.dumps(domain_model.outputs) if domain_model.outputs else None + db_model.outputs = ( + json.dumps(WorkflowRuntimeTypeConverter().to_json_encodable(domain_model.outputs)) + if domain_model.outputs + else None + ) db_model.status = domain_model.status db_model.error = domain_model.error_message if domain_model.error_message else None db_model.total_tokens = domain_model.total_tokens diff --git a/api/core/repositories/sqlalchemy_workflow_node_execution_repository.py b/api/core/repositories/sqlalchemy_workflow_node_execution_repository.py index 2f27442616..797cce9354 100644 --- a/api/core/repositories/sqlalchemy_workflow_node_execution_repository.py +++ b/api/core/repositories/sqlalchemy_workflow_node_execution_repository.py @@ -19,6 +19,7 @@ from core.workflow.entities.workflow_node_execution import ( ) from core.workflow.nodes.enums import NodeType from core.workflow.repositories.workflow_node_execution_repository import OrderConfig, WorkflowNodeExecutionRepository +from core.workflow.workflow_type_encoder import WorkflowRuntimeTypeConverter from models import ( Account, CreatorUserRole, @@ -146,6 +147,7 @@ class SQLAlchemyWorkflowNodeExecutionRepository(WorkflowNodeExecutionRepository) if not self._creator_user_role: raise ValueError("created_by_role is required in repository constructor") + json_converter = WorkflowRuntimeTypeConverter() db_model = WorkflowNodeExecutionModel() db_model.id = domain_model.id db_model.tenant_id = self._tenant_id @@ -160,9 +162,17 @@ class SQLAlchemyWorkflowNodeExecutionRepository(WorkflowNodeExecutionRepository) db_model.node_id = domain_model.node_id db_model.node_type = domain_model.node_type db_model.title = domain_model.title - db_model.inputs = json.dumps(domain_model.inputs) if domain_model.inputs else None - db_model.process_data = json.dumps(domain_model.process_data) if domain_model.process_data else None - db_model.outputs = json.dumps(domain_model.outputs) if domain_model.outputs else None + db_model.inputs = ( + json.dumps(json_converter.to_json_encodable(domain_model.inputs)) if domain_model.inputs else None + ) + db_model.process_data = ( + json.dumps(json_converter.to_json_encodable(domain_model.process_data)) + if domain_model.process_data + else None + ) + db_model.outputs = ( + json.dumps(json_converter.to_json_encodable(domain_model.outputs)) if domain_model.outputs else None + ) db_model.status = domain_model.status db_model.error = domain_model.error db_model.elapsed_time = domain_model.elapsed_time diff --git a/api/core/tools/builtin_tool/providers/audio/tools/tts.py b/api/core/tools/builtin_tool/providers/audio/tools/tts.py index 9b104b00f5..f191968812 100644 --- a/api/core/tools/builtin_tool/providers/audio/tools/tts.py +++ b/api/core/tools/builtin_tool/providers/audio/tools/tts.py @@ -31,6 +31,14 @@ class TTSTool(BuiltinTool): model_type=ModelType.TTS, model=model, ) + if not voice: + voices = model_instance.get_tts_voices() + if voices: + voice = voices[0].get("value") + if not voice: + raise ValueError("Sorry, no voice available.") + else: + raise ValueError("Sorry, no voice available.") tts = model_instance.invoke_tts( content_text=tool_parameters.get("text"), # type: ignore user=user_id, diff --git a/api/core/tools/builtin_tool/providers/code/tools/simple_code.py b/api/core/tools/builtin_tool/providers/code/tools/simple_code.py index ab0e155b98..b4e650e0ed 100644 --- a/api/core/tools/builtin_tool/providers/code/tools/simple_code.py +++ b/api/core/tools/builtin_tool/providers/code/tools/simple_code.py @@ -4,6 +4,7 @@ from typing import Any, Optional from core.helper.code_executor.code_executor import CodeExecutor, CodeLanguage from core.tools.builtin_tool.tool import BuiltinTool from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.errors import ToolInvokeError class SimpleCode(BuiltinTool): @@ -25,6 +26,8 @@ class SimpleCode(BuiltinTool): if language not in {CodeLanguage.PYTHON3, CodeLanguage.JAVASCRIPT}: raise ValueError(f"Only python3 and javascript are supported, not {language}") - result = CodeExecutor.execute_code(language, "", code) - - yield self.create_text_message(result) + try: + result = CodeExecutor.execute_code(language, "", code) + yield self.create_text_message(result) + except Exception as e: + raise ToolInvokeError(str(e)) diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 03047c0545..d2c28076ae 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -240,6 +240,7 @@ class ToolParameter(PluginParameter): FILES = PluginParameterType.FILES.value APP_SELECTOR = PluginParameterType.APP_SELECTOR.value MODEL_SELECTOR = PluginParameterType.MODEL_SELECTOR.value + DYNAMIC_SELECT = PluginParameterType.DYNAMIC_SELECT.value # deprecated, should not use. SYSTEM_FILES = PluginParameterType.SYSTEM_FILES.value diff --git a/api/core/tools/utils/configuration.py b/api/core/tools/utils/configuration.py index 6a5fba65bd..1f23e90351 100644 --- a/api/core/tools/utils/configuration.py +++ b/api/core/tools/utils/configuration.py @@ -86,6 +86,7 @@ class ProviderConfigEncrypter(BaseModel): cached_credentials = cache.get() if cached_credentials: return cached_credentials + data = self._deep_copy(data) # get fields need to be decrypted fields = dict[str, BasicProviderConfig]() diff --git a/api/core/variables/segments.py b/api/core/variables/segments.py index 64ba16c367..6cf09e0372 100644 --- a/api/core/variables/segments.py +++ b/api/core/variables/segments.py @@ -75,6 +75,20 @@ class StringSegment(Segment): class FloatSegment(Segment): value_type: SegmentType = SegmentType.NUMBER value: float + # NOTE(QuantumGhost): seems that the equality for FloatSegment with `NaN` value has some problems. + # The following tests cannot pass. + # + # def test_float_segment_and_nan(): + # nan = float("nan") + # assert nan != nan + # + # f1 = FloatSegment(value=float("nan")) + # f2 = FloatSegment(value=float("nan")) + # assert f1 != f2 + # + # f3 = FloatSegment(value=nan) + # f4 = FloatSegment(value=nan) + # assert f3 != f4 class IntegerSegment(Segment): diff --git a/api/core/variables/types.py b/api/core/variables/types.py index 4387e9693e..68d3d82883 100644 --- a/api/core/variables/types.py +++ b/api/core/variables/types.py @@ -18,3 +18,17 @@ class SegmentType(StrEnum): NONE = "none" GROUP = "group" + + def is_array_type(self): + return self in _ARRAY_TYPES + + +_ARRAY_TYPES = frozenset( + [ + SegmentType.ARRAY_ANY, + SegmentType.ARRAY_STRING, + SegmentType.ARRAY_NUMBER, + SegmentType.ARRAY_OBJECT, + SegmentType.ARRAY_FILE, + ] +) diff --git a/api/core/variables/utils.py b/api/core/variables/utils.py index e5d222af7d..692db3502e 100644 --- a/api/core/variables/utils.py +++ b/api/core/variables/utils.py @@ -1,8 +1,26 @@ +import json from collections.abc import Iterable, Sequence +from .segment_group import SegmentGroup +from .segments import ArrayFileSegment, FileSegment, Segment + def to_selector(node_id: str, name: str, paths: Iterable[str] = ()) -> Sequence[str]: selectors = [node_id, name] if paths: selectors.extend(paths) return selectors + + +class SegmentJSONEncoder(json.JSONEncoder): + def default(self, o): + if isinstance(o, ArrayFileSegment): + return [v.model_dump() for v in o.value] + elif isinstance(o, FileSegment): + return o.value.model_dump() + elif isinstance(o, SegmentGroup): + return [self.default(seg) for seg in o.value] + elif isinstance(o, Segment): + return o.value + else: + super().default(o) diff --git a/api/core/workflow/conversation_variable_updater.py b/api/core/workflow/conversation_variable_updater.py new file mode 100644 index 0000000000..84e99bb582 --- /dev/null +++ b/api/core/workflow/conversation_variable_updater.py @@ -0,0 +1,39 @@ +import abc +from typing import Protocol + +from core.variables import Variable + + +class ConversationVariableUpdater(Protocol): + """ + ConversationVariableUpdater defines an abstraction for updating conversation variable values. + + It is intended for use by `v1.VariableAssignerNode` and `v2.VariableAssignerNode` when updating + conversation variables. + + Implementations may choose to batch updates. If batching is used, the `flush` method + should be implemented to persist buffered changes, and `update` + should handle buffering accordingly. + + Note: Since implementations may buffer updates, instances of ConversationVariableUpdater + are not thread-safe. Each VariableAssignerNode should create its own instance during execution. + """ + + @abc.abstractmethod + def update(self, conversation_id: str, variable: "Variable") -> None: + """ + Updates the value of the specified conversation variable in the underlying storage. + + :param conversation_id: The ID of the conversation to update. Typically references `ConversationVariable.id`. + :param variable: The `Variable` instance containing the updated value. + """ + pass + + @abc.abstractmethod + def flush(self): + """ + Flushes all pending updates to the underlying storage system. + + If the implementation does not buffer updates, this method can be a no-op. + """ + pass diff --git a/api/core/workflow/entities/variable_pool.py b/api/core/workflow/entities/variable_pool.py index af26864c01..80dda2632d 100644 --- a/api/core/workflow/entities/variable_pool.py +++ b/api/core/workflow/entities/variable_pool.py @@ -7,12 +7,12 @@ from pydantic import BaseModel, Field from core.file import File, FileAttribute, file_manager from core.variables import Segment, SegmentGroup, Variable +from core.variables.consts import MIN_SELECTORS_LENGTH from core.variables.segments import FileSegment, NoneSegment +from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, ENVIRONMENT_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID +from core.workflow.enums import SystemVariableKey from factories import variable_factory -from ..constants import CONVERSATION_VARIABLE_NODE_ID, ENVIRONMENT_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID -from ..enums import SystemVariableKey - VariableValue = Union[str, int, float, dict, list, File] VARIABLE_PATTERN = re.compile(r"\{\{#([a-zA-Z0-9_]{1,50}(?:\.[a-zA-Z_][a-zA-Z0-9_]{0,29}){1,10})#\}\}") @@ -30,9 +30,11 @@ class VariablePool(BaseModel): # TODO: This user inputs is not used for pool. user_inputs: Mapping[str, Any] = Field( description="User inputs", + default_factory=dict, ) system_variables: Mapping[SystemVariableKey, Any] = Field( description="System variables", + default_factory=dict, ) environment_variables: Sequence[Variable] = Field( description="Environment variables.", @@ -43,28 +45,7 @@ class VariablePool(BaseModel): default_factory=list, ) - def __init__( - self, - *, - system_variables: Mapping[SystemVariableKey, Any] | None = None, - user_inputs: Mapping[str, Any] | None = None, - environment_variables: Sequence[Variable] | None = None, - conversation_variables: Sequence[Variable] | None = None, - **kwargs, - ): - environment_variables = environment_variables or [] - conversation_variables = conversation_variables or [] - user_inputs = user_inputs or {} - system_variables = system_variables or {} - - super().__init__( - system_variables=system_variables, - user_inputs=user_inputs, - environment_variables=environment_variables, - conversation_variables=conversation_variables, - **kwargs, - ) - + def model_post_init(self, context: Any, /) -> None: for key, value in self.system_variables.items(): self.add((SYSTEM_VARIABLE_NODE_ID, key.value), value) # Add environment variables to the variable pool @@ -91,12 +72,12 @@ class VariablePool(BaseModel): Returns: None """ - if len(selector) < 2: + if len(selector) < MIN_SELECTORS_LENGTH: raise ValueError("Invalid selector") if isinstance(value, Variable): variable = value - if isinstance(value, Segment): + elif isinstance(value, Segment): variable = variable_factory.segment_to_variable(segment=value, selector=selector) else: segment = variable_factory.build_segment(value) @@ -118,7 +99,7 @@ class VariablePool(BaseModel): Raises: ValueError: If the selector is invalid. """ - if len(selector) < 2: + if len(selector) < MIN_SELECTORS_LENGTH: return None hash_key = hash(tuple(selector[1:])) diff --git a/api/core/workflow/entities/workflow_node_execution.py b/api/core/workflow/entities/workflow_node_execution.py index 773f5b777b..09a408f4d7 100644 --- a/api/core/workflow/entities/workflow_node_execution.py +++ b/api/core/workflow/entities/workflow_node_execution.py @@ -66,11 +66,21 @@ class WorkflowNodeExecution(BaseModel): but they are not stored in the model. """ - # Core identification fields - id: str # Unique identifier for this execution record - node_execution_id: Optional[str] = None # Optional secondary ID for cross-referencing + # --------- Core identification fields --------- + + # Unique identifier for this execution record, used when persisting to storage. + # Value is a UUID string (e.g., '09b3e04c-f9ae-404c-ad82-290b8d7bd382'). + id: str + + # Optional secondary ID for cross-referencing purposes. + # + # NOTE: For referencing the persisted record, use `id` rather than `node_execution_id`. + # While `node_execution_id` may sometimes be a UUID string, this is not guaranteed. + # In most scenarios, `id` should be used as the primary identifier. + node_execution_id: Optional[str] = None workflow_id: str # ID of the workflow this node belongs to workflow_execution_id: Optional[str] = None # ID of the specific workflow run (null for single-step debugging) + # --------- Core identification fields ends --------- # Execution positioning and flow index: int # Sequence number for ordering in trace visualization diff --git a/api/core/workflow/graph_engine/entities/event.py b/api/core/workflow/graph_engine/entities/event.py index 9a4939502e..e57e9e4d64 100644 --- a/api/core/workflow/graph_engine/entities/event.py +++ b/api/core/workflow/graph_engine/entities/event.py @@ -66,6 +66,8 @@ class BaseNodeEvent(GraphEngineEvent): """iteration id if node is in iteration""" in_loop_id: Optional[str] = None """loop id if node is in loop""" + # The version of the node, or "1" if not specified. + node_version: str = "1" class NodeRunStartedEvent(BaseNodeEvent): diff --git a/api/core/workflow/graph_engine/graph_engine.py b/api/core/workflow/graph_engine/graph_engine.py index ee2164f22f..5a2915e2d3 100644 --- a/api/core/workflow/graph_engine/graph_engine.py +++ b/api/core/workflow/graph_engine/graph_engine.py @@ -53,6 +53,7 @@ from core.workflow.nodes.end.end_stream_processor import EndStreamProcessor from core.workflow.nodes.enums import ErrorStrategy, FailBranchSourceHandle from core.workflow.nodes.event import RunCompletedEvent, RunRetrieverResourceEvent, RunStreamChunkEvent from core.workflow.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING +from core.workflow.utils import variable_utils from libs.flask_utils import preserve_flask_contexts from models.enums import UserFrom from models.workflow import WorkflowType @@ -102,7 +103,7 @@ class GraphEngine: call_depth: int, graph: Graph, graph_config: Mapping[str, Any], - variable_pool: VariablePool, + graph_runtime_state: GraphRuntimeState, max_execution_steps: int, max_execution_time: int, thread_pool_id: Optional[str] = None, @@ -139,7 +140,7 @@ class GraphEngine: call_depth=call_depth, ) - self.graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) + self.graph_runtime_state = graph_runtime_state self.max_execution_steps = max_execution_steps self.max_execution_time = max_execution_time @@ -314,6 +315,7 @@ class GraphEngine: parallel_start_node_id=parallel_start_node_id, parent_parallel_id=parent_parallel_id, parent_parallel_start_node_id=parent_parallel_start_node_id, + node_version=node_instance.version(), ) raise e @@ -627,6 +629,7 @@ class GraphEngine: parent_parallel_id=parent_parallel_id, parent_parallel_start_node_id=parent_parallel_start_node_id, agent_strategy=agent_strategy, + node_version=node_instance.version(), ) max_retries = node_instance.node_data.retry_config.max_retries @@ -677,6 +680,7 @@ class GraphEngine: error=run_result.error or "Unknown error", retry_index=retries, start_at=retry_start_at, + node_version=node_instance.version(), ) time.sleep(retry_interval) break @@ -712,6 +716,7 @@ class GraphEngine: parallel_start_node_id=parallel_start_node_id, parent_parallel_id=parent_parallel_id, parent_parallel_start_node_id=parent_parallel_start_node_id, + node_version=node_instance.version(), ) should_continue_retry = False else: @@ -726,6 +731,7 @@ class GraphEngine: parallel_start_node_id=parallel_start_node_id, parent_parallel_id=parent_parallel_id, parent_parallel_start_node_id=parent_parallel_start_node_id, + node_version=node_instance.version(), ) should_continue_retry = False elif run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED: @@ -786,6 +792,7 @@ class GraphEngine: parallel_start_node_id=parallel_start_node_id, parent_parallel_id=parent_parallel_id, parent_parallel_start_node_id=parent_parallel_start_node_id, + node_version=node_instance.version(), ) should_continue_retry = False @@ -803,6 +810,7 @@ class GraphEngine: parallel_start_node_id=parallel_start_node_id, parent_parallel_id=parent_parallel_id, parent_parallel_start_node_id=parent_parallel_start_node_id, + node_version=node_instance.version(), ) elif isinstance(event, RunRetrieverResourceEvent): yield NodeRunRetrieverResourceEvent( @@ -817,6 +825,7 @@ class GraphEngine: parallel_start_node_id=parallel_start_node_id, parent_parallel_id=parent_parallel_id, parent_parallel_start_node_id=parent_parallel_start_node_id, + node_version=node_instance.version(), ) except GenerateTaskStoppedError: # trigger node run failed event @@ -833,6 +842,7 @@ class GraphEngine: parallel_start_node_id=parallel_start_node_id, parent_parallel_id=parent_parallel_id, parent_parallel_start_node_id=parent_parallel_start_node_id, + node_version=node_instance.version(), ) return except Exception as e: @@ -847,16 +857,12 @@ class GraphEngine: :param variable_value: variable value :return: """ - self.graph_runtime_state.variable_pool.add([node_id] + variable_key_list, variable_value) - - # if variable_value is a dict, then recursively append variables - if isinstance(variable_value, dict): - for key, value in variable_value.items(): - # construct new key list - new_key_list = variable_key_list + [key] - self._append_variables_recursively( - node_id=node_id, variable_key_list=new_key_list, variable_value=value - ) + variable_utils.append_variables_recursively( + self.graph_runtime_state.variable_pool, + node_id, + variable_key_list, + variable_value, + ) def _is_timed_out(self, start_at: float, max_execution_time: int) -> bool: """ diff --git a/api/core/workflow/nodes/agent/agent_node.py b/api/core/workflow/nodes/agent/agent_node.py index 22c564c1fc..766cdb604f 100644 --- a/api/core/workflow/nodes/agent/agent_node.py +++ b/api/core/workflow/nodes/agent/agent_node.py @@ -1,4 +1,5 @@ import json +import uuid from collections.abc import Generator, Mapping, Sequence from typing import Any, Optional, cast @@ -13,7 +14,7 @@ from core.model_runtime.entities.model_entities import AIModelEntity, ModelType from core.plugin.impl.exc import PluginDaemonClientSideError from core.plugin.impl.plugin import PluginInstaller from core.provider_manager import ProviderManager -from core.tools.entities.tool_entities import ToolParameter, ToolProviderType +from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter, ToolProviderType from core.tools.tool_manager import ToolManager from core.variables.segments import StringSegment from core.workflow.entities.node_entities import NodeRunResult @@ -39,6 +40,10 @@ class AgentNode(ToolNode): _node_data_cls = AgentNodeData # type: ignore _node_type = NodeType.AGENT + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> Generator: """ Run the agent node @@ -98,6 +103,32 @@ class AgentNode(ToolNode): try: # convert tool messages + agent_thoughts: list = [] + + thought_log_message = ToolInvokeMessage( + type=ToolInvokeMessage.MessageType.LOG, + message=ToolInvokeMessage.LogMessage( + id=str(uuid.uuid4()), + label=f"Agent Strategy: {cast(AgentNodeData, self.node_data).agent_strategy_name}", + parent_id=None, + error=None, + status=ToolInvokeMessage.LogMessage.LogStatus.START, + data={ + "strategy": cast(AgentNodeData, self.node_data).agent_strategy_name, + "parameters": parameters_for_log, + "thought_process": "Agent strategy execution started", + }, + metadata={ + "icon": self.agent_strategy_icon, + "agent_strategy": cast(AgentNodeData, self.node_data).agent_strategy_name, + }, + ), + ) + + def enhanced_message_stream(): + yield thought_log_message + + yield from message_stream yield from self._transform_message( message_stream, @@ -106,6 +137,7 @@ class AgentNode(ToolNode): "agent_strategy": cast(AgentNodeData, self.node_data).agent_strategy_name, }, parameters_for_log, + agent_thoughts, ) except PluginDaemonClientSideError as e: yield RunCompletedEvent( @@ -154,7 +186,10 @@ class AgentNode(ToolNode): # variable_pool.convert_template expects a string template, # but if passing a dict, convert to JSON string first before rendering try: - parameter_value = json.dumps(agent_input.value, ensure_ascii=False) + if not isinstance(agent_input.value, str): + parameter_value = json.dumps(agent_input.value, ensure_ascii=False) + else: + parameter_value = str(agent_input.value) except TypeError: parameter_value = str(agent_input.value) segment_group = variable_pool.convert_template(parameter_value) @@ -162,7 +197,8 @@ class AgentNode(ToolNode): # variable_pool.convert_template returns a string, # so we need to convert it back to a dictionary try: - parameter_value = json.loads(parameter_value) + if not isinstance(agent_input.value, str): + parameter_value = json.loads(parameter_value) except json.JSONDecodeError: parameter_value = parameter_value else: diff --git a/api/core/workflow/nodes/answer/answer_node.py b/api/core/workflow/nodes/answer/answer_node.py index aa030870e2..38c2bcbdf5 100644 --- a/api/core/workflow/nodes/answer/answer_node.py +++ b/api/core/workflow/nodes/answer/answer_node.py @@ -18,7 +18,11 @@ from core.workflow.utils.variable_template_parser import VariableTemplateParser class AnswerNode(BaseNode[AnswerNodeData]): _node_data_cls = AnswerNodeData - _node_type: NodeType = NodeType.ANSWER + _node_type = NodeType.ANSWER + + @classmethod + def version(cls) -> str: + return "1" def _run(self) -> NodeRunResult: """ @@ -45,7 +49,10 @@ class AnswerNode(BaseNode[AnswerNodeData]): part = cast(TextGenerateRouteChunk, part) answer += part.text - return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, outputs={"answer": answer, "files": files}) + return NodeRunResult( + status=WorkflowNodeExecutionStatus.SUCCEEDED, + outputs={"answer": answer, "files": ArrayFileSegment(value=files)}, + ) @classmethod def _extract_variable_selector_to_variable_mapping( diff --git a/api/core/workflow/nodes/answer/answer_stream_processor.py b/api/core/workflow/nodes/answer/answer_stream_processor.py index ba6ba16e36..97666fad05 100644 --- a/api/core/workflow/nodes/answer/answer_stream_processor.py +++ b/api/core/workflow/nodes/answer/answer_stream_processor.py @@ -2,7 +2,6 @@ import logging from collections.abc import Generator from typing import cast -from core.file import FILE_MODEL_IDENTITY, File from core.workflow.entities.variable_pool import VariablePool from core.workflow.graph_engine.entities.event import ( GraphEngineEvent, @@ -109,6 +108,7 @@ class AnswerStreamProcessor(StreamProcessor): parallel_id=event.parallel_id, parallel_start_node_id=event.parallel_start_node_id, from_variable_selector=[answer_node_id, "answer"], + node_version=event.node_version, ) else: route_chunk = cast(VarGenerateRouteChunk, route_chunk) @@ -134,6 +134,7 @@ class AnswerStreamProcessor(StreamProcessor): route_node_state=event.route_node_state, parallel_id=event.parallel_id, parallel_start_node_id=event.parallel_start_node_id, + node_version=event.node_version, ) self.route_position[answer_node_id] += 1 @@ -199,44 +200,3 @@ class AnswerStreamProcessor(StreamProcessor): stream_out_answer_node_ids.append(answer_node_id) return stream_out_answer_node_ids - - @classmethod - def _fetch_files_from_variable_value(cls, value: dict | list) -> list[dict]: - """ - Fetch files from variable value - :param value: variable value - :return: - """ - if not value: - return [] - - files = [] - if isinstance(value, list): - for item in value: - file_var = cls._get_file_var_from_value(item) - if file_var: - files.append(file_var) - elif isinstance(value, dict): - file_var = cls._get_file_var_from_value(value) - if file_var: - files.append(file_var) - - return files - - @classmethod - def _get_file_var_from_value(cls, value: dict | list): - """ - Get file var from value - :param value: variable value - :return: - """ - if not value: - return None - - if isinstance(value, dict): - if "dify_model_identity" in value and value["dify_model_identity"] == FILE_MODEL_IDENTITY: - return value - elif isinstance(value, File): - return value.to_dict() - - return None diff --git a/api/core/workflow/nodes/answer/base_stream_processor.py b/api/core/workflow/nodes/answer/base_stream_processor.py index 6671ff0746..09d5464d7a 100644 --- a/api/core/workflow/nodes/answer/base_stream_processor.py +++ b/api/core/workflow/nodes/answer/base_stream_processor.py @@ -57,7 +57,6 @@ class StreamProcessor(ABC): # The branch_identify parameter is added to ensure that # only nodes in the correct logical branch are included. - reachable_node_ids.append(edge.target_node_id) ids = self._fetch_node_ids_in_reachable_branch(edge.target_node_id, run_result.edge_source_handle) reachable_node_ids.extend(ids) else: @@ -74,6 +73,8 @@ class StreamProcessor(ABC): self._remove_node_ids_in_unreachable_branch(node_id, reachable_node_ids) def _fetch_node_ids_in_reachable_branch(self, node_id: str, branch_identify: Optional[str] = None) -> list[str]: + if node_id not in self.rest_node_ids: + self.rest_node_ids.append(node_id) node_ids = [] for edge in self.graph.edge_mapping.get(node_id, []): if edge.target_node_id == self.graph.root_node_id: diff --git a/api/core/workflow/nodes/base/node.py b/api/core/workflow/nodes/base/node.py index 7da0c19740..6973401429 100644 --- a/api/core/workflow/nodes/base/node.py +++ b/api/core/workflow/nodes/base/node.py @@ -1,7 +1,7 @@ import logging from abc import abstractmethod from collections.abc import Generator, Mapping, Sequence -from typing import TYPE_CHECKING, Any, Generic, Optional, TypeVar, Union, cast +from typing import TYPE_CHECKING, Any, ClassVar, Generic, Optional, TypeVar, Union, cast from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus @@ -23,7 +23,7 @@ GenericNodeData = TypeVar("GenericNodeData", bound=BaseNodeData) class BaseNode(Generic[GenericNodeData]): _node_data_cls: type[GenericNodeData] - _node_type: NodeType + _node_type: ClassVar[NodeType] def __init__( self, @@ -90,8 +90,38 @@ class BaseNode(Generic[GenericNodeData]): graph_config: Mapping[str, Any], config: Mapping[str, Any], ) -> Mapping[str, Sequence[str]]: - """ - Extract variable selector to variable mapping + """Extracts references variable selectors from node configuration. + + The `config` parameter represents the configuration for a specific node type and corresponds + to the `data` field in the node definition object. + + The returned mapping has the following structure: + + {'1747829548239.#1747829667553.result#': ['1747829667553', 'result']} + + For loop and iteration nodes, the mapping may look like this: + + { + "1748332301644.input_selector": ["1748332363630", "result"], + "1748332325079.1748332325079.#sys.workflow_id#": ["sys", "workflow_id"], + } + + where `1748332301644` is the ID of the loop / iteration node, + and `1748332325079` is the ID of the node inside the loop or iteration node. + + Here, the key consists of two parts: the current node ID (provided as the `node_id` + parameter to `_extract_variable_selector_to_variable_mapping`) and the variable selector, + enclosed in `#` symbols. These two parts are separated by a dot (`.`). + + The value is a list of string representing the variable selector, where the first element is the node ID + of the referenced variable, and the second element is the variable name within that node. + + The meaning of the above response is: + + The node with ID `1747829548239` references the variable `result` from the node with + ID `1747829667553`. For example, if `1747829548239` is a LLM node, its prompt may contain a + reference to the `result` output variable of node `1747829667553`. + :param graph_config: graph config :param config: node config :return: @@ -101,9 +131,10 @@ class BaseNode(Generic[GenericNodeData]): raise ValueError("Node ID is required when extracting variable selector to variable mapping.") node_data = cls._node_data_cls(**config.get("data", {})) - return cls._extract_variable_selector_to_variable_mapping( + data = cls._extract_variable_selector_to_variable_mapping( graph_config=graph_config, node_id=node_id, node_data=cast(GenericNodeData, node_data) ) + return data @classmethod def _extract_variable_selector_to_variable_mapping( @@ -139,6 +170,16 @@ class BaseNode(Generic[GenericNodeData]): """ return self._node_type + @classmethod + @abstractmethod + def version(cls) -> str: + """`node_version` returns the version of current node type.""" + # NOTE(QuantumGhost): This should be in sync with `NODE_TYPE_CLASSES_MAPPING`. + # + # If you have introduced a new node type, please add it to `NODE_TYPE_CLASSES_MAPPING` + # in `api/core/workflow/nodes/__init__.py`. + raise NotImplementedError("subclasses of BaseNode must implement `version` method.") + @property def should_continue_on_error(self) -> bool: """judge if should continue on error diff --git a/api/core/workflow/nodes/code/code_node.py b/api/core/workflow/nodes/code/code_node.py index 61c08a7d71..22ed9e2651 100644 --- a/api/core/workflow/nodes/code/code_node.py +++ b/api/core/workflow/nodes/code/code_node.py @@ -40,6 +40,10 @@ class CodeNode(BaseNode[CodeNodeData]): return code_provider.get_default_config() + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: # Get code language code_language = self.node_data.code_language @@ -126,6 +130,9 @@ class CodeNode(BaseNode[CodeNodeData]): prefix: str = "", depth: int = 1, ): + # TODO(QuantumGhost): Replace native Python lists with `Array*Segment` classes. + # Note that `_transform_result` may produce lists containing `None` values, + # which don't conform to the type requirements of `Array*Segment` classes. if depth > dify_config.CODE_MAX_DEPTH: raise DepthLimitError(f"Depth limit {dify_config.CODE_MAX_DEPTH} reached, object too deep.") diff --git a/api/core/workflow/nodes/document_extractor/node.py b/api/core/workflow/nodes/document_extractor/node.py index 429fed2d04..8e6150f9cc 100644 --- a/api/core/workflow/nodes/document_extractor/node.py +++ b/api/core/workflow/nodes/document_extractor/node.py @@ -24,7 +24,7 @@ from configs import dify_config from core.file import File, FileTransferMethod, file_manager from core.helper import ssrf_proxy from core.variables import ArrayFileSegment -from core.variables.segments import FileSegment +from core.variables.segments import ArrayStringSegment, FileSegment from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus from core.workflow.nodes.base import BaseNode @@ -45,6 +45,10 @@ class DocumentExtractorNode(BaseNode[DocumentExtractorNodeData]): _node_data_cls = DocumentExtractorNodeData _node_type = NodeType.DOCUMENT_EXTRACTOR + @classmethod + def version(cls) -> str: + return "1" + def _run(self): variable_selector = self.node_data.variable_selector variable = self.graph_runtime_state.variable_pool.get(variable_selector) @@ -67,7 +71,7 @@ class DocumentExtractorNode(BaseNode[DocumentExtractorNodeData]): status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=inputs, process_data=process_data, - outputs={"text": extracted_text_list}, + outputs={"text": ArrayStringSegment(value=extracted_text_list)}, ) elif isinstance(value, File): extracted_text = _extract_text_from_file(value) @@ -447,7 +451,7 @@ def _extract_text_from_excel(file_content: bytes) -> str: df = df.applymap(lambda x: " ".join(str(x).splitlines()) if isinstance(x, str) else x) # type: ignore # Combine multi-line text in column names into a single line - df.columns = pd.Index([" ".join(col.splitlines()) for col in df.columns]) + df.columns = pd.Index([" ".join(str(col).splitlines()) for col in df.columns]) # Manually construct the Markdown table markdown_table += _construct_markdown_table(df) + "\n\n" diff --git a/api/core/workflow/nodes/end/end_node.py b/api/core/workflow/nodes/end/end_node.py index 0e9756b243..17a0b3adeb 100644 --- a/api/core/workflow/nodes/end/end_node.py +++ b/api/core/workflow/nodes/end/end_node.py @@ -9,6 +9,10 @@ class EndNode(BaseNode[EndNodeData]): _node_data_cls = EndNodeData _node_type = NodeType.END + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: """ Run node diff --git a/api/core/workflow/nodes/end/end_stream_processor.py b/api/core/workflow/nodes/end/end_stream_processor.py index 3ae5af7137..a6fb2ffc18 100644 --- a/api/core/workflow/nodes/end/end_stream_processor.py +++ b/api/core/workflow/nodes/end/end_stream_processor.py @@ -139,6 +139,7 @@ class EndStreamProcessor(StreamProcessor): route_node_state=event.route_node_state, parallel_id=event.parallel_id, parallel_start_node_id=event.parallel_start_node_id, + node_version=event.node_version, ) self.route_position[end_node_id] += 1 diff --git a/api/core/workflow/nodes/http_request/executor.py b/api/core/workflow/nodes/http_request/executor.py index 2c83b00d4a..8ac1ae8526 100644 --- a/api/core/workflow/nodes/http_request/executor.py +++ b/api/core/workflow/nodes/http_request/executor.py @@ -8,6 +8,7 @@ from typing import Any, Literal from urllib.parse import urlencode, urlparse import httpx +from json_repair import repair_json from configs import dify_config from core.file import file_manager @@ -178,7 +179,8 @@ class Executor: raise RequestBodyError("json body type should have exactly one item") json_string = self.variable_pool.convert_template(data[0].value).text try: - json_object = json.loads(json_string, strict=False) + repaired = repair_json(json_string) + json_object = json.loads(repaired, strict=False) except json.JSONDecodeError as e: raise RequestBodyError(f"Failed to parse JSON: {json_string}") from e self.json = json_object @@ -333,7 +335,7 @@ class Executor: try: response = getattr(ssrf_proxy, self.method.lower())(**request_args) except (ssrf_proxy.MaxRetriesExceededError, httpx.RequestError) as e: - raise HttpRequestNodeError(str(e)) + raise HttpRequestNodeError(str(e)) from e # FIXME: fix type ignore, this maybe httpx type issue return response # type: ignore diff --git a/api/core/workflow/nodes/http_request/node.py b/api/core/workflow/nodes/http_request/node.py index 6b1ac57c06..971e0f73e7 100644 --- a/api/core/workflow/nodes/http_request/node.py +++ b/api/core/workflow/nodes/http_request/node.py @@ -6,6 +6,7 @@ from typing import Any, Optional from configs import dify_config from core.file import File, FileTransferMethod from core.tools.tool_file_manager import ToolFileManager +from core.variables.segments import ArrayFileSegment from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.variable_entities import VariableSelector from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus @@ -60,6 +61,10 @@ class HttpRequestNode(BaseNode[HttpRequestNodeData]): }, } + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: process_data = {} try: @@ -92,7 +97,7 @@ class HttpRequestNode(BaseNode[HttpRequestNodeData]): status=WorkflowNodeExecutionStatus.SUCCEEDED, outputs={ "status_code": response.status_code, - "body": response.text if not files else "", + "body": response.text if not files.value else "", "headers": response.headers, "files": files, }, @@ -166,7 +171,7 @@ class HttpRequestNode(BaseNode[HttpRequestNodeData]): return mapping - def extract_files(self, url: str, response: Response) -> list[File]: + def extract_files(self, url: str, response: Response) -> ArrayFileSegment: """ Extract files from response by checking both Content-Type header and URL """ @@ -178,7 +183,7 @@ class HttpRequestNode(BaseNode[HttpRequestNodeData]): content_disposition_type = None if not is_file: - return files + return ArrayFileSegment(value=[]) if parsed_content_disposition: content_disposition_filename = parsed_content_disposition.get_filename() @@ -211,4 +216,4 @@ class HttpRequestNode(BaseNode[HttpRequestNodeData]): ) files.append(file) - return files + return ArrayFileSegment(value=files) diff --git a/api/core/workflow/nodes/if_else/if_else_node.py b/api/core/workflow/nodes/if_else/if_else_node.py index 976922f75d..22b748030c 100644 --- a/api/core/workflow/nodes/if_else/if_else_node.py +++ b/api/core/workflow/nodes/if_else/if_else_node.py @@ -1,4 +1,5 @@ -from typing import Literal +from collections.abc import Mapping, Sequence +from typing import Any, Literal from typing_extensions import deprecated @@ -16,6 +17,10 @@ class IfElseNode(BaseNode[IfElseNodeData]): _node_data_cls = IfElseNodeData _node_type = NodeType.IF_ELSE + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: """ Run node @@ -87,6 +92,22 @@ class IfElseNode(BaseNode[IfElseNodeData]): return data + @classmethod + def _extract_variable_selector_to_variable_mapping( + cls, + *, + graph_config: Mapping[str, Any], + node_id: str, + node_data: IfElseNodeData, + ) -> Mapping[str, Sequence[str]]: + var_mapping: dict[str, list[str]] = {} + for case in node_data.cases or []: + for condition in case.conditions: + key = "{}.#{}#".format(node_id, ".".join(condition.variable_selector)) + var_mapping[key] = condition.variable_selector + + return var_mapping + @deprecated("This function is deprecated. You should use the new cases structure.") def _should_not_use_old_function( diff --git a/api/core/workflow/nodes/iteration/iteration_node.py b/api/core/workflow/nodes/iteration/iteration_node.py index 42b6795fb0..c447f433aa 100644 --- a/api/core/workflow/nodes/iteration/iteration_node.py +++ b/api/core/workflow/nodes/iteration/iteration_node.py @@ -1,5 +1,6 @@ import contextvars import logging +import time import uuid from collections.abc import Generator, Mapping, Sequence from concurrent.futures import Future, wait @@ -11,6 +12,7 @@ from flask import Flask, current_app from configs import dify_config from core.variables import ArrayVariable, IntegerVariable, NoneVariable +from core.variables.segments import ArrayAnySegment, ArraySegment from core.workflow.entities.node_entities import ( NodeRunResult, ) @@ -37,6 +39,7 @@ from core.workflow.nodes.base import BaseNode from core.workflow.nodes.enums import NodeType from core.workflow.nodes.event import NodeEvent, RunCompletedEvent from core.workflow.nodes.iteration.entities import ErrorHandleMode, IterationNodeData +from factories.variable_factory import build_segment from libs.flask_utils import preserve_flask_contexts from .exc import ( @@ -72,6 +75,10 @@ class IterationNode(BaseNode[IterationNodeData]): }, } + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> Generator[NodeEvent | InNodeEvent, None, None]: """ Run the node. @@ -85,10 +92,17 @@ class IterationNode(BaseNode[IterationNodeData]): raise InvalidIteratorValueError(f"invalid iterator value: {variable}, please provide a list.") if isinstance(variable, NoneVariable) or len(variable.value) == 0: + # Try our best to preserve the type informat. + if isinstance(variable, ArraySegment): + output = variable.model_copy(update={"value": []}) + else: + output = ArrayAnySegment(value=[]) yield RunCompletedEvent( run_result=NodeRunResult( status=WorkflowNodeExecutionStatus.SUCCEEDED, - outputs={"output": []}, + # TODO(QuantumGhost): is it possible to compute the type of `output` + # from graph definition? + outputs={"output": output}, ) ) return @@ -120,8 +134,11 @@ class IterationNode(BaseNode[IterationNodeData]): variable_pool.add([self.node_id, "item"], iterator_list_value[0]) # init graph engine + from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState from core.workflow.graph_engine.graph_engine import GraphEngine, GraphEngineThreadPool + graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) + graph_engine = GraphEngine( tenant_id=self.tenant_id, app_id=self.app_id, @@ -133,7 +150,7 @@ class IterationNode(BaseNode[IterationNodeData]): call_depth=self.workflow_call_depth, graph=iteration_graph, graph_config=graph_config, - variable_pool=variable_pool, + graph_runtime_state=graph_runtime_state, max_execution_steps=dify_config.WORKFLOW_MAX_EXECUTION_STEPS, max_execution_time=dify_config.WORKFLOW_MAX_EXECUTION_TIME, thread_pool_id=self.thread_pool_id, @@ -231,6 +248,7 @@ class IterationNode(BaseNode[IterationNodeData]): # Flatten the list of lists if isinstance(outputs, list) and all(isinstance(output, list) for output in outputs): outputs = [item for sublist in outputs for item in sublist] + output_segment = build_segment(outputs) yield IterationRunSucceededEvent( iteration_id=self.id, @@ -247,7 +265,7 @@ class IterationNode(BaseNode[IterationNodeData]): yield RunCompletedEvent( run_result=NodeRunResult( status=WorkflowNodeExecutionStatus.SUCCEEDED, - outputs={"output": outputs}, + outputs={"output": output_segment}, metadata={ WorkflowNodeExecutionMetadataKey.ITERATION_DURATION_MAP: iter_run_map, WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens, diff --git a/api/core/workflow/nodes/iteration/iteration_start_node.py b/api/core/workflow/nodes/iteration/iteration_start_node.py index bee481ebdb..9900aa225d 100644 --- a/api/core/workflow/nodes/iteration/iteration_start_node.py +++ b/api/core/workflow/nodes/iteration/iteration_start_node.py @@ -13,6 +13,10 @@ class IterationStartNode(BaseNode[IterationStartNodeData]): _node_data_cls = IterationStartNodeData _node_type = NodeType.ITERATION_START + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: """ Run the node. diff --git a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py index 5cf5848d54..b34d62d669 100644 --- a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py +++ b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py @@ -24,6 +24,7 @@ from core.rag.entities.metadata_entities import Condition, MetadataCondition from core.rag.retrieval.dataset_retrieval import DatasetRetrieval from core.rag.retrieval.retrieval_methods import RetrievalMethod from core.variables import StringSegment +from core.variables.segments import ArrayObjectSegment from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus from core.workflow.nodes.enums import NodeType @@ -70,6 +71,10 @@ class KnowledgeRetrievalNode(LLMNode): _node_data_cls = KnowledgeRetrievalNodeData # type: ignore _node_type = NodeType.KNOWLEDGE_RETRIEVAL + @classmethod + def version(cls): + return "1" + def _run(self) -> NodeRunResult: # type: ignore node_data = cast(KnowledgeRetrievalNodeData, self.node_data) # extract variables @@ -115,9 +120,12 @@ class KnowledgeRetrievalNode(LLMNode): # retrieve knowledge try: results = self._fetch_dataset_retriever(node_data=node_data, query=query) - outputs = {"result": results} + outputs = {"result": ArrayObjectSegment(value=results)} return NodeRunResult( - status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=variables, process_data=None, outputs=outputs + status=WorkflowNodeExecutionStatus.SUCCEEDED, + inputs=variables, + process_data=None, + outputs=outputs, # type: ignore ) except KnowledgeRetrievalNodeError as e: @@ -482,6 +490,9 @@ class KnowledgeRetrievalNode(LLMNode): def _process_metadata_filter_func( self, sequence: int, condition: str, metadata_name: str, value: Optional[Any], filters: list ): + if value is None: + return + key = f"{metadata_name}_{sequence}" key_value = f"{metadata_name}_{sequence}_value" match condition: diff --git a/api/core/workflow/nodes/list_operator/node.py b/api/core/workflow/nodes/list_operator/node.py index e698d3f5d8..3c9ba44cf1 100644 --- a/api/core/workflow/nodes/list_operator/node.py +++ b/api/core/workflow/nodes/list_operator/node.py @@ -3,6 +3,7 @@ from typing import Any, Literal, Union from core.file import File from core.variables import ArrayFileSegment, ArrayNumberSegment, ArrayStringSegment +from core.variables.segments import ArrayAnySegment, ArraySegment from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus from core.workflow.nodes.base import BaseNode @@ -16,6 +17,10 @@ class ListOperatorNode(BaseNode[ListOperatorNodeData]): _node_data_cls = ListOperatorNodeData _node_type = NodeType.LIST_OPERATOR + @classmethod + def version(cls) -> str: + return "1" + def _run(self): inputs: dict[str, list] = {} process_data: dict[str, list] = {} @@ -30,7 +35,11 @@ class ListOperatorNode(BaseNode[ListOperatorNodeData]): if not variable.value: inputs = {"variable": []} process_data = {"variable": []} - outputs = {"result": [], "first_record": None, "last_record": None} + if isinstance(variable, ArraySegment): + result = variable.model_copy(update={"value": []}) + else: + result = ArrayAnySegment(value=[]) + outputs = {"result": result, "first_record": None, "last_record": None} return NodeRunResult( status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=inputs, @@ -71,7 +80,7 @@ class ListOperatorNode(BaseNode[ListOperatorNodeData]): variable = self._apply_slice(variable) outputs = { - "result": variable.value, + "result": variable, "first_record": variable.value[0] if variable.value else None, "last_record": variable.value[-1] if variable.value else None, } diff --git a/api/core/workflow/nodes/llm/file_saver.py b/api/core/workflow/nodes/llm/file_saver.py index c85baade03..a4b45ce652 100644 --- a/api/core/workflow/nodes/llm/file_saver.py +++ b/api/core/workflow/nodes/llm/file_saver.py @@ -119,9 +119,6 @@ class FileSaverImpl(LLMFileSaver): size=len(data), related_id=tool_file.id, url=url, - # TODO(QuantumGhost): how should I set the following key? - # What's the difference between `remote_url` and `url`? - # What's the purpose of `storage_key` and `dify_model_identity`? storage_key=tool_file.file_key, ) diff --git a/api/core/workflow/nodes/llm/node.py b/api/core/workflow/nodes/llm/node.py index d27124d62c..9bfb402dc8 100644 --- a/api/core/workflow/nodes/llm/node.py +++ b/api/core/workflow/nodes/llm/node.py @@ -5,11 +5,11 @@ import logging from collections.abc import Generator, Mapping, Sequence from typing import TYPE_CHECKING, Any, Optional, cast -import json_repair - from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity from core.file import FileType, file_manager from core.helper.code_executor import CodeExecutor, CodeLanguage +from core.llm_generator.output_parser.errors import OutputParserError +from core.llm_generator.output_parser.structured_output import invoke_llm_with_structured_output from core.memory.token_buffer_memory import TokenBufferMemory from core.model_manager import ModelInstance, ModelManager from core.model_runtime.entities import ( @@ -18,7 +18,13 @@ from core.model_runtime.entities import ( PromptMessageContentType, TextPromptMessageContent, ) -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMUsage +from core.model_runtime.entities.llm_entities import ( + LLMResult, + LLMResultChunk, + LLMResultChunkWithStructuredOutput, + LLMStructuredOutput, + LLMUsage, +) from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, PromptMessageContentUnionTypes, @@ -31,7 +37,6 @@ from core.model_runtime.entities.model_entities import ( ModelFeature, ModelPropertyKey, ModelType, - ParameterRule, ) from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel from core.model_runtime.utils.encoders import jsonable_encoder @@ -62,11 +67,6 @@ from core.workflow.nodes.event import ( RunRetrieverResourceEvent, RunStreamChunkEvent, ) -from core.workflow.utils.structured_output.entities import ( - ResponseFormat, - SpecialModelType, -) -from core.workflow.utils.structured_output.prompt import STRUCTURED_OUTPUT_PROMPT from core.workflow.utils.variable_template_parser import VariableTemplateParser from . import llm_utils @@ -138,13 +138,11 @@ class LLMNode(BaseNode[LLMNodeData]): ) self._llm_file_saver = llm_file_saver - def _run(self) -> Generator[NodeEvent | InNodeEvent, None, None]: - def process_structured_output(text: str) -> Optional[dict[str, Any]]: - """Process structured output if enabled""" - if not self.node_data.structured_output_enabled or not self.node_data.structured_output: - return None - return self._parse_structured_output(text) + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> Generator[NodeEvent | InNodeEvent, None, None]: node_inputs: Optional[dict[str, Any]] = None process_data = None result_text = "" @@ -223,15 +221,6 @@ class LLMNode(BaseNode[LLMNodeData]): jinja2_variables=self.node_data.prompt_config.jinja2_variables, ) - process_data = { - "model_mode": model_config.mode, - "prompts": PromptMessageUtil.prompt_messages_to_prompt_for_saving( - model_mode=model_config.mode, prompt_messages=prompt_messages - ), - "model_provider": model_config.provider, - "model_name": model_config.model, - } - # handle invoke result generator = self._invoke_llm( node_data_model=self.node_data.model, @@ -240,6 +229,8 @@ class LLMNode(BaseNode[LLMNodeData]): stop=stop, ) + structured_output: LLMStructuredOutput | None = None + for event in generator: if isinstance(event, RunStreamChunkEvent): yield event @@ -250,12 +241,25 @@ class LLMNode(BaseNode[LLMNodeData]): # deduct quota llm_utils.deduct_llm_quota(tenant_id=self.tenant_id, model_instance=model_instance, usage=usage) break + elif isinstance(event, LLMStructuredOutput): + structured_output = event + + process_data = { + "model_mode": model_config.mode, + "prompts": PromptMessageUtil.prompt_messages_to_prompt_for_saving( + model_mode=model_config.mode, prompt_messages=prompt_messages + ), + "usage": jsonable_encoder(usage), + "finish_reason": finish_reason, + "model_provider": model_config.provider, + "model_name": model_config.model, + } + outputs = {"text": result_text, "usage": jsonable_encoder(usage), "finish_reason": finish_reason} - structured_output = process_structured_output(result_text) if structured_output: - outputs["structured_output"] = structured_output + outputs["structured_output"] = structured_output.structured_output if self._file_outputs is not None: - outputs["files"] = self._file_outputs + outputs["files"] = ArrayFileSegment(value=self._file_outputs) yield RunCompletedEvent( run_result=NodeRunResult( @@ -298,20 +302,40 @@ class LLMNode(BaseNode[LLMNodeData]): model_instance: ModelInstance, prompt_messages: Sequence[PromptMessage], stop: Optional[Sequence[str]] = None, - ) -> Generator[NodeEvent, None, None]: - invoke_result = model_instance.invoke_llm( - prompt_messages=list(prompt_messages), - model_parameters=node_data_model.completion_params, - stop=list(stop or []), - stream=True, - user=self.user_id, + ) -> Generator[NodeEvent | LLMStructuredOutput, None, None]: + model_schema = model_instance.model_type_instance.get_model_schema( + node_data_model.name, model_instance.credentials ) + if not model_schema: + raise ValueError(f"Model schema not found for {node_data_model.name}") + + if self.node_data.structured_output_enabled: + output_schema = self._fetch_structured_output_schema() + invoke_result = invoke_llm_with_structured_output( + provider=model_instance.provider, + model_schema=model_schema, + model_instance=model_instance, + prompt_messages=prompt_messages, + json_schema=output_schema, + model_parameters=node_data_model.completion_params, + stop=list(stop or []), + stream=True, + user=self.user_id, + ) + else: + invoke_result = model_instance.invoke_llm( + prompt_messages=list(prompt_messages), + model_parameters=node_data_model.completion_params, + stop=list(stop or []), + stream=True, + user=self.user_id, + ) return self._handle_invoke_result(invoke_result=invoke_result) def _handle_invoke_result( - self, invoke_result: LLMResult | Generator[LLMResultChunk, None, None] - ) -> Generator[NodeEvent, None, None]: + self, invoke_result: LLMResult | Generator[LLMResultChunk | LLMStructuredOutput, None, None] + ) -> Generator[NodeEvent | LLMStructuredOutput, None, None]: # For blocking mode if isinstance(invoke_result, LLMResult): event = self._handle_blocking_result(invoke_result=invoke_result) @@ -325,23 +349,32 @@ class LLMNode(BaseNode[LLMNodeData]): usage = LLMUsage.empty_usage() finish_reason = None full_text_buffer = io.StringIO() - for result in invoke_result: - contents = result.delta.message.content - for text_part in self._save_multimodal_output_and_convert_result_to_markdown(contents): - full_text_buffer.write(text_part) - yield RunStreamChunkEvent(chunk_content=text_part, from_variable_selector=[self.node_id, "text"]) - - # Update the whole metadata - if not model and result.model: - model = result.model - if len(prompt_messages) == 0: - # TODO(QuantumGhost): it seems that this update has no visable effect. - # What's the purpose of the line below? - prompt_messages = list(result.prompt_messages) - if usage.prompt_tokens == 0 and result.delta.usage: - usage = result.delta.usage - if finish_reason is None and result.delta.finish_reason: - finish_reason = result.delta.finish_reason + # Consume the invoke result and handle generator exception + try: + for result in invoke_result: + if isinstance(result, LLMResultChunkWithStructuredOutput): + yield result + if isinstance(result, LLMResultChunk): + contents = result.delta.message.content + for text_part in self._save_multimodal_output_and_convert_result_to_markdown(contents): + full_text_buffer.write(text_part) + yield RunStreamChunkEvent( + chunk_content=text_part, from_variable_selector=[self.node_id, "text"] + ) + + # Update the whole metadata + if not model and result.model: + model = result.model + if len(prompt_messages) == 0: + # TODO(QuantumGhost): it seems that this update has no visable effect. + # What's the purpose of the line below? + prompt_messages = list(result.prompt_messages) + if usage.prompt_tokens == 0 and result.delta.usage: + usage = result.delta.usage + if finish_reason is None and result.delta.finish_reason: + finish_reason = result.delta.finish_reason + except OutputParserError as e: + raise LLMNodeError(f"Failed to parse structured output: {e}") yield ModelInvokeCompletedEvent(text=full_text_buffer.getvalue(), usage=usage, finish_reason=finish_reason) @@ -518,12 +551,6 @@ class LLMNode(BaseNode[LLMNodeData]): if not model_schema: raise ModelNotExistError(f"Model {node_data_model.name} not exist.") - if self.node_data.structured_output_enabled: - if model_schema.support_structure_output: - completion_params = self._handle_native_json_schema(completion_params, model_schema.parameter_rules) - else: - # Set appropriate response format based on model capabilities - self._set_response_format(completion_params, model_schema.parameter_rules) model_config_with_cred.parameters = completion_params # NOTE(-LAN-): This line modify the `self.node_data.model`, which is used in `_invoke_llm()`. node_data_model.completion_params = completion_params @@ -715,32 +742,8 @@ class LLMNode(BaseNode[LLMNodeData]): ) if not model_schema: raise ModelNotExistError(f"Model {model_config.model} not exist.") - if self.node_data.structured_output_enabled: - if not model_schema.support_structure_output: - filtered_prompt_messages = self._handle_prompt_based_schema( - prompt_messages=filtered_prompt_messages, - ) return filtered_prompt_messages, model_config.stop - def _parse_structured_output(self, result_text: str) -> dict[str, Any]: - structured_output: dict[str, Any] = {} - try: - parsed = json.loads(result_text) - if not isinstance(parsed, dict): - raise LLMNodeError(f"Failed to parse structured output: {result_text}") - structured_output = parsed - except json.JSONDecodeError as e: - # if the result_text is not a valid json, try to repair it - parsed = json_repair.loads(result_text) - if not isinstance(parsed, dict): - # handle reasoning model like deepseek-r1 got '\n\n\n' prefix - if isinstance(parsed, list): - parsed = next((item for item in parsed if isinstance(item, dict)), {}) - else: - raise LLMNodeError(f"Failed to parse structured output: {result_text}") - structured_output = parsed - return structured_output - @classmethod def _extract_variable_selector_to_variable_mapping( cls, @@ -930,104 +933,6 @@ class LLMNode(BaseNode[LLMNodeData]): self._file_outputs.append(saved_file) return saved_file - def _handle_native_json_schema(self, model_parameters: dict, rules: list[ParameterRule]) -> dict: - """ - Handle structured output for models with native JSON schema support. - - :param model_parameters: Model parameters to update - :param rules: Model parameter rules - :return: Updated model parameters with JSON schema configuration - """ - # Process schema according to model requirements - schema = self._fetch_structured_output_schema() - schema_json = self._prepare_schema_for_model(schema) - - # Set JSON schema in parameters - model_parameters["json_schema"] = json.dumps(schema_json, ensure_ascii=False) - - # Set appropriate response format if required by the model - for rule in rules: - if rule.name == "response_format" and ResponseFormat.JSON_SCHEMA.value in rule.options: - model_parameters["response_format"] = ResponseFormat.JSON_SCHEMA.value - - return model_parameters - - def _handle_prompt_based_schema(self, prompt_messages: Sequence[PromptMessage]) -> list[PromptMessage]: - """ - Handle structured output for models without native JSON schema support. - This function modifies the prompt messages to include schema-based output requirements. - - Args: - prompt_messages: Original sequence of prompt messages - - Returns: - list[PromptMessage]: Updated prompt messages with structured output requirements - """ - # Convert schema to string format - schema_str = json.dumps(self._fetch_structured_output_schema(), ensure_ascii=False) - - # Find existing system prompt with schema placeholder - system_prompt = next( - (prompt for prompt in prompt_messages if isinstance(prompt, SystemPromptMessage)), - None, - ) - structured_output_prompt = STRUCTURED_OUTPUT_PROMPT.replace("{{schema}}", schema_str) - # Prepare system prompt content - system_prompt_content = ( - structured_output_prompt + "\n\n" + system_prompt.content - if system_prompt and isinstance(system_prompt.content, str) - else structured_output_prompt - ) - system_prompt = SystemPromptMessage(content=system_prompt_content) - - # Extract content from the last user message - - filtered_prompts = [prompt for prompt in prompt_messages if not isinstance(prompt, SystemPromptMessage)] - updated_prompt = [system_prompt] + filtered_prompts - - return updated_prompt - - def _set_response_format(self, model_parameters: dict, rules: list) -> None: - """ - Set the appropriate response format parameter based on model rules. - - :param model_parameters: Model parameters to update - :param rules: Model parameter rules - """ - for rule in rules: - if rule.name == "response_format": - if ResponseFormat.JSON.value in rule.options: - model_parameters["response_format"] = ResponseFormat.JSON.value - elif ResponseFormat.JSON_OBJECT.value in rule.options: - model_parameters["response_format"] = ResponseFormat.JSON_OBJECT.value - - def _prepare_schema_for_model(self, schema: dict) -> dict: - """ - Prepare JSON schema based on model requirements. - - Different models have different requirements for JSON schema formatting. - This function handles these differences. - - :param schema: The original JSON schema - :return: Processed schema compatible with the current model - """ - - # Deep copy to avoid modifying the original schema - processed_schema = schema.copy() - - # Convert boolean types to string types (common requirement) - convert_boolean_to_string(processed_schema) - - # Apply model-specific transformations - if SpecialModelType.GEMINI in self.node_data.model.name: - remove_additional_properties(processed_schema) - return processed_schema - elif SpecialModelType.OLLAMA in self.node_data.model.provider: - return processed_schema - else: - # Default format with name field - return {"schema": processed_schema, "name": "llm_response"} - def _fetch_model_schema(self, provider: str) -> AIModelEntity | None: """ Fetch model schema @@ -1239,49 +1144,3 @@ def _handle_completion_template( ) prompt_messages.append(prompt_message) return prompt_messages - - -def remove_additional_properties(schema: dict) -> None: - """ - Remove additionalProperties fields from JSON schema. - Used for models like Gemini that don't support this property. - - :param schema: JSON schema to modify in-place - """ - if not isinstance(schema, dict): - return - - # Remove additionalProperties at current level - schema.pop("additionalProperties", None) - - # Process nested structures recursively - for value in schema.values(): - if isinstance(value, dict): - remove_additional_properties(value) - elif isinstance(value, list): - for item in value: - if isinstance(item, dict): - remove_additional_properties(item) - - -def convert_boolean_to_string(schema: dict) -> None: - """ - Convert boolean type specifications to string in JSON schema. - - :param schema: JSON schema to modify in-place - """ - if not isinstance(schema, dict): - return - - # Check for boolean type at current level - if schema.get("type") == "boolean": - schema["type"] = "string" - - # Process nested dictionaries and lists recursively - for value in schema.values(): - if isinstance(value, dict): - convert_boolean_to_string(value) - elif isinstance(value, list): - for item in value: - if isinstance(item, dict): - convert_boolean_to_string(item) diff --git a/api/core/workflow/nodes/loop/loop_end_node.py b/api/core/workflow/nodes/loop/loop_end_node.py index 327b9e234b..b144021bab 100644 --- a/api/core/workflow/nodes/loop/loop_end_node.py +++ b/api/core/workflow/nodes/loop/loop_end_node.py @@ -13,6 +13,10 @@ class LoopEndNode(BaseNode[LoopEndNodeData]): _node_data_cls = LoopEndNodeData _node_type = NodeType.LOOP_END + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: """ Run the node. diff --git a/api/core/workflow/nodes/loop/loop_node.py b/api/core/workflow/nodes/loop/loop_node.py index fafa205386..11fd7b6c2d 100644 --- a/api/core/workflow/nodes/loop/loop_node.py +++ b/api/core/workflow/nodes/loop/loop_node.py @@ -1,5 +1,6 @@ import json import logging +import time from collections.abc import Generator, Mapping, Sequence from datetime import UTC, datetime from typing import TYPE_CHECKING, Any, Literal, cast @@ -54,6 +55,10 @@ class LoopNode(BaseNode[LoopNodeData]): _node_data_cls = LoopNodeData _node_type = NodeType.LOOP + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> Generator[NodeEvent | InNodeEvent, None, None]: """Run the node.""" # Get inputs @@ -97,8 +102,11 @@ class LoopNode(BaseNode[LoopNodeData]): loop_variable_selectors[loop_variable.label] = variable_selector inputs[loop_variable.label] = processed_segment.value + from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState from core.workflow.graph_engine.graph_engine import GraphEngine + graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) + graph_engine = GraphEngine( tenant_id=self.tenant_id, app_id=self.app_id, @@ -110,7 +118,7 @@ class LoopNode(BaseNode[LoopNodeData]): call_depth=self.workflow_call_depth, graph=loop_graph, graph_config=self.graph_config, - variable_pool=variable_pool, + graph_runtime_state=graph_runtime_state, max_execution_steps=dify_config.WORKFLOW_MAX_EXECUTION_STEPS, max_execution_time=dify_config.WORKFLOW_MAX_EXECUTION_TIME, thread_pool_id=self.thread_pool_id, @@ -482,6 +490,13 @@ class LoopNode(BaseNode[LoopNodeData]): variable_mapping.update(sub_node_variable_mapping) + for loop_variable in node_data.loop_variables or []: + if loop_variable.value_type == "variable": + assert loop_variable.value is not None, "Loop variable value must be provided for variable type" + # add loop variable to variable mapping + selector = loop_variable.value + variable_mapping[f"{node_id}.{loop_variable.label}"] = selector + # remove variable out from loop variable_mapping = { key: value for key, value in variable_mapping.items() if value[0] not in loop_graph.node_ids diff --git a/api/core/workflow/nodes/loop/loop_start_node.py b/api/core/workflow/nodes/loop/loop_start_node.py index 5a15f36044..f5e38b7516 100644 --- a/api/core/workflow/nodes/loop/loop_start_node.py +++ b/api/core/workflow/nodes/loop/loop_start_node.py @@ -13,6 +13,10 @@ class LoopStartNode(BaseNode[LoopStartNodeData]): _node_data_cls = LoopStartNodeData _node_type = NodeType.LOOP_START + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: """ Run the node. diff --git a/api/core/workflow/nodes/node_mapping.py b/api/core/workflow/nodes/node_mapping.py index 1f1be59542..67cc884f20 100644 --- a/api/core/workflow/nodes/node_mapping.py +++ b/api/core/workflow/nodes/node_mapping.py @@ -25,6 +25,11 @@ from core.workflow.nodes.variable_assigner.v2 import VariableAssignerNode as Var LATEST_VERSION = "latest" +# NOTE(QuantumGhost): This should be in sync with subclasses of BaseNode. +# Specifically, if you have introduced new node types, you should add them here. +# +# TODO(QuantumGhost): This could be automated with either metaclass or `__init_subclass__` +# hook. Try to avoid duplication of node information. NODE_TYPE_CLASSES_MAPPING: Mapping[NodeType, Mapping[str, type[BaseNode]]] = { NodeType.START: { LATEST_VERSION: StartNode, diff --git a/api/core/workflow/nodes/parameter_extractor/entities.py b/api/core/workflow/nodes/parameter_extractor/entities.py index 369eb13b04..916778d167 100644 --- a/api/core/workflow/nodes/parameter_extractor/entities.py +++ b/api/core/workflow/nodes/parameter_extractor/entities.py @@ -7,6 +7,10 @@ from core.workflow.nodes.base import BaseNodeData from core.workflow.nodes.llm import ModelConfig, VisionConfig +class _ParameterConfigError(Exception): + pass + + class ParameterConfig(BaseModel): """ Parameter Config. @@ -27,6 +31,19 @@ class ParameterConfig(BaseModel): raise ValueError("Invalid parameter name, __reason and __is_success are reserved") return str(value) + def is_array_type(self) -> bool: + return self.type in ("array[string]", "array[number]", "array[object]") + + def element_type(self) -> Literal["string", "number", "object"]: + if self.type == "array[number]": + return "number" + elif self.type == "array[string]": + return "string" + elif self.type == "array[object]": + return "object" + else: + raise _ParameterConfigError(f"{self.type} is not array type.") + class ParameterExtractorNodeData(BaseNodeData): """ diff --git a/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py b/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py index 2552784762..25a534256b 100644 --- a/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py +++ b/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py @@ -25,6 +25,7 @@ from core.prompt.advanced_prompt_transform import AdvancedPromptTransform from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, CompletionModelPromptTemplate from core.prompt.simple_prompt_transform import ModelMode from core.prompt.utils.prompt_message_util import PromptMessageUtil +from core.variables.types import SegmentType from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.variable_pool import VariablePool from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus @@ -32,6 +33,7 @@ from core.workflow.nodes.base.node import BaseNode from core.workflow.nodes.enums import NodeType from core.workflow.nodes.llm import ModelConfig, llm_utils from core.workflow.utils import variable_template_parser +from factories.variable_factory import build_segment_with_type from .entities import ParameterExtractorNodeData from .exc import ( @@ -109,6 +111,10 @@ class ParameterExtractorNode(BaseNode): } } + @classmethod + def version(cls) -> str: + return "1" + def _run(self): """ Run the node. @@ -247,7 +253,12 @@ class ParameterExtractorNode(BaseNode): status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=inputs, process_data=process_data, - outputs={"__is_success": 1 if not error else 0, "__reason": error, **result}, + outputs={ + "__is_success": 1 if not error else 0, + "__reason": error, + "__usage": jsonable_encoder(usage), + **result, + }, metadata={ WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: usage.total_tokens, WorkflowNodeExecutionMetadataKey.TOTAL_PRICE: usage.total_price, @@ -584,28 +595,30 @@ class ParameterExtractorNode(BaseNode): elif parameter.type in {"string", "select"}: if isinstance(result[parameter.name], str): transformed_result[parameter.name] = result[parameter.name] - elif parameter.type.startswith("array"): + elif parameter.is_array_type(): if isinstance(result[parameter.name], list): - nested_type = parameter.type[6:-1] - transformed_result[parameter.name] = [] + nested_type = parameter.element_type() + assert nested_type is not None + segment_value = build_segment_with_type(segment_type=SegmentType(parameter.type), value=[]) + transformed_result[parameter.name] = segment_value for item in result[parameter.name]: if nested_type == "number": if isinstance(item, int | float): - transformed_result[parameter.name].append(item) + segment_value.value.append(item) elif isinstance(item, str): try: if "." in item: - transformed_result[parameter.name].append(float(item)) + segment_value.value.append(float(item)) else: - transformed_result[parameter.name].append(int(item)) + segment_value.value.append(int(item)) except ValueError: pass elif nested_type == "string": if isinstance(item, str): - transformed_result[parameter.name].append(item) + segment_value.value.append(item) elif nested_type == "object": if isinstance(item, dict): - transformed_result[parameter.name].append(item) + segment_value.value.append(item) if parameter.name not in transformed_result: if parameter.type == "number": @@ -615,7 +628,9 @@ class ParameterExtractorNode(BaseNode): elif parameter.type in {"string", "select"}: transformed_result[parameter.name] = "" elif parameter.type.startswith("array"): - transformed_result[parameter.name] = [] + transformed_result[parameter.name] = build_segment_with_type( + segment_type=SegmentType(parameter.type), value=[] + ) return transformed_result diff --git a/api/core/workflow/nodes/question_classifier/question_classifier_node.py b/api/core/workflow/nodes/question_classifier/question_classifier_node.py index 1f50700c7e..74024ed90c 100644 --- a/api/core/workflow/nodes/question_classifier/question_classifier_node.py +++ b/api/core/workflow/nodes/question_classifier/question_classifier_node.py @@ -40,6 +40,10 @@ class QuestionClassifierNode(LLMNode): _node_data_cls = QuestionClassifierNodeData # type: ignore _node_type = NodeType.QUESTION_CLASSIFIER + @classmethod + def version(cls): + return "1" + def _run(self): node_data = cast(QuestionClassifierNodeData, self.node_data) variable_pool = self.graph_runtime_state.variable_pool @@ -141,7 +145,11 @@ class QuestionClassifierNode(LLMNode): "model_provider": model_config.provider, "model_name": model_config.model, } - outputs = {"class_name": category_name, "class_id": category_id} + outputs = { + "class_name": category_name, + "class_id": category_id, + "usage": jsonable_encoder(usage), + } return NodeRunResult( status=WorkflowNodeExecutionStatus.SUCCEEDED, diff --git a/api/core/workflow/nodes/start/start_node.py b/api/core/workflow/nodes/start/start_node.py index 8839aec9d6..5ee9bc331f 100644 --- a/api/core/workflow/nodes/start/start_node.py +++ b/api/core/workflow/nodes/start/start_node.py @@ -10,6 +10,10 @@ class StartNode(BaseNode[StartNodeData]): _node_data_cls = StartNodeData _node_type = NodeType.START + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: node_inputs = dict(self.graph_runtime_state.variable_pool.user_inputs) system_inputs = self.graph_runtime_state.variable_pool.system_variables @@ -18,5 +22,6 @@ class StartNode(BaseNode[StartNodeData]): # Set system variables as node outputs. for var in system_inputs: node_inputs[SYSTEM_VARIABLE_NODE_ID + "." + var] = system_inputs[var] + outputs = dict(node_inputs) - return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=node_inputs, outputs=node_inputs) + return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=node_inputs, outputs=outputs) diff --git a/api/core/workflow/nodes/template_transform/template_transform_node.py b/api/core/workflow/nodes/template_transform/template_transform_node.py index 476cf7eee4..ba573074c3 100644 --- a/api/core/workflow/nodes/template_transform/template_transform_node.py +++ b/api/core/workflow/nodes/template_transform/template_transform_node.py @@ -28,6 +28,10 @@ class TemplateTransformNode(BaseNode[TemplateTransformNodeData]): "config": {"variables": [{"variable": "arg1", "value_selector": []}], "template": "{{ arg1 }}"}, } + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: # Get variables variables = {} diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index aaecc7b989..59b3b1e2ae 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -1,18 +1,19 @@ from collections.abc import Generator, Mapping, Sequence -from typing import Any, cast +from typing import Any, Optional, cast from sqlalchemy import select from sqlalchemy.orm import Session from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler from core.file import File, FileTransferMethod +from core.model_runtime.entities.llm_entities import LLMUsage from core.plugin.impl.exc import PluginDaemonClientSideError from core.plugin.impl.plugin import PluginInstaller from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter from core.tools.errors import ToolInvokeError from core.tools.tool_engine import ToolEngine from core.tools.utils.message_transformer import ToolFileMessageTransformer -from core.variables.segments import ArrayAnySegment +from core.variables.segments import ArrayAnySegment, ArrayFileSegment from core.variables.variables import ArrayAnyVariable from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.variable_pool import VariablePool @@ -44,6 +45,10 @@ class ToolNode(BaseNode[ToolNodeData]): _node_data_cls = ToolNodeData _node_type = NodeType.TOOL + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> Generator: """ Run the tool node @@ -163,7 +168,9 @@ class ToolNode(BaseNode[ToolNodeData]): if tool_input.type == "variable": variable = variable_pool.get(tool_input.value) if variable is None: - raise ToolParameterError(f"Variable {tool_input.value} does not exist") + if parameter.required: + raise ToolParameterError(f"Variable {tool_input.value} does not exist") + continue parameter_value = variable.value elif tool_input.type in {"mixed", "constant"}: segment_group = variable_pool.convert_template(str(tool_input.value)) @@ -184,6 +191,7 @@ class ToolNode(BaseNode[ToolNodeData]): messages: Generator[ToolInvokeMessage, None, None], tool_info: Mapping[str, Any], parameters_for_log: dict[str, Any], + agent_thoughts: Optional[list] = None, ) -> Generator: """ Convert ToolInvokeMessages into tuple[plain_text, files] @@ -202,7 +210,7 @@ class ToolNode(BaseNode[ToolNodeData]): agent_logs: list[AgentLogEvent] = [] agent_execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] = {} - + llm_usage: LLMUsage | None = None variables: dict[str, Any] = {} for message in message_stream: @@ -270,9 +278,10 @@ class ToolNode(BaseNode[ToolNodeData]): elif message.type == ToolInvokeMessage.MessageType.JSON: assert isinstance(message.message, ToolInvokeMessage.JsonMessage) if self.node_type == NodeType.AGENT: - msg_metadata = message.message.json_object.pop("execution_metadata", {}) + msg_metadata: dict[str, Any] = message.message.json_object.pop("execution_metadata", {}) + llm_usage = LLMUsage.from_metadata(msg_metadata) agent_execution_metadata = { - key: value + WorkflowNodeExecutionMetadataKey(key): value for key, value in msg_metadata.items() if key in WorkflowNodeExecutionMetadataKey.__members__.values() } @@ -300,6 +309,7 @@ class ToolNode(BaseNode[ToolNodeData]): variables[variable_name] = variable_value elif message.type == ToolInvokeMessage.MessageType.FILE: assert message.meta is not None + assert isinstance(message.meta, File) files.append(message.meta["file"]) elif message.type == ToolInvokeMessage.MessageType.LOG: assert isinstance(message.message, ToolInvokeMessage.LogMessage) @@ -359,17 +369,42 @@ class ToolNode(BaseNode[ToolNodeData]): agent_logs.append(agent_log) yield agent_log - + # Add agent_logs to outputs['json'] to ensure frontend can access thinking process + json_output: dict[str, Any] = {} + if json: + if isinstance(json, list) and len(json) == 1: + # If json is a list with only one element, convert it to a dictionary + json_output = json[0] if isinstance(json[0], dict) else {"data": json[0]} + elif isinstance(json, list): + # If json is a list with multiple elements, create a dictionary containing all data + json_output = {"data": json} + + if agent_logs: + # Add agent_logs to json output + json_output["agent_logs"] = [ + { + "id": log.id, + "parent_id": log.parent_id, + "error": log.error, + "status": log.status, + "data": log.data, + "label": log.label, + "metadata": log.metadata, + "node_id": log.node_id, + } + for log in agent_logs + ] yield RunCompletedEvent( run_result=NodeRunResult( status=WorkflowNodeExecutionStatus.SUCCEEDED, - outputs={"text": text, "files": files, "json": json, **variables}, + outputs={"text": text, "files": ArrayFileSegment(value=files), "json": json_output, **variables}, metadata={ **agent_execution_metadata, WorkflowNodeExecutionMetadataKey.TOOL_INFO: tool_info, WorkflowNodeExecutionMetadataKey.AGENT_LOG: agent_logs, }, inputs=parameters_for_log, + llm_usage=llm_usage, ) ) diff --git a/api/core/workflow/nodes/variable_aggregator/variable_aggregator_node.py b/api/core/workflow/nodes/variable_aggregator/variable_aggregator_node.py index db3e25b015..96bb3e793a 100644 --- a/api/core/workflow/nodes/variable_aggregator/variable_aggregator_node.py +++ b/api/core/workflow/nodes/variable_aggregator/variable_aggregator_node.py @@ -1,3 +1,6 @@ +from collections.abc import Mapping + +from core.variables.segments import Segment from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus from core.workflow.nodes.base import BaseNode @@ -9,16 +12,20 @@ class VariableAggregatorNode(BaseNode[VariableAssignerNodeData]): _node_data_cls = VariableAssignerNodeData _node_type = NodeType.VARIABLE_AGGREGATOR + @classmethod + def version(cls) -> str: + return "1" + def _run(self) -> NodeRunResult: # Get variables - outputs = {} + outputs: dict[str, Segment | Mapping[str, Segment]] = {} inputs = {} if not self.node_data.advanced_settings or not self.node_data.advanced_settings.group_enabled: for selector in self.node_data.variables: variable = self.graph_runtime_state.variable_pool.get(selector) if variable is not None: - outputs = {"output": variable.to_object()} + outputs = {"output": variable} inputs = {".".join(selector[1:]): variable.to_object()} break @@ -28,7 +35,7 @@ class VariableAggregatorNode(BaseNode[VariableAssignerNodeData]): variable = self.graph_runtime_state.variable_pool.get(selector) if variable is not None: - outputs[group.group_name] = {"output": variable.to_object()} + outputs[group.group_name] = {"output": variable} inputs[".".join(selector[1:])] = variable.to_object() break diff --git a/api/core/workflow/nodes/variable_assigner/common/helpers.py b/api/core/workflow/nodes/variable_assigner/common/helpers.py index 8031b57fa8..0d2822233e 100644 --- a/api/core/workflow/nodes/variable_assigner/common/helpers.py +++ b/api/core/workflow/nodes/variable_assigner/common/helpers.py @@ -1,19 +1,55 @@ -from sqlalchemy import select -from sqlalchemy.orm import Session +from collections.abc import Mapping, MutableMapping, Sequence +from typing import Any, TypeVar -from core.variables import Variable -from core.workflow.nodes.variable_assigner.common.exc import VariableOperatorNodeError -from extensions.ext_database import db -from models import ConversationVariable +from pydantic import BaseModel +from core.variables import Segment +from core.variables.consts import MIN_SELECTORS_LENGTH +from core.variables.types import SegmentType -def update_conversation_variable(conversation_id: str, variable: Variable): - stmt = select(ConversationVariable).where( - ConversationVariable.id == variable.id, ConversationVariable.conversation_id == conversation_id +# Use double underscore (`__`) prefix for internal variables +# to minimize risk of collision with user-defined variable names. +_UPDATED_VARIABLES_KEY = "__updated_variables" + + +class UpdatedVariable(BaseModel): + name: str + selector: Sequence[str] + value_type: SegmentType + new_value: Any + + +_T = TypeVar("_T", bound=MutableMapping[str, Any]) + + +def variable_to_processed_data(selector: Sequence[str], seg: Segment) -> UpdatedVariable: + if len(selector) < MIN_SELECTORS_LENGTH: + raise Exception("selector too short") + node_id, var_name = selector[:2] + return UpdatedVariable( + name=var_name, + selector=list(selector[:2]), + value_type=seg.value_type, + new_value=seg.value, ) - with Session(db.engine) as session: - row = session.scalar(stmt) - if not row: - raise VariableOperatorNodeError("conversation variable not found in the database") - row.data = variable.model_dump_json() - session.commit() + + +def set_updated_variables(m: _T, updates: Sequence[UpdatedVariable]) -> _T: + m[_UPDATED_VARIABLES_KEY] = updates + return m + + +def get_updated_variables(m: Mapping[str, Any]) -> Sequence[UpdatedVariable] | None: + updated_values = m.get(_UPDATED_VARIABLES_KEY, None) + if updated_values is None: + return None + result = [] + for items in updated_values: + if isinstance(items, UpdatedVariable): + result.append(items) + elif isinstance(items, dict): + items = UpdatedVariable.model_validate(items) + result.append(items) + else: + raise TypeError(f"Invalid updated variable: {items}, type={type(items)}") + return result diff --git a/api/core/workflow/nodes/variable_assigner/common/impl.py b/api/core/workflow/nodes/variable_assigner/common/impl.py new file mode 100644 index 0000000000..8f7a44bb62 --- /dev/null +++ b/api/core/workflow/nodes/variable_assigner/common/impl.py @@ -0,0 +1,38 @@ +from sqlalchemy import Engine, select +from sqlalchemy.orm import Session + +from core.variables.variables import Variable +from models.engine import db +from models.workflow import ConversationVariable + +from .exc import VariableOperatorNodeError + + +class ConversationVariableUpdaterImpl: + _engine: Engine | None + + def __init__(self, engine: Engine | None = None) -> None: + self._engine = engine + + def _get_engine(self) -> Engine: + if self._engine: + return self._engine + return db.engine + + def update(self, conversation_id: str, variable: Variable): + stmt = select(ConversationVariable).where( + ConversationVariable.id == variable.id, ConversationVariable.conversation_id == conversation_id + ) + with Session(self._get_engine()) as session: + row = session.scalar(stmt) + if not row: + raise VariableOperatorNodeError("conversation variable not found in the database") + row.data = variable.model_dump_json() + session.commit() + + def flush(self): + pass + + +def conversation_variable_updater_factory() -> ConversationVariableUpdaterImpl: + return ConversationVariableUpdaterImpl() diff --git a/api/core/workflow/nodes/variable_assigner/v1/node.py b/api/core/workflow/nodes/variable_assigner/v1/node.py index 835e1d77b5..be5083c9c1 100644 --- a/api/core/workflow/nodes/variable_assigner/v1/node.py +++ b/api/core/workflow/nodes/variable_assigner/v1/node.py @@ -1,4 +1,9 @@ +from collections.abc import Callable, Mapping, Sequence +from typing import TYPE_CHECKING, Any, Optional, TypeAlias + from core.variables import SegmentType, Variable +from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID +from core.workflow.conversation_variable_updater import ConversationVariableUpdater from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus from core.workflow.nodes.base import BaseNode @@ -7,16 +12,71 @@ from core.workflow.nodes.variable_assigner.common import helpers as common_helpe from core.workflow.nodes.variable_assigner.common.exc import VariableOperatorNodeError from factories import variable_factory +from ..common.impl import conversation_variable_updater_factory from .node_data import VariableAssignerData, WriteMode +if TYPE_CHECKING: + from core.workflow.graph_engine import Graph, GraphInitParams, GraphRuntimeState + + +_CONV_VAR_UPDATER_FACTORY: TypeAlias = Callable[[], ConversationVariableUpdater] + class VariableAssignerNode(BaseNode[VariableAssignerData]): _node_data_cls = VariableAssignerData _node_type = NodeType.VARIABLE_ASSIGNER + _conv_var_updater_factory: _CONV_VAR_UPDATER_FACTORY + + def __init__( + self, + id: str, + config: Mapping[str, Any], + graph_init_params: "GraphInitParams", + graph: "Graph", + graph_runtime_state: "GraphRuntimeState", + previous_node_id: Optional[str] = None, + thread_pool_id: Optional[str] = None, + conv_var_updater_factory: _CONV_VAR_UPDATER_FACTORY = conversation_variable_updater_factory, + ) -> None: + super().__init__( + id=id, + config=config, + graph_init_params=graph_init_params, + graph=graph, + graph_runtime_state=graph_runtime_state, + previous_node_id=previous_node_id, + thread_pool_id=thread_pool_id, + ) + self._conv_var_updater_factory = conv_var_updater_factory + + @classmethod + def version(cls) -> str: + return "1" + + @classmethod + def _extract_variable_selector_to_variable_mapping( + cls, + *, + graph_config: Mapping[str, Any], + node_id: str, + node_data: VariableAssignerData, + ) -> Mapping[str, Sequence[str]]: + mapping = {} + assigned_variable_node_id = node_data.assigned_variable_selector[0] + if assigned_variable_node_id == CONVERSATION_VARIABLE_NODE_ID: + selector_key = ".".join(node_data.assigned_variable_selector) + key = f"{node_id}.#{selector_key}#" + mapping[key] = node_data.assigned_variable_selector + + selector_key = ".".join(node_data.input_variable_selector) + key = f"{node_id}.#{selector_key}#" + mapping[key] = node_data.input_variable_selector + return mapping def _run(self) -> NodeRunResult: + assigned_variable_selector = self.node_data.assigned_variable_selector # Should be String, Number, Object, ArrayString, ArrayNumber, ArrayObject - original_variable = self.graph_runtime_state.variable_pool.get(self.node_data.assigned_variable_selector) + original_variable = self.graph_runtime_state.variable_pool.get(assigned_variable_selector) if not isinstance(original_variable, Variable): raise VariableOperatorNodeError("assigned variable not found") @@ -44,20 +104,28 @@ class VariableAssignerNode(BaseNode[VariableAssignerData]): raise VariableOperatorNodeError(f"unsupported write mode: {self.node_data.write_mode}") # Over write the variable. - self.graph_runtime_state.variable_pool.add(self.node_data.assigned_variable_selector, updated_variable) + self.graph_runtime_state.variable_pool.add(assigned_variable_selector, updated_variable) # TODO: Move database operation to the pipeline. # Update conversation variable. conversation_id = self.graph_runtime_state.variable_pool.get(["sys", "conversation_id"]) if not conversation_id: raise VariableOperatorNodeError("conversation_id not found") - common_helpers.update_conversation_variable(conversation_id=conversation_id.text, variable=updated_variable) + conv_var_updater = self._conv_var_updater_factory() + conv_var_updater.update(conversation_id=conversation_id.text, variable=updated_variable) + conv_var_updater.flush() + updated_variables = [common_helpers.variable_to_processed_data(assigned_variable_selector, updated_variable)] return NodeRunResult( status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs={ "value": income_value.to_object(), }, + # NOTE(QuantumGhost): although only one variable is updated in `v1.VariableAssignerNode`, + # we still set `output_variables` as a list to ensure the schema of output is + # compatible with `v2.VariableAssignerNode`. + process_data=common_helpers.set_updated_variables({}, updated_variables), + outputs={}, ) diff --git a/api/core/workflow/nodes/variable_assigner/v2/entities.py b/api/core/workflow/nodes/variable_assigner/v2/entities.py index 01df33b6d4..d93affcd15 100644 --- a/api/core/workflow/nodes/variable_assigner/v2/entities.py +++ b/api/core/workflow/nodes/variable_assigner/v2/entities.py @@ -12,6 +12,12 @@ class VariableOperationItem(BaseModel): variable_selector: Sequence[str] input_type: InputType operation: Operation + # NOTE(QuantumGhost): The `value` field serves multiple purposes depending on context: + # + # 1. For CONSTANT input_type: Contains the literal value to be used in the operation. + # 2. For VARIABLE input_type: Initially contains the selector of the source variable. + # 3. During the variable updating procedure: The `value` field is reassigned to hold + # the resolved actual value that will be applied to the target variable. value: Any | None = None diff --git a/api/core/workflow/nodes/variable_assigner/v2/exc.py b/api/core/workflow/nodes/variable_assigner/v2/exc.py index b67af6d73c..fd6c304a9a 100644 --- a/api/core/workflow/nodes/variable_assigner/v2/exc.py +++ b/api/core/workflow/nodes/variable_assigner/v2/exc.py @@ -29,3 +29,8 @@ class InvalidInputValueError(VariableOperatorNodeError): class ConversationIDNotFoundError(VariableOperatorNodeError): def __init__(self): super().__init__("conversation_id not found") + + +class InvalidDataError(VariableOperatorNodeError): + def __init__(self, message: str) -> None: + super().__init__(message) diff --git a/api/core/workflow/nodes/variable_assigner/v2/node.py b/api/core/workflow/nodes/variable_assigner/v2/node.py index 8759a55b34..9292da6f1c 100644 --- a/api/core/workflow/nodes/variable_assigner/v2/node.py +++ b/api/core/workflow/nodes/variable_assigner/v2/node.py @@ -1,34 +1,84 @@ import json -from collections.abc import Sequence -from typing import Any, cast +from collections.abc import Callable, Mapping, MutableMapping, Sequence +from typing import Any, TypeAlias, cast from core.app.entities.app_invoke_entities import InvokeFrom from core.variables import SegmentType, Variable +from core.variables.consts import MIN_SELECTORS_LENGTH from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID +from core.workflow.conversation_variable_updater import ConversationVariableUpdater from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus from core.workflow.nodes.base import BaseNode from core.workflow.nodes.enums import NodeType from core.workflow.nodes.variable_assigner.common import helpers as common_helpers from core.workflow.nodes.variable_assigner.common.exc import VariableOperatorNodeError +from core.workflow.nodes.variable_assigner.common.impl import conversation_variable_updater_factory from . import helpers from .constants import EMPTY_VALUE_MAPPING -from .entities import VariableAssignerNodeData +from .entities import VariableAssignerNodeData, VariableOperationItem from .enums import InputType, Operation from .exc import ( ConversationIDNotFoundError, InputTypeNotSupportedError, + InvalidDataError, InvalidInputValueError, OperationNotSupportedError, VariableNotFoundError, ) +_CONV_VAR_UPDATER_FACTORY: TypeAlias = Callable[[], ConversationVariableUpdater] + + +def _target_mapping_from_item(mapping: MutableMapping[str, Sequence[str]], node_id: str, item: VariableOperationItem): + selector_node_id = item.variable_selector[0] + if selector_node_id != CONVERSATION_VARIABLE_NODE_ID: + return + selector_str = ".".join(item.variable_selector) + key = f"{node_id}.#{selector_str}#" + mapping[key] = item.variable_selector + + +def _source_mapping_from_item(mapping: MutableMapping[str, Sequence[str]], node_id: str, item: VariableOperationItem): + # Keep this in sync with the logic in _run methods... + if item.input_type != InputType.VARIABLE: + return + selector = item.value + if not isinstance(selector, list): + raise InvalidDataError(f"selector is not a list, {node_id=}, {item=}") + if len(selector) < MIN_SELECTORS_LENGTH: + raise InvalidDataError(f"selector too short, {node_id=}, {item=}") + selector_str = ".".join(selector) + key = f"{node_id}.#{selector_str}#" + mapping[key] = selector + class VariableAssignerNode(BaseNode[VariableAssignerNodeData]): _node_data_cls = VariableAssignerNodeData _node_type = NodeType.VARIABLE_ASSIGNER + def _conv_var_updater_factory(self) -> ConversationVariableUpdater: + return conversation_variable_updater_factory() + + @classmethod + def version(cls) -> str: + return "2" + + @classmethod + def _extract_variable_selector_to_variable_mapping( + cls, + *, + graph_config: Mapping[str, Any], + node_id: str, + node_data: VariableAssignerNodeData, + ) -> Mapping[str, Sequence[str]]: + var_mapping: dict[str, Sequence[str]] = {} + for item in node_data.items: + _target_mapping_from_item(var_mapping, node_id, item) + _source_mapping_from_item(var_mapping, node_id, item) + return var_mapping + def _run(self) -> NodeRunResult: inputs = self.node_data.model_dump() process_data: dict[str, Any] = {} @@ -114,6 +164,7 @@ class VariableAssignerNode(BaseNode[VariableAssignerNodeData]): # remove the duplicated items first. updated_variable_selectors = list(set(map(tuple, updated_variable_selectors))) + conv_var_updater = self._conv_var_updater_factory() # Update variables for selector in updated_variable_selectors: variable = self.graph_runtime_state.variable_pool.get(selector) @@ -128,15 +179,23 @@ class VariableAssignerNode(BaseNode[VariableAssignerNodeData]): raise ConversationIDNotFoundError else: conversation_id = conversation_id.value - common_helpers.update_conversation_variable( + conv_var_updater.update( conversation_id=cast(str, conversation_id), variable=variable, ) - + conv_var_updater.flush() + updated_variables = [ + common_helpers.variable_to_processed_data(selector, seg) + for selector in updated_variable_selectors + if (seg := self.graph_runtime_state.variable_pool.get(selector)) is not None + ] + + process_data = common_helpers.set_updated_variables(process_data, updated_variables) return NodeRunResult( status=WorkflowNodeExecutionStatus.SUCCEEDED, inputs=inputs, process_data=process_data, + outputs={}, ) def _handle_item( diff --git a/api/core/workflow/repositories/draft_variable_repository.py b/api/core/workflow/repositories/draft_variable_repository.py new file mode 100644 index 0000000000..cadc23f845 --- /dev/null +++ b/api/core/workflow/repositories/draft_variable_repository.py @@ -0,0 +1,32 @@ +import abc +from collections.abc import Mapping +from typing import Any, Protocol + +from sqlalchemy.orm import Session + +from core.workflow.nodes.enums import NodeType + + +class DraftVariableSaver(Protocol): + @abc.abstractmethod + def save(self, process_data: Mapping[str, Any] | None, outputs: Mapping[str, Any] | None): + pass + + +class DraftVariableSaverFactory(Protocol): + @abc.abstractmethod + def __call__( + self, + session: Session, + app_id: str, + node_id: str, + node_type: NodeType, + node_execution_id: str, + enclosing_node_id: str | None = None, + ) -> "DraftVariableSaver": + pass + + +class NoopDraftVariableSaver(DraftVariableSaver): + def save(self, process_data: Mapping[str, Any] | None, outputs: Mapping[str, Any] | None): + pass diff --git a/api/core/workflow/utils/structured_output/entities.py b/api/core/workflow/utils/structured_output/entities.py deleted file mode 100644 index 6491042bfe..0000000000 --- a/api/core/workflow/utils/structured_output/entities.py +++ /dev/null @@ -1,16 +0,0 @@ -from enum import StrEnum - - -class ResponseFormat(StrEnum): - """Constants for model response formats""" - - JSON_SCHEMA = "json_schema" # model's structured output mode. some model like gemini, gpt-4o, support this mode. - JSON = "JSON" # model's json mode. some model like claude support this mode. - JSON_OBJECT = "json_object" # json mode's another alias. some model like deepseek-chat, qwen use this alias. - - -class SpecialModelType(StrEnum): - """Constants for identifying model types""" - - GEMINI = "gemini" - OLLAMA = "ollama" diff --git a/api/core/workflow/utils/structured_output/prompt.py b/api/core/workflow/utils/structured_output/prompt.py deleted file mode 100644 index 06d9b2056e..0000000000 --- a/api/core/workflow/utils/structured_output/prompt.py +++ /dev/null @@ -1,17 +0,0 @@ -STRUCTURED_OUTPUT_PROMPT = """You’re a helpful AI assistant. You could answer questions and output in JSON format. -constraints: - - You must output in JSON format. - - Do not output boolean value, use string type instead. - - Do not output integer or float value, use number type instead. -eg: - Here is the JSON schema: - {"additionalProperties": false, "properties": {"age": {"type": "number"}, "name": {"type": "string"}}, "required": ["name", "age"], "type": "object"} - - Here is the user's question: - My name is John Doe and I am 30 years old. - - output: - {"name": "John Doe", "age": 30} -Here is the JSON schema: -{{schema}} -""" # noqa: E501 diff --git a/api/core/workflow/utils/variable_utils.py b/api/core/workflow/utils/variable_utils.py new file mode 100644 index 0000000000..868868315b --- /dev/null +++ b/api/core/workflow/utils/variable_utils.py @@ -0,0 +1,29 @@ +from core.variables.segments import ObjectSegment, Segment +from core.workflow.entities.variable_pool import VariablePool, VariableValue + + +def append_variables_recursively( + pool: VariablePool, node_id: str, variable_key_list: list[str], variable_value: VariableValue | Segment +): + """ + Append variables recursively + :param pool: variable pool to append variables to + :param node_id: node id + :param variable_key_list: variable key list + :param variable_value: variable value + :return: + """ + pool.add([node_id] + variable_key_list, variable_value) + + # if variable_value is a dict, then recursively append variables + if isinstance(variable_value, ObjectSegment): + variable_dict = variable_value.value + elif isinstance(variable_value, dict): + variable_dict = variable_value + else: + return + + for key, value in variable_dict.items(): + # construct new key list + new_key_list = variable_key_list + [key] + append_variables_recursively(pool, node_id=node_id, variable_key_list=new_key_list, variable_value=value) diff --git a/api/core/workflow/variable_loader.py b/api/core/workflow/variable_loader.py new file mode 100644 index 0000000000..1e13871d0a --- /dev/null +++ b/api/core/workflow/variable_loader.py @@ -0,0 +1,84 @@ +import abc +from collections.abc import Mapping, Sequence +from typing import Any, Protocol + +from core.variables import Variable +from core.variables.consts import MIN_SELECTORS_LENGTH +from core.workflow.entities.variable_pool import VariablePool +from core.workflow.utils import variable_utils + + +class VariableLoader(Protocol): + """Interface for loading variables based on selectors. + + A `VariableLoader` is responsible for retrieving additional variables required during the execution + of a single node, which are not provided as user inputs. + + NOTE(QuantumGhost): Typically, all variables loaded by a `VariableLoader` should belong to the same + application and share the same `app_id`. However, this interface does not enforce that constraint, + and the `app_id` parameter is intentionally omitted from `load_variables` to achieve separation of + concern and allow for flexible implementations. + + Implementations of `VariableLoader` should almost always have an `app_id` parameter in + their constructor. + + TODO(QuantumGhost): this is a temporally workaround. If we can move the creation of node instance into + `WorkflowService.single_step_run`, we may get rid of this interface. + """ + + @abc.abstractmethod + def load_variables(self, selectors: list[list[str]]) -> list[Variable]: + """Load variables based on the provided selectors. If the selectors are empty, + this method should return an empty list. + + The order of the returned variables is not guaranteed. If the caller wants to ensure + a specific order, they should sort the returned list themselves. + + :param: selectors: a list of string list, each inner list should have at least two elements: + - the first element is the node ID, + - the second element is the variable name. + :return: a list of Variable objects that match the provided selectors. + """ + pass + + +class _DummyVariableLoader(VariableLoader): + """A dummy implementation of VariableLoader that does not load any variables. + Serves as a placeholder when no variable loading is needed. + """ + + def load_variables(self, selectors: list[list[str]]) -> list[Variable]: + return [] + + +DUMMY_VARIABLE_LOADER = _DummyVariableLoader() + + +def load_into_variable_pool( + variable_loader: VariableLoader, + variable_pool: VariablePool, + variable_mapping: Mapping[str, Sequence[str]], + user_inputs: Mapping[str, Any], +): + # Loading missing variable from draft var here, and set it into + # variable_pool. + variables_to_load: list[list[str]] = [] + for key, selector in variable_mapping.items(): + # NOTE(QuantumGhost): this logic needs to be in sync with + # `WorkflowEntry.mapping_user_inputs_to_variable_pool`. + node_variable_list = key.split(".") + if len(node_variable_list) < 1: + raise ValueError(f"Invalid variable key: {key}. It should have at least one element.") + if key in user_inputs: + continue + node_variable_key = ".".join(node_variable_list[1:]) + if node_variable_key in user_inputs: + continue + if variable_pool.get(selector) is None: + variables_to_load.append(list(selector)) + loaded = variable_loader.load_variables(variables_to_load) + for var in loaded: + assert len(var.selector) >= MIN_SELECTORS_LENGTH, f"Invalid variable {var}" + variable_utils.append_variables_recursively( + variable_pool, node_id=var.selector[0], variable_key_list=list(var.selector[1:]), variable_value=var + ) diff --git a/api/core/workflow/workflow_cycle_manager.py b/api/core/workflow/workflow_cycle_manager.py index b88f9edd03..0aab2426af 100644 --- a/api/core/workflow/workflow_cycle_manager.py +++ b/api/core/workflow/workflow_cycle_manager.py @@ -27,6 +27,7 @@ from core.workflow.enums import SystemVariableKey from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository from core.workflow.workflow_entry import WorkflowEntry +from libs.datetime_utils import naive_utc_now @dataclass @@ -92,7 +93,7 @@ class WorkflowCycleManager: ) -> WorkflowExecution: workflow_execution = self._get_workflow_execution_or_raise_error(workflow_run_id) - outputs = WorkflowEntry.handle_special_values(outputs) + # outputs = WorkflowEntry.handle_special_values(outputs) workflow_execution.status = WorkflowExecutionStatus.SUCCEEDED workflow_execution.outputs = outputs or {} @@ -125,7 +126,7 @@ class WorkflowCycleManager: trace_manager: Optional[TraceQueueManager] = None, ) -> WorkflowExecution: execution = self._get_workflow_execution_or_raise_error(workflow_run_id) - outputs = WorkflowEntry.handle_special_values(dict(outputs) if outputs else None) + # outputs = WorkflowEntry.handle_special_values(dict(outputs) if outputs else None) execution.status = WorkflowExecutionStatus.PARTIAL_SUCCEEDED execution.outputs = outputs or {} @@ -160,12 +161,13 @@ class WorkflowCycleManager: exceptions_count: int = 0, ) -> WorkflowExecution: workflow_execution = self._get_workflow_execution_or_raise_error(workflow_run_id) + now = naive_utc_now() workflow_execution.status = WorkflowExecutionStatus(status.value) workflow_execution.error_message = error_message workflow_execution.total_tokens = total_tokens workflow_execution.total_steps = total_steps - workflow_execution.finished_at = datetime.now(UTC).replace(tzinfo=None) + workflow_execution.finished_at = now workflow_execution.exceptions_count = exceptions_count # Use the instance repository to find running executions for a workflow run @@ -174,7 +176,6 @@ class WorkflowCycleManager: ) # Update the domain models - now = datetime.now(UTC).replace(tzinfo=None) for node_execution in running_node_executions: if node_execution.node_execution_id: # Update the domain model @@ -242,9 +243,9 @@ class WorkflowCycleManager: raise ValueError(f"Domain node execution not found: {event.node_execution_id}") # Process data - inputs = WorkflowEntry.handle_special_values(event.inputs) - process_data = WorkflowEntry.handle_special_values(event.process_data) - outputs = WorkflowEntry.handle_special_values(event.outputs) + inputs = event.inputs + process_data = event.process_data + outputs = event.outputs # Convert metadata keys to strings execution_metadata_dict = {} @@ -289,7 +290,7 @@ class WorkflowCycleManager: # Process data inputs = WorkflowEntry.handle_special_values(event.inputs) process_data = WorkflowEntry.handle_special_values(event.process_data) - outputs = WorkflowEntry.handle_special_values(event.outputs) + outputs = event.outputs # Convert metadata keys to strings execution_metadata_dict = {} @@ -326,7 +327,7 @@ class WorkflowCycleManager: finished_at = datetime.now(UTC).replace(tzinfo=None) elapsed_time = (finished_at - created_at).total_seconds() inputs = WorkflowEntry.handle_special_values(event.inputs) - outputs = WorkflowEntry.handle_special_values(event.outputs) + outputs = event.outputs # Convert metadata keys to strings origin_metadata = { diff --git a/api/core/workflow/workflow_entry.py b/api/core/workflow/workflow_entry.py index 7648947fca..2868dcb7de 100644 --- a/api/core/workflow/workflow_entry.py +++ b/api/core/workflow/workflow_entry.py @@ -21,6 +21,7 @@ from core.workflow.nodes import NodeType from core.workflow.nodes.base import BaseNode from core.workflow.nodes.event import NodeEvent from core.workflow.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING +from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader, load_into_variable_pool from factories import file_factory from models.enums import UserFrom from models.workflow import ( @@ -68,6 +69,7 @@ class WorkflowEntry: raise ValueError("Max workflow call depth {} reached.".format(workflow_call_max_depth)) # init workflow run state + graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) self.graph_engine = GraphEngine( tenant_id=tenant_id, app_id=app_id, @@ -79,7 +81,7 @@ class WorkflowEntry: call_depth=call_depth, graph=graph, graph_config=graph_config, - variable_pool=variable_pool, + graph_runtime_state=graph_runtime_state, max_execution_steps=dify_config.WORKFLOW_MAX_EXECUTION_STEPS, max_execution_time=dify_config.WORKFLOW_MAX_EXECUTION_TIME, thread_pool_id=thread_pool_id, @@ -119,7 +121,9 @@ class WorkflowEntry: workflow: Workflow, node_id: str, user_id: str, - user_inputs: dict, + user_inputs: Mapping[str, Any], + variable_pool: VariablePool, + variable_loader: VariableLoader = DUMMY_VARIABLE_LOADER, ) -> tuple[BaseNode, Generator[NodeEvent | InNodeEvent, None, None]]: """ Single step run workflow node @@ -129,29 +133,14 @@ class WorkflowEntry: :param user_inputs: user inputs :return: """ - # fetch node info from workflow graph - workflow_graph = workflow.graph_dict - if not workflow_graph: - raise ValueError("workflow graph not found") - - nodes = workflow_graph.get("nodes") - if not nodes: - raise ValueError("nodes not found in workflow graph") - - # fetch node config from node id - try: - node_config = next(filter(lambda node: node["id"] == node_id, nodes)) - except StopIteration: - raise ValueError("node id not found in workflow graph") + node_config = workflow.get_node_config_by_id(node_id) + node_config_data = node_config.get("data", {}) # Get node class - node_type = NodeType(node_config.get("data", {}).get("type")) - node_version = node_config.get("data", {}).get("version", "1") + node_type = NodeType(node_config_data.get("type")) + node_version = node_config_data.get("version", "1") node_cls = NODE_TYPE_CLASSES_MAPPING[node_type][node_version] - # init variable pool - variable_pool = VariablePool(environment_variables=workflow.environment_variables) - # init graph graph = Graph.init(graph_config=workflow.graph_dict) @@ -182,16 +171,33 @@ class WorkflowEntry: except NotImplementedError: variable_mapping = {} + # Loading missing variable from draft var here, and set it into + # variable_pool. + load_into_variable_pool( + variable_loader=variable_loader, + variable_pool=variable_pool, + variable_mapping=variable_mapping, + user_inputs=user_inputs, + ) + cls.mapping_user_inputs_to_variable_pool( variable_mapping=variable_mapping, user_inputs=user_inputs, variable_pool=variable_pool, tenant_id=workflow.tenant_id, ) + try: # run node generator = node_instance.run() except Exception as e: + logger.exception( + "error while running node_instance, workflow_id=%s, node_id=%s, type=%s, version=%s", + workflow.id, + node_instance.id, + node_instance.node_type, + node_instance.version(), + ) raise WorkflowNodeRunFailedError(node_instance=node_instance, error=str(e)) return node_instance, generator @@ -294,10 +300,20 @@ class WorkflowEntry: return node_instance, generator except Exception as e: + logger.exception( + "error while running node_instance, node_id=%s, type=%s, version=%s", + node_instance.id, + node_instance.node_type, + node_instance.version(), + ) raise WorkflowNodeRunFailedError(node_instance=node_instance, error=str(e)) @staticmethod def handle_special_values(value: Optional[Mapping[str, Any]]) -> Mapping[str, Any] | None: + # NOTE(QuantumGhost): Avoid using this function in new code. + # Keep values structured as long as possible and only convert to dict + # immediately before serialization (e.g., JSON serialization) to maintain + # data integrity and type information. result = WorkflowEntry._handle_special_values(value) return result if isinstance(result, Mapping) or result is None else dict(result) @@ -324,10 +340,17 @@ class WorkflowEntry: cls, *, variable_mapping: Mapping[str, Sequence[str]], - user_inputs: dict, + user_inputs: Mapping[str, Any], variable_pool: VariablePool, tenant_id: str, ) -> None: + # NOTE(QuantumGhost): This logic should remain synchronized with + # the implementation of `load_into_variable_pool`, specifically the logic about + # variable existence checking. + + # WARNING(QuantumGhost): The semantics of this method are not clearly defined, + # and multiple parts of the codebase depend on its current behavior. + # Modify with caution. for node_variable, variable_selector in variable_mapping.items(): # fetch node id and variable key from node_variable node_variable_list = node_variable.split(".") diff --git a/api/core/workflow/workflow_type_encoder.py b/api/core/workflow/workflow_type_encoder.py new file mode 100644 index 0000000000..0123fdac18 --- /dev/null +++ b/api/core/workflow/workflow_type_encoder.py @@ -0,0 +1,49 @@ +import json +from collections.abc import Mapping +from typing import Any + +from pydantic import BaseModel + +from core.file.models import File +from core.variables import Segment + + +class WorkflowRuntimeTypeEncoder(json.JSONEncoder): + def default(self, o: Any): + if isinstance(o, Segment): + return o.value + elif isinstance(o, File): + return o.to_dict() + elif isinstance(o, BaseModel): + return o.model_dump(mode="json") + else: + return super().default(o) + + +class WorkflowRuntimeTypeConverter: + def to_json_encodable(self, value: Mapping[str, Any] | None) -> Mapping[str, Any] | None: + result = self._to_json_encodable_recursive(value) + return result if isinstance(result, Mapping) or result is None else dict(result) + + def _to_json_encodable_recursive(self, value: Any) -> Any: + if value is None: + return value + if isinstance(value, (bool, int, str, float)): + return value + if isinstance(value, Segment): + return self._to_json_encodable_recursive(value.value) + if isinstance(value, File): + return value.to_dict() + if isinstance(value, BaseModel): + return value.model_dump(mode="json") + if isinstance(value, dict): + res = {} + for k, v in value.items(): + res[k] = self._to_json_encodable_recursive(v) + return res + if isinstance(value, list): + res_list = [] + for item in value: + res_list.append(self._to_json_encodable_recursive(item)) + return res_list + return value diff --git a/api/events/event_handlers/__init__.py b/api/events/event_handlers/__init__.py index 1d6ad35333..ebc55d5ef8 100644 --- a/api/events/event_handlers/__init__.py +++ b/api/events/event_handlers/__init__.py @@ -3,8 +3,10 @@ from .clean_when_document_deleted import handle from .create_document_index import handle from .create_installed_app_when_app_created import handle from .create_site_record_when_app_created import handle -from .deduct_quota_when_message_created import handle from .delete_tool_parameters_cache_when_sync_draft_workflow import handle from .update_app_dataset_join_when_app_model_config_updated import handle from .update_app_dataset_join_when_app_published_workflow_updated import handle -from .update_provider_last_used_at_when_message_created import handle + +# Consolidated handler replaces both deduct_quota_when_message_created and +# update_provider_last_used_at_when_message_created +from .update_provider_when_message_created import handle diff --git a/api/events/event_handlers/deduct_quota_when_message_created.py b/api/events/event_handlers/deduct_quota_when_message_created.py deleted file mode 100644 index b8e7019446..0000000000 --- a/api/events/event_handlers/deduct_quota_when_message_created.py +++ /dev/null @@ -1,65 +0,0 @@ -from datetime import UTC, datetime - -from configs import dify_config -from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, ChatAppGenerateEntity -from core.entities.provider_entities import QuotaUnit -from core.plugin.entities.plugin import ModelProviderID -from events.message_event import message_was_created -from extensions.ext_database import db -from models.provider import Provider, ProviderType - - -@message_was_created.connect -def handle(sender, **kwargs): - message = sender - application_generate_entity = kwargs.get("application_generate_entity") - - if not isinstance(application_generate_entity, ChatAppGenerateEntity | AgentChatAppGenerateEntity): - return - - model_config = application_generate_entity.model_conf - provider_model_bundle = model_config.provider_model_bundle - provider_configuration = provider_model_bundle.configuration - - if provider_configuration.using_provider_type != ProviderType.SYSTEM: - return - - system_configuration = provider_configuration.system_configuration - - if not system_configuration.current_quota_type: - return - - quota_unit = None - for quota_configuration in system_configuration.quota_configurations: - if quota_configuration.quota_type == system_configuration.current_quota_type: - quota_unit = quota_configuration.quota_unit - - if quota_configuration.quota_limit == -1: - return - - break - - used_quota = None - if quota_unit: - if quota_unit == QuotaUnit.TOKENS: - used_quota = message.message_tokens + message.answer_tokens - elif quota_unit == QuotaUnit.CREDITS: - used_quota = dify_config.get_model_credits(model_config.model) - else: - used_quota = 1 - - if used_quota is not None and system_configuration.current_quota_type is not None: - db.session.query(Provider).filter( - Provider.tenant_id == application_generate_entity.app_config.tenant_id, - # TODO: Use provider name with prefix after the data migration. - Provider.provider_name == ModelProviderID(model_config.provider).provider_name, - Provider.provider_type == ProviderType.SYSTEM.value, - Provider.quota_type == system_configuration.current_quota_type.value, - Provider.quota_limit > Provider.quota_used, - ).update( - { - "quota_used": Provider.quota_used + used_quota, - "last_used": datetime.now(tz=UTC).replace(tzinfo=None), - } - ) - db.session.commit() diff --git a/api/events/event_handlers/update_provider_last_used_at_when_message_created.py b/api/events/event_handlers/update_provider_last_used_at_when_message_created.py deleted file mode 100644 index 59412cf87c..0000000000 --- a/api/events/event_handlers/update_provider_last_used_at_when_message_created.py +++ /dev/null @@ -1,20 +0,0 @@ -from datetime import UTC, datetime - -from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, ChatAppGenerateEntity -from events.message_event import message_was_created -from extensions.ext_database import db -from models.provider import Provider - - -@message_was_created.connect -def handle(sender, **kwargs): - application_generate_entity = kwargs.get("application_generate_entity") - - if not isinstance(application_generate_entity, ChatAppGenerateEntity | AgentChatAppGenerateEntity): - return - - db.session.query(Provider).filter( - Provider.tenant_id == application_generate_entity.app_config.tenant_id, - Provider.provider_name == application_generate_entity.model_conf.provider, - ).update({"last_used": datetime.now(UTC).replace(tzinfo=None)}) - db.session.commit() diff --git a/api/events/event_handlers/update_provider_when_message_created.py b/api/events/event_handlers/update_provider_when_message_created.py new file mode 100644 index 0000000000..d3943f2eda --- /dev/null +++ b/api/events/event_handlers/update_provider_when_message_created.py @@ -0,0 +1,234 @@ +import logging +import time as time_module +from datetime import datetime +from typing import Any, Optional + +from pydantic import BaseModel +from sqlalchemy import update +from sqlalchemy.orm import Session + +from configs import dify_config +from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, ChatAppGenerateEntity +from core.entities.provider_entities import QuotaUnit, SystemConfiguration +from core.plugin.entities.plugin import ModelProviderID +from events.message_event import message_was_created +from extensions.ext_database import db +from libs import datetime_utils +from models.model import Message +from models.provider import Provider, ProviderType + +logger = logging.getLogger(__name__) + + +class _ProviderUpdateFilters(BaseModel): + """Filters for identifying Provider records to update.""" + + tenant_id: str + provider_name: str + provider_type: Optional[str] = None + quota_type: Optional[str] = None + + +class _ProviderUpdateAdditionalFilters(BaseModel): + """Additional filters for Provider updates.""" + + quota_limit_check: bool = False + + +class _ProviderUpdateValues(BaseModel): + """Values to update in Provider records.""" + + last_used: Optional[datetime] = None + quota_used: Optional[Any] = None # Can be Provider.quota_used + int expression + + +class _ProviderUpdateOperation(BaseModel): + """A single Provider update operation.""" + + filters: _ProviderUpdateFilters + values: _ProviderUpdateValues + additional_filters: _ProviderUpdateAdditionalFilters = _ProviderUpdateAdditionalFilters() + description: str = "unknown" + + +@message_was_created.connect +def handle(sender: Message, **kwargs): + """ + Consolidated handler for Provider updates when a message is created. + + This handler replaces both: + - update_provider_last_used_at_when_message_created + - deduct_quota_when_message_created + + By performing all Provider updates in a single transaction, we ensure + consistency and efficiency when updating Provider records. + """ + message = sender + application_generate_entity = kwargs.get("application_generate_entity") + + if not isinstance(application_generate_entity, ChatAppGenerateEntity | AgentChatAppGenerateEntity): + return + + tenant_id = application_generate_entity.app_config.tenant_id + provider_name = application_generate_entity.model_conf.provider + current_time = datetime_utils.naive_utc_now() + + # Prepare updates for both scenarios + updates_to_perform: list[_ProviderUpdateOperation] = [] + + # 1. Always update last_used for the provider + basic_update = _ProviderUpdateOperation( + filters=_ProviderUpdateFilters( + tenant_id=tenant_id, + provider_name=provider_name, + ), + values=_ProviderUpdateValues(last_used=current_time), + description="basic_last_used_update", + ) + updates_to_perform.append(basic_update) + + # 2. Check if we need to deduct quota (system provider only) + model_config = application_generate_entity.model_conf + provider_model_bundle = model_config.provider_model_bundle + provider_configuration = provider_model_bundle.configuration + + if ( + provider_configuration.using_provider_type == ProviderType.SYSTEM + and provider_configuration.system_configuration + and provider_configuration.system_configuration.current_quota_type is not None + ): + system_configuration = provider_configuration.system_configuration + + # Calculate quota usage + used_quota = _calculate_quota_usage( + message=message, + system_configuration=system_configuration, + model_name=model_config.model, + ) + + if used_quota is not None: + quota_update = _ProviderUpdateOperation( + filters=_ProviderUpdateFilters( + tenant_id=tenant_id, + provider_name=ModelProviderID(model_config.provider).provider_name, + provider_type=ProviderType.SYSTEM.value, + quota_type=provider_configuration.system_configuration.current_quota_type.value, + ), + values=_ProviderUpdateValues(quota_used=Provider.quota_used + used_quota, last_used=current_time), + additional_filters=_ProviderUpdateAdditionalFilters( + quota_limit_check=True # Provider.quota_limit > Provider.quota_used + ), + description="quota_deduction_update", + ) + updates_to_perform.append(quota_update) + + # Execute all updates + start_time = time_module.perf_counter() + try: + _execute_provider_updates(updates_to_perform) + + # Log successful completion with timing + duration = time_module.perf_counter() - start_time + + logger.info( + f"Provider updates completed successfully. " + f"Updates: {len(updates_to_perform)}, Duration: {duration:.3f}s, " + f"Tenant: {tenant_id}, Provider: {provider_name}" + ) + + except Exception as e: + # Log failure with timing and context + duration = time_module.perf_counter() - start_time + + logger.exception( + f"Provider updates failed after {duration:.3f}s. " + f"Updates: {len(updates_to_perform)}, Tenant: {tenant_id}, " + f"Provider: {provider_name}" + ) + raise + + +def _calculate_quota_usage( + *, message: Message, system_configuration: SystemConfiguration, model_name: str +) -> Optional[int]: + """Calculate quota usage based on message tokens and quota type.""" + quota_unit = None + for quota_configuration in system_configuration.quota_configurations: + if quota_configuration.quota_type == system_configuration.current_quota_type: + quota_unit = quota_configuration.quota_unit + if quota_configuration.quota_limit == -1: + return None + break + if quota_unit is None: + return None + + try: + if quota_unit == QuotaUnit.TOKENS: + tokens = message.message_tokens + message.answer_tokens + return tokens + if quota_unit == QuotaUnit.CREDITS: + tokens = dify_config.get_model_credits(model_name) + return tokens + elif quota_unit == QuotaUnit.TIMES: + return 1 + return None + except Exception as e: + logger.exception("Failed to calculate quota usage") + return None + + +def _execute_provider_updates(updates_to_perform: list[_ProviderUpdateOperation]): + """Execute all Provider updates in a single transaction.""" + if not updates_to_perform: + return + + # Use SQLAlchemy's context manager for transaction management + # This automatically handles commit/rollback + with Session(db.engine) as session: + # Use a single transaction for all updates + for update_operation in updates_to_perform: + filters = update_operation.filters + values = update_operation.values + additional_filters = update_operation.additional_filters + description = update_operation.description + + # Build the where conditions + where_conditions = [ + Provider.tenant_id == filters.tenant_id, + Provider.provider_name == filters.provider_name, + ] + + # Add additional filters if specified + if filters.provider_type is not None: + where_conditions.append(Provider.provider_type == filters.provider_type) + if filters.quota_type is not None: + where_conditions.append(Provider.quota_type == filters.quota_type) + if additional_filters.quota_limit_check: + where_conditions.append(Provider.quota_limit > Provider.quota_used) + + # Prepare values dict for SQLAlchemy update + update_values = {} + if values.last_used is not None: + update_values["last_used"] = values.last_used + if values.quota_used is not None: + update_values["quota_used"] = values.quota_used + + # Build and execute the update statement + stmt = update(Provider).where(*where_conditions).values(**update_values) + result = session.execute(stmt) + rows_affected = result.rowcount + + logger.debug( + f"Provider update ({description}): {rows_affected} rows affected. " + f"Filters: {filters.model_dump()}, Values: {update_values}" + ) + + # If no rows were affected for quota updates, log a warning + if rows_affected == 0 and description == "quota_deduction_update": + logger.warning( + f"No Provider rows updated for quota deduction. " + f"This may indicate quota limit exceeded or provider not found. " + f"Filters: {filters.model_dump()}" + ) + + logger.debug(f"Successfully processed {len(updates_to_perform)} Provider updates") diff --git a/api/extensions/ext_app_metrics.py b/api/extensions/ext_app_metrics.py index b7d412d68d..56a69a1862 100644 --- a/api/extensions/ext_app_metrics.py +++ b/api/extensions/ext_app_metrics.py @@ -12,14 +12,14 @@ def init_app(app: DifyApp): @app.after_request def after_request(response): """Add Version headers to the response.""" - response.headers.add("X-Version", dify_config.CURRENT_VERSION) + response.headers.add("X-Version", dify_config.project.version) response.headers.add("X-Env", dify_config.DEPLOY_ENV) return response @app.route("/health") def health(): return Response( - json.dumps({"pid": os.getpid(), "status": "ok", "version": dify_config.CURRENT_VERSION}), + json.dumps({"pid": os.getpid(), "status": "ok", "version": dify_config.project.version}), status=200, content_type="application/json", ) diff --git a/api/extensions/ext_celery.py b/api/extensions/ext_celery.py index a837552007..6279b1ad36 100644 --- a/api/extensions/ext_celery.py +++ b/api/extensions/ext_celery.py @@ -21,6 +21,7 @@ def init_app(app: DifyApp) -> Celery: "master_name": dify_config.CELERY_SENTINEL_MASTER_NAME, "sentinel_kwargs": { "socket_timeout": dify_config.CELERY_SENTINEL_SOCKET_TIMEOUT, + "password": dify_config.CELERY_SENTINEL_PASSWORD, }, } diff --git a/api/extensions/ext_mail.py b/api/extensions/ext_mail.py index 84bc12eca0..df5d8a9c11 100644 --- a/api/extensions/ext_mail.py +++ b/api/extensions/ext_mail.py @@ -54,6 +54,15 @@ class Mail: use_tls=dify_config.SMTP_USE_TLS, opportunistic_tls=dify_config.SMTP_OPPORTUNISTIC_TLS, ) + case "sendgrid": + from libs.sendgrid import SendGridClient + + if not dify_config.SENDGRID_API_KEY: + raise ValueError("SENDGRID_API_KEY is required for SendGrid mail type") + + self._client = SendGridClient( + sendgrid_api_key=dify_config.SENDGRID_API_KEY, _from=dify_config.MAIL_DEFAULT_SEND_FROM or "" + ) case _: raise ValueError("Unsupported mail type {}".format(mail_type)) diff --git a/api/extensions/ext_otel.py b/api/extensions/ext_otel.py index 6dcfa7bec6..23cf4c5cab 100644 --- a/api/extensions/ext_otel.py +++ b/api/extensions/ext_otel.py @@ -49,7 +49,7 @@ def init_app(app: DifyApp): logging.getLogger().addHandler(exception_handler) def init_flask_instrumentor(app: DifyApp): - meter = get_meter("http_metrics", version=dify_config.CURRENT_VERSION) + meter = get_meter("http_metrics", version=dify_config.project.version) _http_response_counter = meter.create_counter( "http.server.response.count", description="Total number of HTTP responses by status code, method and target", @@ -163,7 +163,7 @@ def init_app(app: DifyApp): resource = Resource( attributes={ ResourceAttributes.SERVICE_NAME: dify_config.APPLICATION_NAME, - ResourceAttributes.SERVICE_VERSION: f"dify-{dify_config.CURRENT_VERSION}-{dify_config.COMMIT_SHA}", + ResourceAttributes.SERVICE_VERSION: f"dify-{dify_config.project.version}-{dify_config.COMMIT_SHA}", ResourceAttributes.PROCESS_PID: os.getpid(), ResourceAttributes.DEPLOYMENT_ENVIRONMENT: f"{dify_config.DEPLOY_ENV}-{dify_config.EDITION}", ResourceAttributes.HOST_NAME: socket.gethostname(), diff --git a/api/extensions/ext_sentry.py b/api/extensions/ext_sentry.py index 3a74aace6a..82aed0d98d 100644 --- a/api/extensions/ext_sentry.py +++ b/api/extensions/ext_sentry.py @@ -35,6 +35,6 @@ def init_app(app: DifyApp): traces_sample_rate=dify_config.SENTRY_TRACES_SAMPLE_RATE, profiles_sample_rate=dify_config.SENTRY_PROFILES_SAMPLE_RATE, environment=dify_config.DEPLOY_ENV, - release=f"dify-{dify_config.CURRENT_VERSION}-{dify_config.COMMIT_SHA}", + release=f"dify-{dify_config.project.version}-{dify_config.COMMIT_SHA}", before_send=before_send, ) diff --git a/api/factories/file_factory.py b/api/factories/file_factory.py index 52f119936f..25d1390492 100644 --- a/api/factories/file_factory.py +++ b/api/factories/file_factory.py @@ -5,6 +5,7 @@ from typing import Any, cast import httpx from sqlalchemy import select +from sqlalchemy.orm import Session from constants import AUDIO_EXTENSIONS, DOCUMENT_EXTENSIONS, IMAGE_EXTENSIONS, VIDEO_EXTENSIONS from core.file import File, FileBelongsTo, FileTransferMethod, FileType, FileUploadConfig, helpers @@ -91,6 +92,8 @@ def build_from_mappings( tenant_id: str, strict_type_validation: bool = False, ) -> Sequence[File]: + # TODO(QuantumGhost): Performance concern - each mapping triggers a separate database query. + # Implement batch processing to reduce database load when handling multiple files. files = [ build_from_mapping( mapping=mapping, @@ -377,3 +380,75 @@ def _get_file_type_by_mimetype(mime_type: str) -> FileType | None: def get_file_type_by_mime_type(mime_type: str) -> FileType: return _get_file_type_by_mimetype(mime_type) or FileType.CUSTOM + + +class StorageKeyLoader: + """FileKeyLoader load the storage key from database for a list of files. + This loader is batched, the database query count is constant regardless of the input size. + """ + + def __init__(self, session: Session, tenant_id: str) -> None: + self._session = session + self._tenant_id = tenant_id + + def _load_upload_files(self, upload_file_ids: Sequence[uuid.UUID]) -> Mapping[uuid.UUID, UploadFile]: + stmt = select(UploadFile).where( + UploadFile.id.in_(upload_file_ids), + UploadFile.tenant_id == self._tenant_id, + ) + + return {uuid.UUID(i.id): i for i in self._session.scalars(stmt)} + + def _load_tool_files(self, tool_file_ids: Sequence[uuid.UUID]) -> Mapping[uuid.UUID, ToolFile]: + stmt = select(ToolFile).where( + ToolFile.id.in_(tool_file_ids), + ToolFile.tenant_id == self._tenant_id, + ) + return {uuid.UUID(i.id): i for i in self._session.scalars(stmt)} + + def load_storage_keys(self, files: Sequence[File]): + """Loads storage keys for a sequence of files by retrieving the corresponding + `UploadFile` or `ToolFile` records from the database based on their transfer method. + + This method doesn't modify the input sequence structure but updates the `_storage_key` + property of each file object by extracting the relevant key from its database record. + + Performance note: This is a batched operation where database query count remains constant + regardless of input size. However, for optimal performance, input sequences should contain + fewer than 1000 files. For larger collections, split into smaller batches and process each + batch separately. + """ + + upload_file_ids: list[uuid.UUID] = [] + tool_file_ids: list[uuid.UUID] = [] + for file in files: + related_model_id = file.related_id + if file.related_id is None: + raise ValueError("file id should not be None.") + if file.tenant_id != self._tenant_id: + err_msg = ( + f"invalid file, expected tenant_id={self._tenant_id}, " + f"got tenant_id={file.tenant_id}, file_id={file.id}, related_model_id={related_model_id}" + ) + raise ValueError(err_msg) + model_id = uuid.UUID(related_model_id) + + if file.transfer_method in (FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL): + upload_file_ids.append(model_id) + elif file.transfer_method == FileTransferMethod.TOOL_FILE: + tool_file_ids.append(model_id) + + tool_files = self._load_tool_files(tool_file_ids) + upload_files = self._load_upload_files(upload_file_ids) + for file in files: + model_id = uuid.UUID(file.related_id) + if file.transfer_method in (FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL): + upload_file_row = upload_files.get(model_id) + if upload_file_row is None: + raise ValueError(f"Upload file not found for id: {model_id}") + file._storage_key = upload_file_row.key + elif file.transfer_method == FileTransferMethod.TOOL_FILE: + tool_file_row = tool_files.get(model_id) + if tool_file_row is None: + raise ValueError(f"Tool file not found for id: {model_id}") + file._storage_key = tool_file_row.file_key diff --git a/api/factories/variable_factory.py b/api/factories/variable_factory.py index a41ef4ae4e..250ee4695e 100644 --- a/api/factories/variable_factory.py +++ b/api/factories/variable_factory.py @@ -43,6 +43,10 @@ class UnsupportedSegmentTypeError(Exception): pass +class TypeMismatchError(Exception): + pass + + # Define the constant SEGMENT_TO_VARIABLE_MAP = { StringSegment: StringVariable, @@ -110,6 +114,10 @@ def _build_variable_from_mapping(*, mapping: Mapping[str, Any], selector: Sequen return cast(Variable, result) +def infer_segment_type_from_value(value: Any, /) -> SegmentType: + return build_segment(value).value_type + + def build_segment(value: Any, /) -> Segment: if value is None: return NoneSegment() @@ -140,10 +148,80 @@ def build_segment(value: Any, /) -> Segment: case SegmentType.NONE: return ArrayAnySegment(value=value) case _: + # This should be unreachable. raise ValueError(f"not supported value {value}") raise ValueError(f"not supported value {value}") +def build_segment_with_type(segment_type: SegmentType, value: Any) -> Segment: + """ + Build a segment with explicit type checking. + + This function creates a segment from a value while enforcing type compatibility + with the specified segment_type. It provides stricter type validation compared + to the standard build_segment function. + + Args: + segment_type: The expected SegmentType for the resulting segment + value: The value to be converted into a segment + + Returns: + Segment: A segment instance of the appropriate type + + Raises: + TypeMismatchError: If the value type doesn't match the expected segment_type + + Special Cases: + - For empty list [] values, if segment_type is array[*], returns the corresponding array type + - Type validation is performed before segment creation + + Examples: + >>> build_segment_with_type(SegmentType.STRING, "hello") + StringSegment(value="hello") + + >>> build_segment_with_type(SegmentType.ARRAY_STRING, []) + ArrayStringSegment(value=[]) + + >>> build_segment_with_type(SegmentType.STRING, 123) + # Raises TypeMismatchError + """ + # Handle None values + if value is None: + if segment_type == SegmentType.NONE: + return NoneSegment() + else: + raise TypeMismatchError(f"Expected {segment_type}, but got None") + + # Handle empty list special case for array types + if isinstance(value, list) and len(value) == 0: + if segment_type == SegmentType.ARRAY_ANY: + return ArrayAnySegment(value=value) + elif segment_type == SegmentType.ARRAY_STRING: + return ArrayStringSegment(value=value) + elif segment_type == SegmentType.ARRAY_NUMBER: + return ArrayNumberSegment(value=value) + elif segment_type == SegmentType.ARRAY_OBJECT: + return ArrayObjectSegment(value=value) + elif segment_type == SegmentType.ARRAY_FILE: + return ArrayFileSegment(value=value) + else: + raise TypeMismatchError(f"Expected {segment_type}, but got empty list") + + # Build segment using existing logic to infer actual type + inferred_segment = build_segment(value) + inferred_type = inferred_segment.value_type + + # Type compatibility checking + if inferred_type == segment_type: + return inferred_segment + + # Type mismatch - raise error with descriptive message + raise TypeMismatchError( + f"Type mismatch: expected {segment_type}, but value '{value}' " + f"(type: {type(value).__name__}) corresponds to {inferred_type}" + ) + + def segment_to_variable( *, segment: Segment, diff --git a/api/fields/workflow_fields.py b/api/fields/workflow_fields.py index 9f1bef3b36..f00ea71c54 100644 --- a/api/fields/workflow_fields.py +++ b/api/fields/workflow_fields.py @@ -17,6 +17,7 @@ class EnvironmentVariableField(fields.Raw): "name": value.name, "value": encrypter.obfuscated_token(value.value), "value_type": value.value_type.value, + "description": value.description, } if isinstance(value, Variable): return { @@ -24,6 +25,7 @@ class EnvironmentVariableField(fields.Raw): "name": value.name, "value": value.value, "value_type": value.value_type.value, + "description": value.description, } if isinstance(value, dict): value_type = value.get("value_type") diff --git a/api/fields/workflow_run_fields.py b/api/fields/workflow_run_fields.py index 74fdf8bd97..a106728e9c 100644 --- a/api/fields/workflow_run_fields.py +++ b/api/fields/workflow_run_fields.py @@ -19,7 +19,6 @@ workflow_run_for_log_fields = { workflow_run_for_list_fields = { "id": fields.String, - "sequence_number": fields.Integer, "version": fields.String, "status": fields.String, "elapsed_time": fields.Float, @@ -36,7 +35,6 @@ advanced_chat_workflow_run_for_list_fields = { "id": fields.String, "conversation_id": fields.String, "message_id": fields.String, - "sequence_number": fields.Integer, "version": fields.String, "status": fields.String, "elapsed_time": fields.Float, @@ -63,7 +61,6 @@ workflow_run_pagination_fields = { workflow_run_detail_fields = { "id": fields.String, - "sequence_number": fields.Integer, "version": fields.String, "graph": fields.Raw(attribute="graph_dict"), "inputs": fields.Raw(attribute="inputs_dict"), diff --git a/api/libs/datetime_utils.py b/api/libs/datetime_utils.py new file mode 100644 index 0000000000..e576a34629 --- /dev/null +++ b/api/libs/datetime_utils.py @@ -0,0 +1,22 @@ +import abc +import datetime +from typing import Protocol + + +class _NowFunction(Protocol): + @abc.abstractmethod + def __call__(self, tz: datetime.timezone | None) -> datetime.datetime: + pass + + +# _now_func is a callable with the _NowFunction signature. +# Its sole purpose is to abstract time retrieval, enabling +# developers to mock this behavior in tests and time-dependent scenarios. +_now_func: _NowFunction = datetime.datetime.now + + +def naive_utc_now() -> datetime.datetime: + """Return a naive datetime object (without timezone information) + representing current UTC time. + """ + return _now_func(datetime.UTC).replace(tzinfo=None) diff --git a/api/libs/file_utils.py b/api/libs/file_utils.py new file mode 100644 index 0000000000..982b2cc1ac --- /dev/null +++ b/api/libs/file_utils.py @@ -0,0 +1,30 @@ +from pathlib import Path + + +def search_file_upwards( + base_dir_path: Path, + target_file_name: str, + max_search_parent_depth: int, +) -> Path: + """ + Find a target file in the current directory or its parent directories up to a specified depth. + :param base_dir_path: Starting directory path to search from. + :param target_file_name: Name of the file to search for. + :param max_search_parent_depth: Maximum number of parent directories to search upwards. + :return: Path of the file if found, otherwise None. + """ + current_path = base_dir_path.resolve() + for _ in range(max_search_parent_depth): + candidate_path = current_path / target_file_name + if candidate_path.is_file(): + return candidate_path + parent_path = current_path.parent + if parent_path == current_path: # reached the root directory + break + else: + current_path = parent_path + + raise ValueError( + f"File '{target_file_name}' not found in the directory '{base_dir_path.resolve()}' or its parent directories" + f" in depth of {max_search_parent_depth}." + ) diff --git a/api/libs/jsonutil.py b/api/libs/jsonutil.py new file mode 100644 index 0000000000..fa29671034 --- /dev/null +++ b/api/libs/jsonutil.py @@ -0,0 +1,11 @@ +import json + +from pydantic import BaseModel + + +class PydanticModelEncoder(json.JSONEncoder): + def default(self, o): + if isinstance(o, BaseModel): + return o.model_dump() + else: + super().default(o) diff --git a/api/libs/sendgrid.py b/api/libs/sendgrid.py new file mode 100644 index 0000000000..5409e3eeeb --- /dev/null +++ b/api/libs/sendgrid.py @@ -0,0 +1,45 @@ +import logging + +import sendgrid # type: ignore +from python_http_client.exceptions import ForbiddenError, UnauthorizedError +from sendgrid.helpers.mail import Content, Email, Mail, To # type: ignore + + +class SendGridClient: + def __init__(self, sendgrid_api_key: str, _from: str): + self.sendgrid_api_key = sendgrid_api_key + self._from = _from + + def send(self, mail: dict): + logging.debug("Sending email with SendGrid") + + try: + _to = mail["to"] + + if not _to: + raise ValueError("SendGridClient: Cannot send email: recipient address is missing.") + + sg = sendgrid.SendGridAPIClient(api_key=self.sendgrid_api_key) + from_email = Email(self._from) + to_email = To(_to) + subject = mail["subject"] + content = Content("text/html", mail["html"]) + mail = Mail(from_email, to_email, subject, content) + mail_json = mail.get() # type: ignore + response = sg.client.mail.send.post(request_body=mail_json) + logging.debug(response.status_code) + logging.debug(response.body) + logging.debug(response.headers) + + except TimeoutError as e: + logging.exception("SendGridClient Timeout occurred while sending email") + raise + except (UnauthorizedError, ForbiddenError) as e: + logging.exception( + "SendGridClient Authentication failed. " + "Verify that your credentials and the 'from' email address are correct" + ) + raise + except Exception as e: + logging.exception(f"SendGridClient Unexpected error occurred while sending email to {_to}") + raise diff --git a/api/libs/smtp.py b/api/libs/smtp.py index 35561f071c..b94386660e 100644 --- a/api/libs/smtp.py +++ b/api/libs/smtp.py @@ -22,7 +22,11 @@ class SMTPClient: if self.use_tls: if self.opportunistic_tls: smtp = smtplib.SMTP(self.server, self.port, timeout=10) + # Send EHLO command with the HELO domain name as the server address + smtp.ehlo(self.server) smtp.starttls() + # Resend EHLO command to identify the TLS session + smtp.ehlo(self.server) else: smtp = smtplib.SMTP_SSL(self.server, self.port, timeout=10) else: diff --git a/api/migrations/versions/2025_06_19_1633-0ab65e1cc7fa_remove_sequence_number_from_workflow_.py b/api/migrations/versions/2025_06_19_1633-0ab65e1cc7fa_remove_sequence_number_from_workflow_.py new file mode 100644 index 0000000000..29fef77798 --- /dev/null +++ b/api/migrations/versions/2025_06_19_1633-0ab65e1cc7fa_remove_sequence_number_from_workflow_.py @@ -0,0 +1,66 @@ +"""remove sequence_number from workflow_runs + +Revision ID: 0ab65e1cc7fa +Revises: 4474872b0ee6 +Create Date: 2025-06-19 16:33:13.377215 + +""" +from alembic import op +import models as models +import sqlalchemy as sa + + +# revision identifiers, used by Alembic. +revision = '0ab65e1cc7fa' +down_revision = '4474872b0ee6' +branch_labels = None +depends_on = None + + +def upgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('workflow_runs', schema=None) as batch_op: + batch_op.drop_index(batch_op.f('workflow_run_tenant_app_sequence_idx')) + batch_op.drop_column('sequence_number') + + # ### end Alembic commands ### + + +def downgrade(): + # ### commands auto generated by Alembic - please adjust! ### + + # WARNING: This downgrade CANNOT recover the original sequence_number values! + # The original sequence numbers are permanently lost after the upgrade. + # This downgrade will regenerate sequence numbers based on created_at order, + # which may result in different values than the original sequence numbers. + # + # If you need to preserve original sequence numbers, use the alternative + # migration approach that creates a backup table before removal. + + # Step 1: Add sequence_number column as nullable first + with op.batch_alter_table('workflow_runs', schema=None) as batch_op: + batch_op.add_column(sa.Column('sequence_number', sa.INTEGER(), autoincrement=False, nullable=True)) + + # Step 2: Populate sequence_number values based on created_at order within each app + # NOTE: This recreates sequence numbering logic but values will be different + # from the original sequence numbers that were removed in the upgrade + connection = op.get_bind() + connection.execute(sa.text(""" + UPDATE workflow_runs + SET sequence_number = subquery.row_num + FROM ( + SELECT id, ROW_NUMBER() OVER ( + PARTITION BY tenant_id, app_id + ORDER BY created_at, id + ) as row_num + FROM workflow_runs + ) subquery + WHERE workflow_runs.id = subquery.id + """)) + + # Step 3: Make the column NOT NULL and add the index + with op.batch_alter_table('workflow_runs', schema=None) as batch_op: + batch_op.alter_column('sequence_number', nullable=False) + batch_op.create_index(batch_op.f('workflow_run_tenant_app_sequence_idx'), ['tenant_id', 'app_id', 'sequence_number'], unique=False) + + # ### end Alembic commands ### diff --git a/api/models/_workflow_exc.py b/api/models/_workflow_exc.py new file mode 100644 index 0000000000..f6271bda47 --- /dev/null +++ b/api/models/_workflow_exc.py @@ -0,0 +1,20 @@ +"""All these exceptions are not meant to be caught by callers.""" + + +class WorkflowDataError(Exception): + """Base class for all workflow data related exceptions. + + This should be used to indicate issues with workflow data integrity, such as + no `graph` configuration, missing `nodes` field in `graph` configuration, or + similar issues. + """ + + pass + + +class NodeNotFoundError(WorkflowDataError): + """Raised when a node with the specified ID is not found in the workflow.""" + + def __init__(self, node_id: str): + super().__init__(f"Node with ID '{node_id}' not found in the workflow.") + self.node_id = node_id diff --git a/api/models/dataset.py b/api/models/dataset.py index ad43d6f371..1ec27203a0 100644 --- a/api/models/dataset.py +++ b/api/models/dataset.py @@ -140,7 +140,7 @@ class Dataset(Base): def word_count(self): return ( db.session.query(Document) - .with_entities(func.coalesce(func.sum(Document.word_count))) + .with_entities(func.coalesce(func.sum(Document.word_count), 0)) .filter(Document.dataset_id == self.id) .scalar() ) @@ -448,7 +448,7 @@ class Document(Base): def hit_count(self): return ( db.session.query(DocumentSegment) - .with_entities(func.coalesce(func.sum(DocumentSegment.hit_count))) + .with_entities(func.coalesce(func.sum(DocumentSegment.hit_count), 0)) .filter(DocumentSegment.document_id == self.id) .scalar() ) diff --git a/api/models/enums.py b/api/models/enums.py index 4434c3fec8..cc9f28a7bb 100644 --- a/api/models/enums.py +++ b/api/models/enums.py @@ -21,3 +21,12 @@ class DraftVariableType(StrEnum): NODE = "node" SYS = "sys" CONVERSATION = "conversation" + + +class MessageStatus(StrEnum): + """ + Message Status Enum + """ + + NORMAL = "normal" + ERROR = "error" diff --git a/api/models/model.py b/api/models/model.py index fa83baa9cf..93737043d5 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -611,6 +611,14 @@ class InstalledApp(Base): return tenant +class ConversationSource(StrEnum): + """This enumeration is designed for use with `Conversation.from_source`.""" + + # NOTE(QuantumGhost): The enumeration members may not cover all possible cases. + API = "api" + CONSOLE = "console" + + class Conversation(Base): __tablename__ = "conversations" __table_args__ = ( @@ -632,7 +640,14 @@ class Conversation(Base): system_instruction = db.Column(db.Text) system_instruction_tokens = db.Column(db.Integer, nullable=False, server_default=db.text("0")) status = db.Column(db.String(255), nullable=False) + + # The `invoke_from` records how the conversation is created. + # + # Its value corresponds to the members of `InvokeFrom`. + # (api/core/app/entities/app_invoke_entities.py) invoke_from = db.Column(db.String(255), nullable=True) + + # ref: ConversationSource. from_source = db.Column(db.String(255), nullable=False) from_end_user_id = db.Column(StringUUID) from_account_id = db.Column(StringUUID) @@ -661,7 +676,7 @@ class Conversation(Base): if isinstance(value, dict) and value.get("dify_model_identity") == FILE_MODEL_IDENTITY: if value["transfer_method"] == FileTransferMethod.TOOL_FILE: value["tool_file_id"] = value["related_id"] - elif value["transfer_method"] == FileTransferMethod.LOCAL_FILE: + elif value["transfer_method"] in [FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL]: value["upload_file_id"] = value["related_id"] inputs[key] = file_factory.build_from_mapping(mapping=value, tenant_id=value["tenant_id"]) elif isinstance(value, list) and all( @@ -671,7 +686,7 @@ class Conversation(Base): for item in value: if item["transfer_method"] == FileTransferMethod.TOOL_FILE: item["tool_file_id"] = item["related_id"] - elif item["transfer_method"] == FileTransferMethod.LOCAL_FILE: + elif item["transfer_method"] in [FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL]: item["upload_file_id"] = item["related_id"] inputs[key].append(file_factory.build_from_mapping(mapping=item, tenant_id=item["tenant_id"])) @@ -703,7 +718,6 @@ class Conversation(Base): if "model" in override_model_configs: app_model_config = AppModelConfig() app_model_config = app_model_config.from_model_config_dict(override_model_configs) - assert app_model_config is not None, "app model config not found" model_config = app_model_config.to_dict() else: model_config["configs"] = override_model_configs @@ -817,7 +831,12 @@ class Conversation(Base): @property def first_message(self): - return db.session.query(Message).filter(Message.conversation_id == self.id).first() + return ( + db.session.query(Message) + .filter(Message.conversation_id == self.id) + .order_by(Message.created_at.asc()) + .first() + ) @property def app(self): @@ -894,11 +913,11 @@ class Message(Base): _inputs: Mapped[dict] = mapped_column("inputs", db.JSON) query: Mapped[str] = db.Column(db.Text, nullable=False) message = db.Column(db.JSON, nullable=False) - message_tokens = db.Column(db.Integer, nullable=False, server_default=db.text("0")) + message_tokens: Mapped[int] = db.Column(db.Integer, nullable=False, server_default=db.text("0")) message_unit_price = db.Column(db.Numeric(10, 4), nullable=False) message_price_unit = db.Column(db.Numeric(10, 7), nullable=False, server_default=db.text("0.001")) answer: Mapped[str] = db.Column(db.Text, nullable=False) - answer_tokens = db.Column(db.Integer, nullable=False, server_default=db.text("0")) + answer_tokens: Mapped[int] = db.Column(db.Integer, nullable=False, server_default=db.text("0")) answer_unit_price = db.Column(db.Numeric(10, 4), nullable=False) answer_price_unit = db.Column(db.Numeric(10, 7), nullable=False, server_default=db.text("0.001")) parent_message_id = db.Column(StringUUID, nullable=True) @@ -927,7 +946,7 @@ class Message(Base): if isinstance(value, dict) and value.get("dify_model_identity") == FILE_MODEL_IDENTITY: if value["transfer_method"] == FileTransferMethod.TOOL_FILE: value["tool_file_id"] = value["related_id"] - elif value["transfer_method"] == FileTransferMethod.LOCAL_FILE: + elif value["transfer_method"] in [FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL]: value["upload_file_id"] = value["related_id"] inputs[key] = file_factory.build_from_mapping(mapping=value, tenant_id=value["tenant_id"]) elif isinstance(value, list) and all( @@ -937,7 +956,7 @@ class Message(Base): for item in value: if item["transfer_method"] == FileTransferMethod.TOOL_FILE: item["tool_file_id"] = item["related_id"] - elif item["transfer_method"] == FileTransferMethod.LOCAL_FILE: + elif item["transfer_method"] in [FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL]: item["upload_file_id"] = item["related_id"] inputs[key].append(file_factory.build_from_mapping(mapping=item, tenant_id=item["tenant_id"])) return inputs diff --git a/api/models/workflow.py b/api/models/workflow.py index 2fff045543..7f01135af3 100644 --- a/api/models/workflow.py +++ b/api/models/workflow.py @@ -7,10 +7,16 @@ from typing import TYPE_CHECKING, Any, Optional, Union from uuid import uuid4 from flask_login import current_user +from sqlalchemy import orm +from core.file.constants import maybe_file_object +from core.file.models import File from core.variables import utils as variable_utils from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID -from factories.variable_factory import build_segment +from core.workflow.nodes.enums import NodeType +from factories.variable_factory import TypeMismatchError, build_segment_with_type + +from ._workflow_exc import NodeNotFoundError, WorkflowDataError if TYPE_CHECKING: from models.model import AppMode @@ -72,6 +78,10 @@ class WorkflowType(Enum): return cls.WORKFLOW if app_mode == AppMode.WORKFLOW else cls.CHAT +class _InvalidGraphDefinitionError(Exception): + pass + + class Workflow(Base): """ Workflow, for `Workflow App` and `Chat App workflow mode`. @@ -136,6 +146,8 @@ class Workflow(Base): "conversation_variables", db.Text, nullable=False, server_default="{}" ) + VERSION_DRAFT = "draft" + @classmethod def new( cls, @@ -179,8 +191,72 @@ class Workflow(Base): @property def graph_dict(self) -> Mapping[str, Any]: + # TODO(QuantumGhost): Consider caching `graph_dict` to avoid repeated JSON decoding. + # + # Using `functools.cached_property` could help, but some code in the codebase may + # modify the returned dict, which can cause issues elsewhere. + # + # For example, changing this property to a cached property led to errors like the + # following when single stepping an `Iteration` node: + # + # Root node id 1748401971780start not found in the graph + # + # There is currently no standard way to make a dict deeply immutable in Python, + # and tracking modifications to the returned dict is difficult. For now, we leave + # the code as-is to avoid these issues. + # + # Currently, the following functions / methods would mutate the returned dict: + # + # - `_get_graph_and_variable_pool_of_single_iteration`. + # - `_get_graph_and_variable_pool_of_single_loop`. return json.loads(self.graph) if self.graph else {} + def get_node_config_by_id(self, node_id: str) -> Mapping[str, Any]: + """Extract a node configuration from the workflow graph by node ID. + A node configuration is a dictionary containing the node's properties, including + the node's id, title, and its data as a dict. + """ + workflow_graph = self.graph_dict + + if not workflow_graph: + raise WorkflowDataError(f"workflow graph not found, workflow_id={self.id}") + + nodes = workflow_graph.get("nodes") + if not nodes: + raise WorkflowDataError("nodes not found in workflow graph") + + try: + node_config = next(filter(lambda node: node["id"] == node_id, nodes)) + except StopIteration: + raise NodeNotFoundError(node_id) + assert isinstance(node_config, dict) + return node_config + + @staticmethod + def get_node_type_from_node_config(node_config: Mapping[str, Any]) -> NodeType: + """Extract type of a node from the node configuration returned by `get_node_config_by_id`.""" + node_config_data = node_config.get("data", {}) + # Get node class + node_type = NodeType(node_config_data.get("type")) + return node_type + + @staticmethod + def get_enclosing_node_type_and_id(node_config: Mapping[str, Any]) -> tuple[NodeType, str] | None: + in_loop = node_config.get("isInLoop", False) + in_iteration = node_config.get("isInIteration", False) + if in_loop: + loop_id = node_config.get("loop_id") + if loop_id is None: + raise _InvalidGraphDefinitionError("invalid graph") + return NodeType.LOOP, loop_id + elif in_iteration: + iteration_id = node_config.get("iteration_id") + if iteration_id is None: + raise _InvalidGraphDefinitionError("invalid graph") + return NodeType.ITERATION, iteration_id + else: + return None + @property def features(self) -> str: """ @@ -376,6 +452,10 @@ class Workflow(Base): ensure_ascii=False, ) + @staticmethod + def version_from_datetime(d: datetime) -> str: + return str(d) + class WorkflowRun(Base): """ @@ -386,7 +466,7 @@ class WorkflowRun(Base): - id (uuid) Run ID - tenant_id (uuid) Workspace ID - app_id (uuid) App ID - - sequence_number (int) Auto-increment sequence number, incremented within the App, starting from 1 + - workflow_id (uuid) Workflow ID - type (string) Workflow type - triggered_from (string) Trigger source @@ -419,13 +499,12 @@ class WorkflowRun(Base): __table_args__ = ( db.PrimaryKeyConstraint("id", name="workflow_run_pkey"), db.Index("workflow_run_triggerd_from_idx", "tenant_id", "app_id", "triggered_from"), - db.Index("workflow_run_tenant_app_sequence_idx", "tenant_id", "app_id", "sequence_number"), ) id: Mapped[str] = mapped_column(StringUUID, server_default=db.text("uuid_generate_v4()")) tenant_id: Mapped[str] = mapped_column(StringUUID) app_id: Mapped[str] = mapped_column(StringUUID) - sequence_number: Mapped[int] = mapped_column() + workflow_id: Mapped[str] = mapped_column(StringUUID) type: Mapped[str] = mapped_column(db.String(255)) triggered_from: Mapped[str] = mapped_column(db.String(255)) @@ -485,7 +564,6 @@ class WorkflowRun(Base): "id": self.id, "tenant_id": self.tenant_id, "app_id": self.app_id, - "sequence_number": self.sequence_number, "workflow_id": self.workflow_id, "type": self.type, "triggered_from": self.triggered_from, @@ -511,7 +589,6 @@ class WorkflowRun(Base): id=data.get("id"), tenant_id=data.get("tenant_id"), app_id=data.get("app_id"), - sequence_number=data.get("sequence_number"), workflow_id=data.get("workflow_id"), type=data.get("type"), triggered_from=data.get("triggered_from"), @@ -838,8 +915,18 @@ def _naive_utc_datetime(): class WorkflowDraftVariable(Base): + """`WorkflowDraftVariable` record variables and outputs generated during + debugging worfklow or chatflow. + + IMPORTANT: This model maintains multiple invariant rules that must be preserved. + Do not instantiate this class directly with the constructor. + + Instead, use the factory methods (`new_conversation_variable`, `new_sys_variable`, + `new_node_variable`) defined below to ensure all invariants are properly maintained. + """ + @staticmethod - def unique_columns() -> list[str]: + def unique_app_id_node_id_name() -> list[str]: return [ "app_id", "node_id", @@ -847,7 +934,9 @@ class WorkflowDraftVariable(Base): ] __tablename__ = "workflow_draft_variables" - __table_args__ = (UniqueConstraint(*unique_columns()),) + __table_args__ = (UniqueConstraint(*unique_app_id_node_id_name()),) + # Required for instance variable annotation. + __allow_unmapped__ = True # id is the unique identifier of a draft variable. id: Mapped[str] = mapped_column(StringUUID, primary_key=True, server_default=db.text("uuid_generate_v4()")) @@ -928,6 +1017,36 @@ class WorkflowDraftVariable(Base): default=None, ) + # Cache for deserialized value + # + # NOTE(QuantumGhost): This field serves two purposes: + # + # 1. Caches deserialized values to reduce repeated parsing costs + # 2. Allows modification of the deserialized value after retrieval, + # particularly important for `File`` variables which require database + # lookups to obtain storage_key and other metadata + # + # Use double underscore prefix for better encapsulation, + # making this attribute harder to access from outside the class. + __value: Segment | None + + def __init__(self, *args, **kwargs): + """ + The constructor of `WorkflowDraftVariable` is not intended for + direct use outside this file. Its solo purpose is setup private state + used by the model instance. + + Please use the factory methods + (`new_conversation_variable`, `new_sys_variable`, `new_node_variable`) + defined below to create instances of this class. + """ + super().__init__(*args, **kwargs) + self.__value = None + + @orm.reconstructor + def _init_on_load(self): + self.__value = None + def get_selector(self) -> list[str]: selector = json.loads(self.selector) if not isinstance(selector, list): @@ -942,15 +1061,92 @@ class WorkflowDraftVariable(Base): def _set_selector(self, value: list[str]): self.selector = json.dumps(value) - def get_value(self) -> Segment | None: - return build_segment(json.loads(self.value)) + def _loads_value(self) -> Segment: + value = json.loads(self.value) + return self.build_segment_with_type(self.value_type, value) + + @staticmethod + def rebuild_file_types(value: Any) -> Any: + # NOTE(QuantumGhost): Temporary workaround for structured data handling. + # By this point, `output` has been converted to dict by + # `WorkflowEntry.handle_special_values`, so we need to + # reconstruct File objects from their serialized form + # to maintain proper variable saving behavior. + # + # Ideally, we should work with structured data objects directly + # rather than their serialized forms. + # However, multiple components in the codebase depend on + # `WorkflowEntry.handle_special_values`, making a comprehensive migration challenging. + if isinstance(value, dict): + if not maybe_file_object(value): + return value + return File.model_validate(value) + elif isinstance(value, list) and value: + first = value[0] + if not maybe_file_object(first): + return value + return [File.model_validate(i) for i in value] + else: + return value + + @classmethod + def build_segment_with_type(cls, segment_type: SegmentType, value: Any) -> Segment: + # Extends `variable_factory.build_segment_with_type` functionality by + # reconstructing `FileSegment`` or `ArrayFileSegment`` objects from + # their serialized dictionary or list representations, respectively. + if segment_type == SegmentType.FILE: + if isinstance(value, File): + return build_segment_with_type(segment_type, value) + elif isinstance(value, dict): + file = cls.rebuild_file_types(value) + return build_segment_with_type(segment_type, file) + else: + raise TypeMismatchError(f"expected dict or File for FileSegment, got {type(value)}") + if segment_type == SegmentType.ARRAY_FILE: + if not isinstance(value, list): + raise TypeMismatchError(f"expected list for ArrayFileSegment, got {type(value)}") + file_list = cls.rebuild_file_types(value) + return build_segment_with_type(segment_type=segment_type, value=file_list) + + return build_segment_with_type(segment_type=segment_type, value=value) + + def get_value(self) -> Segment: + """Decode the serialized value into its corresponding `Segment` object. + + This method caches the result, so repeated calls will return the same + object instance without re-parsing the serialized data. + + If you need to modify the returned `Segment`, use `value.model_copy()` + to create a copy first to avoid affecting the cached instance. + + For more information about the caching mechanism, see the documentation + of the `__value` field. + + Returns: + Segment: The deserialized value as a Segment object. + """ + + if self.__value is not None: + return self.__value + value = self._loads_value() + self.__value = value + return value def set_name(self, name: str): self.name = name self._set_selector([self.node_id, name]) def set_value(self, value: Segment): - self.value = json.dumps(value.value) + """Updates the `value` and corresponding `value_type` fields in the database model. + + This method also stores the provided Segment object in the deserialized cache + without creating a copy, allowing for efficient value access. + + Args: + value: The Segment object to store as the variable's value. + """ + self.__value = value + self.value = json.dumps(value, cls=variable_utils.SegmentJSONEncoder) self.value_type = value.value_type def get_node_id(self) -> str | None: @@ -976,6 +1172,7 @@ class WorkflowDraftVariable(Base): node_id: str, name: str, value: Segment, + node_execution_id: str | None, description: str = "", ) -> "WorkflowDraftVariable": variable = WorkflowDraftVariable() @@ -987,6 +1184,7 @@ class WorkflowDraftVariable(Base): variable.name = name variable.set_value(value) variable._set_selector(list(variable_utils.to_selector(node_id, name))) + variable.node_execution_id = node_execution_id return variable @classmethod @@ -996,13 +1194,17 @@ class WorkflowDraftVariable(Base): app_id: str, name: str, value: Segment, + description: str = "", ) -> "WorkflowDraftVariable": variable = cls._new( app_id=app_id, node_id=CONVERSATION_VARIABLE_NODE_ID, name=name, value=value, + description=description, + node_execution_id=None, ) + variable.editable = True return variable @classmethod @@ -1012,9 +1214,16 @@ class WorkflowDraftVariable(Base): app_id: str, name: str, value: Segment, + node_execution_id: str, editable: bool = False, ) -> "WorkflowDraftVariable": - variable = cls._new(app_id=app_id, node_id=SYSTEM_VARIABLE_NODE_ID, name=name, value=value) + variable = cls._new( + app_id=app_id, + node_id=SYSTEM_VARIABLE_NODE_ID, + name=name, + node_execution_id=node_execution_id, + value=value, + ) variable.editable = editable return variable @@ -1026,11 +1235,19 @@ class WorkflowDraftVariable(Base): node_id: str, name: str, value: Segment, + node_execution_id: str, visible: bool = True, + editable: bool = True, ) -> "WorkflowDraftVariable": - variable = cls._new(app_id=app_id, node_id=node_id, name=name, value=value) + variable = cls._new( + app_id=app_id, + node_id=node_id, + name=name, + node_execution_id=node_execution_id, + value=value, + ) variable.visible = visible - variable.editable = True + variable.editable = editable return variable @property diff --git a/api/mypy.ini b/api/mypy.ini index 12fe529b08..6836b2602b 100644 --- a/api/mypy.ini +++ b/api/mypy.ini @@ -18,4 +18,3 @@ ignore_missing_imports=True [mypy-flask_restful.inputs] ignore_missing_imports=True - diff --git a/api/pyproject.toml b/api/pyproject.toml index 9631586ed4..d33806d0ae 100644 --- a/api/pyproject.toml +++ b/api/pyproject.toml @@ -1,9 +1,10 @@ [project] name = "dify-api" -dynamic = ["version"] +version = "1.5.1" requires-python = ">=3.11,<3.13" dependencies = [ + "arize-phoenix-otel~=0.9.2", "authlib==1.3.1", "azure-identity==1.16.1", "beautifulsoup4==4.12.2", @@ -81,6 +82,7 @@ dependencies = [ "weave~=0.51.0", "yarl~=1.18.3", "webvtt-py~=0.5.1", + "sendgrid~=6.12.3", ] # Before adding new dependency, consider place it in # alphabet order (a-z) and suitable group. @@ -148,11 +150,13 @@ dev = [ "types-ujson>=5.10.0", "boto3-stubs>=1.38.20", "types-jmespath>=1.0.2.20240106", + "hypothesis>=6.131.15", "types_pyOpenSSL>=24.1.0", "types_cffi>=1.17.0", "types_setuptools>=80.9.0", "pandas-stubs~=2.2.3", "scipy-stubs>=1.15.3.0", + "types-python-http-client>=3.3.7.20240910", ] ############################################################ @@ -195,11 +199,12 @@ vdb = [ "pymochow==1.3.1", "pyobvector~=0.1.6", "qdrant-client==1.9.0", - "tablestore==6.1.0", + "tablestore==6.2.0", "tcvectordb~=1.6.4", "tidb-vector==0.0.9", "upstash-vector==0.6.0", "volcengine-compat~=1.0.0", "weaviate-client~=3.24.0", "xinference-client~=1.2.2", + "mo-vector~=0.1.13", ] diff --git a/api/services/account_service.py b/api/services/account_service.py index 14d238467d..3fdbda48a6 100644 --- a/api/services/account_service.py +++ b/api/services/account_service.py @@ -889,7 +889,7 @@ class RegisterService: TenantService.create_owner_tenant_if_not_exist(account=account, is_setup=True) - dify_setup = DifySetup(version=dify_config.CURRENT_VERSION) + dify_setup = DifySetup(version=dify_config.project.version) db.session.add(dify_setup) db.session.commit() except Exception as e: diff --git a/api/services/app_dsl_service.py b/api/services/app_dsl_service.py index 1b026acfd6..20257fa345 100644 --- a/api/services/app_dsl_service.py +++ b/api/services/app_dsl_service.py @@ -32,6 +32,7 @@ from models import Account, App, AppMode from models.model import AppModelConfig from models.workflow import Workflow from services.plugin.dependencies_analysis import DependenciesAnalysisService +from services.workflow_draft_variable_service import WorkflowDraftVariableService from services.workflow_service import WorkflowService logger = logging.getLogger(__name__) @@ -292,6 +293,8 @@ class AppDslService: dependencies=check_dependencies_pending_data, ) + draft_var_srv = WorkflowDraftVariableService(session=self._session) + draft_var_srv.delete_workflow_variables(app_id=app.id) return Import( id=import_id, status=status, diff --git a/api/services/audio_service.py b/api/services/audio_service.py index a259f5a4c4..e8923eb51b 100644 --- a/api/services/audio_service.py +++ b/api/services/audio_service.py @@ -1,13 +1,17 @@ import io import logging import uuid +from collections.abc import Generator from typing import Optional +from flask import Response, stream_with_context from werkzeug.datastructures import FileStorage from constants import AUDIO_EXTENSIONS from core.model_manager import ModelManager from core.model_runtime.entities.model_entities import ModelType +from extensions.ext_database import db +from models.enums import MessageStatus from models.model import App, AppMode, AppModelConfig, Message from services.errors.audio import ( AudioTooLargeServiceError, @@ -16,6 +20,7 @@ from services.errors.audio import ( ProviderNotSupportTextToSpeechServiceError, UnsupportedAudioTypeServiceError, ) +from services.workflow_service import WorkflowService FILE_SIZE = 30 FILE_SIZE_LIMIT = FILE_SIZE * 1024 * 1024 @@ -74,35 +79,36 @@ class AudioService: voice: Optional[str] = None, end_user: Optional[str] = None, message_id: Optional[str] = None, + is_draft: bool = False, ): - from collections.abc import Generator - - from flask import Response, stream_with_context - from app import app - from extensions.ext_database import db - def invoke_tts(text_content: str, app_model: App, voice: Optional[str] = None): + def invoke_tts(text_content: str, app_model: App, voice: Optional[str] = None, is_draft: bool = False): with app.app_context(): - if app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}: - workflow = app_model.workflow - if workflow is None: - raise ValueError("TTS is not enabled") - - features_dict = workflow.features_dict - if "text_to_speech" not in features_dict or not features_dict["text_to_speech"].get("enabled"): - raise ValueError("TTS is not enabled") - - voice = features_dict["text_to_speech"].get("voice") if voice is None else voice - else: - if app_model.app_model_config is None: - raise ValueError("AppModelConfig not found") - text_to_speech_dict = app_model.app_model_config.text_to_speech_dict - - if not text_to_speech_dict.get("enabled"): - raise ValueError("TTS is not enabled") - - voice = text_to_speech_dict.get("voice") if voice is None else voice + if voice is None: + if app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}: + if is_draft: + workflow = WorkflowService().get_draft_workflow(app_model=app_model) + else: + workflow = app_model.workflow + if ( + workflow is None + or "text_to_speech" not in workflow.features_dict + or not workflow.features_dict["text_to_speech"].get("enabled") + ): + raise ValueError("TTS is not enabled") + + voice = workflow.features_dict["text_to_speech"].get("voice") + else: + if not is_draft: + if app_model.app_model_config is None: + raise ValueError("AppModelConfig not found") + text_to_speech_dict = app_model.app_model_config.text_to_speech_dict + + if not text_to_speech_dict.get("enabled"): + raise ValueError("TTS is not enabled") + + voice = text_to_speech_dict.get("voice") model_manager = ModelManager() model_instance = model_manager.get_default_model_instance( @@ -132,18 +138,18 @@ class AudioService: message = db.session.query(Message).filter(Message.id == message_id).first() if message is None: return None - if message.answer == "" and message.status == "normal": + if message.answer == "" and message.status == MessageStatus.NORMAL: return None else: - response = invoke_tts(message.answer, app_model=app_model, voice=voice) + response = invoke_tts(text_content=message.answer, app_model=app_model, voice=voice, is_draft=is_draft) if isinstance(response, Generator): return Response(stream_with_context(response), content_type="audio/mpeg") return response else: if text is None: raise ValueError("Text is required") - response = invoke_tts(text, app_model, voice) + response = invoke_tts(text_content=text, app_model=app_model, voice=voice, is_draft=is_draft) if isinstance(response, Generator): return Response(stream_with_context(response), content_type="audio/mpeg") return response diff --git a/api/services/dataset_service.py b/api/services/dataset_service.py index e98b47921f..e42b5ace75 100644 --- a/api/services/dataset_service.py +++ b/api/services/dataset_service.py @@ -59,6 +59,7 @@ from services.external_knowledge_service import ExternalDatasetService from services.feature_service import FeatureModel, FeatureService from services.tag_service import TagService from services.vector_service import VectorService +from tasks.add_document_to_index_task import add_document_to_index_task from tasks.batch_clean_document_task import batch_clean_document_task from tasks.clean_notion_document_task import clean_notion_document_task from tasks.deal_dataset_vector_index_task import deal_dataset_vector_index_task @@ -70,6 +71,7 @@ from tasks.document_indexing_update_task import document_indexing_update_task from tasks.duplicate_document_indexing_task import duplicate_document_indexing_task from tasks.enable_segments_to_index_task import enable_segments_to_index_task from tasks.recover_document_indexing_task import recover_document_indexing_task +from tasks.remove_document_from_index_task import remove_document_from_index_task from tasks.retry_document_indexing_task import retry_document_indexing_task from tasks.sync_website_document_indexing_task import sync_website_document_indexing_task @@ -276,176 +278,351 @@ class DatasetService: except ProviderTokenNotInitError as ex: raise ValueError(ex.description) + @staticmethod + def check_reranking_model_setting(tenant_id: str, reranking_model_provider: str, reranking_model: str): + try: + model_manager = ModelManager() + model_manager.get_model_instance( + tenant_id=tenant_id, + provider=reranking_model_provider, + model_type=ModelType.RERANK, + model=reranking_model, + ) + except LLMBadRequestError: + raise ValueError( + "No Rerank Model available. Please configure a valid provider in the Settings -> Model Provider." + ) + except ProviderTokenNotInitError as ex: + raise ValueError(ex.description) + @staticmethod def update_dataset(dataset_id, data, user): + """ + Update dataset configuration and settings. + + Args: + dataset_id: The unique identifier of the dataset to update + data: Dictionary containing the update data + user: The user performing the update operation + + Returns: + Dataset: The updated dataset object + + Raises: + ValueError: If dataset not found or validation fails + NoPermissionError: If user lacks permission to update the dataset + """ + # Retrieve and validate dataset existence dataset = DatasetService.get_dataset(dataset_id) if not dataset: raise ValueError("Dataset not found") + # Verify user has permission to update this dataset DatasetService.check_dataset_permission(dataset, user) + + # Handle external dataset updates if dataset.provider == "external": - external_retrieval_model = data.get("external_retrieval_model", None) - if external_retrieval_model: - dataset.retrieval_model = external_retrieval_model - dataset.name = data.get("name", dataset.name) - dataset.description = data.get("description", "") - permission = data.get("permission") - if permission: - dataset.permission = permission - external_knowledge_id = data.get("external_knowledge_id", None) - db.session.add(dataset) - if not external_knowledge_id: - raise ValueError("External knowledge id is required.") - external_knowledge_api_id = data.get("external_knowledge_api_id", None) - if not external_knowledge_api_id: - raise ValueError("External knowledge api id is required.") - - with Session(db.engine) as session: - external_knowledge_binding = ( - session.query(ExternalKnowledgeBindings).filter_by(dataset_id=dataset_id).first() - ) + return DatasetService._update_external_dataset(dataset, data, user) + else: + return DatasetService._update_internal_dataset(dataset, data, user) - if not external_knowledge_binding: - raise ValueError("External knowledge binding not found.") + @staticmethod + def _update_external_dataset(dataset, data, user): + """ + Update external dataset configuration. + + Args: + dataset: The dataset object to update + data: Update data dictionary + user: User performing the update + + Returns: + Dataset: Updated dataset object + """ + # Update retrieval model if provided + external_retrieval_model = data.get("external_retrieval_model", None) + if external_retrieval_model: + dataset.retrieval_model = external_retrieval_model + + # Update basic dataset properties + dataset.name = data.get("name", dataset.name) + dataset.description = data.get("description", dataset.description) + + # Update permission if provided + permission = data.get("permission") + if permission: + dataset.permission = permission + + # Validate and update external knowledge configuration + external_knowledge_id = data.get("external_knowledge_id", None) + external_knowledge_api_id = data.get("external_knowledge_api_id", None) + + if not external_knowledge_id: + raise ValueError("External knowledge id is required.") + if not external_knowledge_api_id: + raise ValueError("External knowledge api id is required.") + # Update metadata fields + dataset.updated_by = user.id if user else None + dataset.updated_at = datetime.datetime.utcnow() + db.session.add(dataset) - if ( - external_knowledge_binding.external_knowledge_id != external_knowledge_id - or external_knowledge_binding.external_knowledge_api_id != external_knowledge_api_id - ): - external_knowledge_binding.external_knowledge_id = external_knowledge_id - external_knowledge_binding.external_knowledge_api_id = external_knowledge_api_id - db.session.add(external_knowledge_binding) - db.session.commit() - else: - data.pop("partial_member_list", None) - data.pop("external_knowledge_api_id", None) - data.pop("external_knowledge_id", None) - data.pop("external_retrieval_model", None) - filtered_data = {k: v for k, v in data.items() if v is not None or k == "description"} - action = None - if dataset.indexing_technique != data["indexing_technique"]: - # if update indexing_technique - if data["indexing_technique"] == "economy": - action = "remove" - filtered_data["embedding_model"] = None - filtered_data["embedding_model_provider"] = None - filtered_data["collection_binding_id"] = None - elif data["indexing_technique"] == "high_quality": - action = "add" - # get embedding model setting - try: - model_manager = ModelManager() - embedding_model = model_manager.get_model_instance( - tenant_id=current_user.current_tenant_id, - provider=data["embedding_model_provider"], - model_type=ModelType.TEXT_EMBEDDING, - model=data["embedding_model"], - ) - filtered_data["embedding_model"] = embedding_model.model - filtered_data["embedding_model_provider"] = embedding_model.provider - dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding( - embedding_model.provider, embedding_model.model - ) - filtered_data["collection_binding_id"] = dataset_collection_binding.id - except LLMBadRequestError: - raise ValueError( - "No Embedding Model available. Please configure a valid provider " - "in the Settings -> Model Provider." - ) - except ProviderTokenNotInitError as ex: - raise ValueError(ex.description) - else: - # add default plugin id to both setting sets, to make sure the plugin model provider is consistent - # Skip embedding model checks if not provided in the update request - if ( - "embedding_model_provider" not in data - or "embedding_model" not in data - or not data.get("embedding_model_provider") - or not data.get("embedding_model") - ): - # If the dataset already has embedding model settings, use those - if dataset.embedding_model_provider and dataset.embedding_model: - # Keep existing values - filtered_data["embedding_model_provider"] = dataset.embedding_model_provider - filtered_data["embedding_model"] = dataset.embedding_model - # If collection_binding_id exists, keep it too - if dataset.collection_binding_id: - filtered_data["collection_binding_id"] = dataset.collection_binding_id - # Otherwise, don't try to update embedding model settings at all - # Remove these fields from filtered_data if they exist but are None/empty - if "embedding_model_provider" in filtered_data and not filtered_data["embedding_model_provider"]: - del filtered_data["embedding_model_provider"] - if "embedding_model" in filtered_data and not filtered_data["embedding_model"]: - del filtered_data["embedding_model"] - else: - skip_embedding_update = False - try: - # Handle existing model provider - plugin_model_provider = dataset.embedding_model_provider - plugin_model_provider_str = None - if plugin_model_provider: - plugin_model_provider_str = str(ModelProviderID(plugin_model_provider)) - - # Handle new model provider from request - new_plugin_model_provider = data["embedding_model_provider"] - new_plugin_model_provider_str = None - if new_plugin_model_provider: - new_plugin_model_provider_str = str(ModelProviderID(new_plugin_model_provider)) - - # Only update embedding model if both values are provided and different from current - if ( - plugin_model_provider_str != new_plugin_model_provider_str - or data["embedding_model"] != dataset.embedding_model - ): - action = "update" - model_manager = ModelManager() - try: - embedding_model = model_manager.get_model_instance( - tenant_id=current_user.current_tenant_id, - provider=data["embedding_model_provider"], - model_type=ModelType.TEXT_EMBEDDING, - model=data["embedding_model"], - ) - except ProviderTokenNotInitError: - # If we can't get the embedding model, skip updating it - # and keep the existing settings if available - if dataset.embedding_model_provider and dataset.embedding_model: - filtered_data["embedding_model_provider"] = dataset.embedding_model_provider - filtered_data["embedding_model"] = dataset.embedding_model - if dataset.collection_binding_id: - filtered_data["collection_binding_id"] = dataset.collection_binding_id - # Skip the rest of the embedding model update - skip_embedding_update = True - if not skip_embedding_update: - filtered_data["embedding_model"] = embedding_model.model - filtered_data["embedding_model_provider"] = embedding_model.provider - dataset_collection_binding = ( - DatasetCollectionBindingService.get_dataset_collection_binding( - embedding_model.provider, embedding_model.model - ) - ) - filtered_data["collection_binding_id"] = dataset_collection_binding.id - except LLMBadRequestError: - raise ValueError( - "No Embedding Model available. Please configure a valid provider " - "in the Settings -> Model Provider." - ) - except ProviderTokenNotInitError as ex: - raise ValueError(ex.description) + # Update external knowledge binding + DatasetService._update_external_knowledge_binding(dataset.id, external_knowledge_id, external_knowledge_api_id) + + # Commit changes to database + db.session.commit() + + return dataset - filtered_data["updated_by"] = user.id - filtered_data["updated_at"] = datetime.datetime.now() + @staticmethod + def _update_external_knowledge_binding(dataset_id, external_knowledge_id, external_knowledge_api_id): + """ + Update external knowledge binding configuration. + + Args: + dataset_id: Dataset identifier + external_knowledge_id: External knowledge identifier + external_knowledge_api_id: External knowledge API identifier + """ + with Session(db.engine) as session: + external_knowledge_binding = ( + session.query(ExternalKnowledgeBindings).filter_by(dataset_id=dataset_id).first() + ) - # update Retrieval model - filtered_data["retrieval_model"] = data["retrieval_model"] + if not external_knowledge_binding: + raise ValueError("External knowledge binding not found.") - db.session.query(Dataset).filter_by(id=dataset_id).update(filtered_data) + # Update binding if values have changed + if ( + external_knowledge_binding.external_knowledge_id != external_knowledge_id + or external_knowledge_binding.external_knowledge_api_id != external_knowledge_api_id + ): + external_knowledge_binding.external_knowledge_id = external_knowledge_id + external_knowledge_binding.external_knowledge_api_id = external_knowledge_api_id + db.session.add(external_knowledge_binding) + + @staticmethod + def _update_internal_dataset(dataset, data, user): + """ + Update internal dataset configuration. + + Args: + dataset: The dataset object to update + data: Update data dictionary + user: User performing the update + + Returns: + Dataset: Updated dataset object + """ + # Remove external-specific fields from update data + data.pop("partial_member_list", None) + data.pop("external_knowledge_api_id", None) + data.pop("external_knowledge_id", None) + data.pop("external_retrieval_model", None) + + # Filter out None values except for description field + filtered_data = {k: v for k, v in data.items() if v is not None or k == "description"} + + # Handle indexing technique changes and embedding model updates + action = DatasetService._handle_indexing_technique_change(dataset, data, filtered_data) + + # Add metadata fields + filtered_data["updated_by"] = user.id + filtered_data["updated_at"] = datetime.datetime.now(datetime.UTC).replace(tzinfo=None) + # update Retrieval model + filtered_data["retrieval_model"] = data["retrieval_model"] + + # Update dataset in database + db.session.query(Dataset).filter_by(id=dataset.id).update(filtered_data) + db.session.commit() + + # Trigger vector index task if indexing technique changed + if action: + deal_dataset_vector_index_task.delay(dataset.id, action) - db.session.commit() - if action: - deal_dataset_vector_index_task.delay(dataset_id, action) return dataset + @staticmethod + def _handle_indexing_technique_change(dataset, data, filtered_data): + """ + Handle changes in indexing technique and configure embedding models accordingly. + + Args: + dataset: Current dataset object + data: Update data dictionary + filtered_data: Filtered update data + + Returns: + str: Action to perform ('add', 'remove', 'update', or None) + """ + if dataset.indexing_technique != data["indexing_technique"]: + if data["indexing_technique"] == "economy": + # Remove embedding model configuration for economy mode + filtered_data["embedding_model"] = None + filtered_data["embedding_model_provider"] = None + filtered_data["collection_binding_id"] = None + return "remove" + elif data["indexing_technique"] == "high_quality": + # Configure embedding model for high quality mode + DatasetService._configure_embedding_model_for_high_quality(data, filtered_data) + return "add" + else: + # Handle embedding model updates when indexing technique remains the same + return DatasetService._handle_embedding_model_update_when_technique_unchanged(dataset, data, filtered_data) + return None + + @staticmethod + def _configure_embedding_model_for_high_quality(data, filtered_data): + """ + Configure embedding model settings for high quality indexing. + + Args: + data: Update data dictionary + filtered_data: Filtered update data to modify + """ + try: + model_manager = ModelManager() + embedding_model = model_manager.get_model_instance( + tenant_id=current_user.current_tenant_id, + provider=data["embedding_model_provider"], + model_type=ModelType.TEXT_EMBEDDING, + model=data["embedding_model"], + ) + filtered_data["embedding_model"] = embedding_model.model + filtered_data["embedding_model_provider"] = embedding_model.provider + dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding( + embedding_model.provider, embedding_model.model + ) + filtered_data["collection_binding_id"] = dataset_collection_binding.id + except LLMBadRequestError: + raise ValueError( + "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider." + ) + except ProviderTokenNotInitError as ex: + raise ValueError(ex.description) + + @staticmethod + def _handle_embedding_model_update_when_technique_unchanged(dataset, data, filtered_data): + """ + Handle embedding model updates when indexing technique remains the same. + + Args: + dataset: Current dataset object + data: Update data dictionary + filtered_data: Filtered update data to modify + + Returns: + str: Action to perform ('update' or None) + """ + # Skip embedding model checks if not provided in the update request + if ( + "embedding_model_provider" not in data + or "embedding_model" not in data + or not data.get("embedding_model_provider") + or not data.get("embedding_model") + ): + DatasetService._preserve_existing_embedding_settings(dataset, filtered_data) + return None + else: + return DatasetService._update_embedding_model_settings(dataset, data, filtered_data) + + @staticmethod + def _preserve_existing_embedding_settings(dataset, filtered_data): + """ + Preserve existing embedding model settings when not provided in update. + + Args: + dataset: Current dataset object + filtered_data: Filtered update data to modify + """ + # If the dataset already has embedding model settings, use those + if dataset.embedding_model_provider and dataset.embedding_model: + filtered_data["embedding_model_provider"] = dataset.embedding_model_provider + filtered_data["embedding_model"] = dataset.embedding_model + # If collection_binding_id exists, keep it too + if dataset.collection_binding_id: + filtered_data["collection_binding_id"] = dataset.collection_binding_id + # Otherwise, don't try to update embedding model settings at all + # Remove these fields from filtered_data if they exist but are None/empty + if "embedding_model_provider" in filtered_data and not filtered_data["embedding_model_provider"]: + del filtered_data["embedding_model_provider"] + if "embedding_model" in filtered_data and not filtered_data["embedding_model"]: + del filtered_data["embedding_model"] + + @staticmethod + def _update_embedding_model_settings(dataset, data, filtered_data): + """ + Update embedding model settings with new values. + + Args: + dataset: Current dataset object + data: Update data dictionary + filtered_data: Filtered update data to modify + + Returns: + str: Action to perform ('update' or None) + """ + try: + # Compare current and new model provider settings + current_provider_str = ( + str(ModelProviderID(dataset.embedding_model_provider)) if dataset.embedding_model_provider else None + ) + new_provider_str = ( + str(ModelProviderID(data["embedding_model_provider"])) if data["embedding_model_provider"] else None + ) + + # Only update if values are different + if current_provider_str != new_provider_str or data["embedding_model"] != dataset.embedding_model: + DatasetService._apply_new_embedding_settings(dataset, data, filtered_data) + return "update" + except LLMBadRequestError: + raise ValueError( + "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider." + ) + except ProviderTokenNotInitError as ex: + raise ValueError(ex.description) + return None + + @staticmethod + def _apply_new_embedding_settings(dataset, data, filtered_data): + """ + Apply new embedding model settings to the dataset. + + Args: + dataset: Current dataset object + data: Update data dictionary + filtered_data: Filtered update data to modify + """ + model_manager = ModelManager() + try: + embedding_model = model_manager.get_model_instance( + tenant_id=current_user.current_tenant_id, + provider=data["embedding_model_provider"], + model_type=ModelType.TEXT_EMBEDDING, + model=data["embedding_model"], + ) + except ProviderTokenNotInitError: + # If we can't get the embedding model, preserve existing settings + logging.warning( + f"Failed to initialize embedding model {data['embedding_model_provider']}/{data['embedding_model']}, " + f"preserving existing settings" + ) + if dataset.embedding_model_provider and dataset.embedding_model: + filtered_data["embedding_model_provider"] = dataset.embedding_model_provider + filtered_data["embedding_model"] = dataset.embedding_model + if dataset.collection_binding_id: + filtered_data["collection_binding_id"] = dataset.collection_binding_id + # Skip the rest of the embedding model update + return + + # Apply new embedding model settings + filtered_data["embedding_model"] = embedding_model.model + filtered_data["embedding_model_provider"] = embedding_model.provider + dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding( + embedding_model.provider, embedding_model.model + ) + filtered_data["collection_binding_id"] = dataset_collection_binding.id + @staticmethod def delete_dataset(dataset_id, user): dataset = DatasetService.get_dataset(dataset_id) @@ -976,12 +1153,17 @@ class DocumentService: process_rule = knowledge_config.process_rule if process_rule: if process_rule.mode in ("custom", "hierarchical"): - dataset_process_rule = DatasetProcessRule( - dataset_id=dataset.id, - mode=process_rule.mode, - rules=process_rule.rules.model_dump_json() if process_rule.rules else None, - created_by=account.id, - ) + if process_rule.rules: + dataset_process_rule = DatasetProcessRule( + dataset_id=dataset.id, + mode=process_rule.mode, + rules=process_rule.rules.model_dump_json() if process_rule.rules else None, + created_by=account.id, + ) + else: + dataset_process_rule = dataset.latest_process_rule + if not dataset_process_rule: + raise ValueError("No process rule found.") elif process_rule.mode == "automatic": dataset_process_rule = DatasetProcessRule( dataset_id=dataset.id, @@ -1402,16 +1584,16 @@ class DocumentService: knowledge_config.embedding_model, # type: ignore ) dataset_collection_binding_id = dataset_collection_binding.id - if knowledge_config.retrieval_model: - retrieval_model = knowledge_config.retrieval_model - else: - retrieval_model = RetrievalModel( - search_method=RetrievalMethod.SEMANTIC_SEARCH.value, - reranking_enable=False, - reranking_model=RerankingModel(reranking_provider_name="", reranking_model_name=""), - top_k=2, - score_threshold_enabled=False, - ) + if knowledge_config.retrieval_model: + retrieval_model = knowledge_config.retrieval_model + else: + retrieval_model = RetrievalModel( + search_method=RetrievalMethod.SEMANTIC_SEARCH.value, + reranking_enable=False, + reranking_model=RerankingModel(reranking_provider_name="", reranking_model_name=""), + top_k=2, + score_threshold_enabled=False, + ) # save dataset dataset = Dataset( tenant_id=tenant_id, @@ -1603,6 +1785,191 @@ class DocumentService: if not isinstance(args["process_rule"]["rules"]["segmentation"]["max_tokens"], int): raise ValueError("Process rule segmentation max_tokens is invalid") + @staticmethod + def batch_update_document_status(dataset: Dataset, document_ids: list[str], action: str, user): + """ + Batch update document status. + + Args: + dataset (Dataset): The dataset object + document_ids (list[str]): List of document IDs to update + action (str): Action to perform (enable, disable, archive, un_archive) + user: Current user performing the action + + Raises: + DocumentIndexingError: If document is being indexed or not in correct state + ValueError: If action is invalid + """ + if not document_ids: + return + + # Early validation of action parameter + valid_actions = ["enable", "disable", "archive", "un_archive"] + if action not in valid_actions: + raise ValueError(f"Invalid action: {action}. Must be one of {valid_actions}") + + documents_to_update = [] + + # First pass: validate all documents and prepare updates + for document_id in document_ids: + document = DocumentService.get_document(dataset.id, document_id) + if not document: + continue + + # Check if document is being indexed + indexing_cache_key = f"document_{document.id}_indexing" + cache_result = redis_client.get(indexing_cache_key) + if cache_result is not None: + raise DocumentIndexingError(f"Document:{document.name} is being indexed, please try again later") + + # Prepare update based on action + update_info = DocumentService._prepare_document_status_update(document, action, user) + if update_info: + documents_to_update.append(update_info) + + # Second pass: apply all updates in a single transaction + if documents_to_update: + try: + for update_info in documents_to_update: + document = update_info["document"] + updates = update_info["updates"] + + # Apply updates to the document + for field, value in updates.items(): + setattr(document, field, value) + + db.session.add(document) + + # Batch commit all changes + db.session.commit() + except Exception as e: + # Rollback on any error + db.session.rollback() + raise e + # Execute async tasks and set Redis cache after successful commit + # propagation_error is used to capture any errors for submitting async task execution + propagation_error = None + for update_info in documents_to_update: + try: + # Execute async tasks after successful commit + if update_info["async_task"]: + task_info = update_info["async_task"] + task_func = task_info["function"] + task_args = task_info["args"] + task_func.delay(*task_args) + except Exception as e: + # Log the error but do not rollback the transaction + logging.exception(f"Error executing async task for document {update_info['document'].id}") + # don't raise the error immediately, but capture it for later + propagation_error = e + try: + # Set Redis cache if needed after successful commit + if update_info["set_cache"]: + document = update_info["document"] + indexing_cache_key = f"document_{document.id}_indexing" + redis_client.setex(indexing_cache_key, 600, 1) + except Exception as e: + # Log the error but do not rollback the transaction + logging.exception(f"Error setting cache for document {update_info['document'].id}") + # Raise any propagation error after all updates + if propagation_error: + raise propagation_error + + @staticmethod + def _prepare_document_status_update(document, action: str, user): + """ + Prepare document status update information. + + Args: + document: Document object to update + action: Action to perform + user: Current user + + Returns: + dict: Update information or None if no update needed + """ + now = datetime.datetime.now(datetime.UTC).replace(tzinfo=None) + + if action == "enable": + return DocumentService._prepare_enable_update(document, now) + elif action == "disable": + return DocumentService._prepare_disable_update(document, user, now) + elif action == "archive": + return DocumentService._prepare_archive_update(document, user, now) + elif action == "un_archive": + return DocumentService._prepare_unarchive_update(document, now) + + return None + + @staticmethod + def _prepare_enable_update(document, now): + """Prepare updates for enabling a document.""" + if document.enabled: + return None + + return { + "document": document, + "updates": {"enabled": True, "disabled_at": None, "disabled_by": None, "updated_at": now}, + "async_task": {"function": add_document_to_index_task, "args": [document.id]}, + "set_cache": True, + } + + @staticmethod + def _prepare_disable_update(document, user, now): + """Prepare updates for disabling a document.""" + if not document.completed_at or document.indexing_status != "completed": + raise DocumentIndexingError(f"Document: {document.name} is not completed.") + + if not document.enabled: + return None + + return { + "document": document, + "updates": {"enabled": False, "disabled_at": now, "disabled_by": user.id, "updated_at": now}, + "async_task": {"function": remove_document_from_index_task, "args": [document.id]}, + "set_cache": True, + } + + @staticmethod + def _prepare_archive_update(document, user, now): + """Prepare updates for archiving a document.""" + if document.archived: + return None + + update_info = { + "document": document, + "updates": {"archived": True, "archived_at": now, "archived_by": user.id, "updated_at": now}, + "async_task": None, + "set_cache": False, + } + + # Only set async task and cache if document is currently enabled + if document.enabled: + update_info["async_task"] = {"function": remove_document_from_index_task, "args": [document.id]} + update_info["set_cache"] = True + + return update_info + + @staticmethod + def _prepare_unarchive_update(document, now): + """Prepare updates for unarchiving a document.""" + if not document.archived: + return None + + update_info = { + "document": document, + "updates": {"archived": False, "archived_at": None, "archived_by": None, "updated_at": now}, + "async_task": None, + "set_cache": False, + } + + # Only re-index if the document is currently enabled + if document.enabled: + update_info["async_task"] = {"function": add_document_to_index_task, "args": [document.id]} + update_info["set_cache"] = True + + return update_info + class SegmentService: @classmethod @@ -1857,6 +2224,7 @@ class SegmentService: # calc embedding use tokens if document.doc_form == "qa_model": + segment.answer = args.answer tokens = embedding_model.get_text_embedding_num_tokens(texts=[content + segment.answer])[0] else: tokens = embedding_model.get_text_embedding_num_tokens(texts=[content])[0] diff --git a/api/services/entities/knowledge_entities/knowledge_entities.py b/api/services/entities/knowledge_entities/knowledge_entities.py index bb3be61f85..603064ca07 100644 --- a/api/services/entities/knowledge_entities/knowledge_entities.py +++ b/api/services/entities/knowledge_entities/knowledge_entities.py @@ -101,7 +101,7 @@ class WeightModel(BaseModel): class RetrievalModel(BaseModel): - search_method: Literal["hybrid_search", "semantic_search", "full_text_search"] + search_method: Literal["hybrid_search", "semantic_search", "full_text_search", "keyword_search"] reranking_enable: bool reranking_model: Optional[RerankingModel] = None reranking_mode: Optional[str] = None diff --git a/api/services/errors/app.py b/api/services/errors/app.py index 87e9e9247d..5d348c61be 100644 --- a/api/services/errors/app.py +++ b/api/services/errors/app.py @@ -4,3 +4,7 @@ class MoreLikeThisDisabledError(Exception): class WorkflowHashNotEqualError(Exception): pass + + +class IsDraftWorkflowError(Exception): + pass diff --git a/api/services/metadata_service.py b/api/services/metadata_service.py index 26d6d4ce18..cfcb121153 100644 --- a/api/services/metadata_service.py +++ b/api/services/metadata_service.py @@ -19,6 +19,10 @@ from services.entities.knowledge_entities.knowledge_entities import ( class MetadataService: @staticmethod def create_metadata(dataset_id: str, metadata_args: MetadataArgs) -> DatasetMetadata: + # check if metadata name is too long + if len(metadata_args.name) > 255: + raise ValueError("Metadata name cannot exceed 255 characters.") + # check if metadata name already exists if ( db.session.query(DatasetMetadata) @@ -42,6 +46,10 @@ class MetadataService: @staticmethod def update_metadata_name(dataset_id: str, metadata_id: str, name: str) -> DatasetMetadata: # type: ignore + # check if metadata name is too long + if len(name) > 255: + raise ValueError("Metadata name cannot exceed 255 characters.") + lock_key = f"dataset_metadata_lock_{dataset_id}" # check if metadata name already exists if ( diff --git a/api/services/moderation_service.py b/api/services/moderation_service.py deleted file mode 100644 index 082afeed89..0000000000 --- a/api/services/moderation_service.py +++ /dev/null @@ -1,23 +0,0 @@ -from typing import Optional - -from core.moderation.factory import ModerationFactory, ModerationOutputsResult -from extensions.ext_database import db -from models.model import App, AppModelConfig - - -class ModerationService: - def moderation_for_outputs(self, app_id: str, app_model: App, text: str) -> ModerationOutputsResult: - app_model_config: Optional[AppModelConfig] = None - - app_model_config = ( - db.session.query(AppModelConfig).filter(AppModelConfig.id == app_model.app_model_config_id).first() - ) - - if not app_model_config: - raise ValueError("app model config not found") - - name = app_model_config.sensitive_word_avoidance_dict["type"] - config = app_model_config.sensitive_word_avoidance_dict["config"] - - moderation = ModerationFactory(name, app_id, app_model.tenant_id, config) - return moderation.moderation_for_outputs(text) diff --git a/api/services/ops_service.py b/api/services/ops_service.py index 792f50703e..dbeb4f1908 100644 --- a/api/services/ops_service.py +++ b/api/services/ops_service.py @@ -34,6 +34,24 @@ class OpsService: ) new_decrypt_tracing_config = OpsTraceManager.obfuscated_decrypt_token(tracing_provider, decrypt_tracing_config) + if tracing_provider == "arize" and ( + "project_url" not in decrypt_tracing_config or not decrypt_tracing_config.get("project_url") + ): + try: + project_url = OpsTraceManager.get_trace_config_project_url(decrypt_tracing_config, tracing_provider) + new_decrypt_tracing_config.update({"project_url": project_url}) + except Exception: + new_decrypt_tracing_config.update({"project_url": "https://app.arize.com/"}) + + if tracing_provider == "phoenix" and ( + "project_url" not in decrypt_tracing_config or not decrypt_tracing_config.get("project_url") + ): + try: + project_url = OpsTraceManager.get_trace_config_project_url(decrypt_tracing_config, tracing_provider) + new_decrypt_tracing_config.update({"project_url": project_url}) + except Exception: + new_decrypt_tracing_config.update({"project_url": "https://app.phoenix.arize.com/projects/"}) + if tracing_provider == "langfuse" and ( "project_key" not in decrypt_tracing_config or not decrypt_tracing_config.get("project_key") ): @@ -76,6 +94,16 @@ class OpsService: new_decrypt_tracing_config.update({"project_url": project_url}) except Exception: new_decrypt_tracing_config.update({"project_url": "https://wandb.ai/"}) + + if tracing_provider == "aliyun" and ( + "project_url" not in decrypt_tracing_config or not decrypt_tracing_config.get("project_url") + ): + try: + project_url = OpsTraceManager.get_trace_config_project_url(decrypt_tracing_config, tracing_provider) + new_decrypt_tracing_config.update({"project_url": project_url}) + except Exception: + new_decrypt_tracing_config.update({"project_url": "https://arms.console.aliyun.com/"}) + trace_config_data.tracing_config = new_decrypt_tracing_config return trace_config_data.to_dict() @@ -107,7 +135,9 @@ class OpsService: return {"error": "Invalid Credentials"} # get project url - if tracing_provider == "langfuse": + if tracing_provider in ("arize", "phoenix"): + project_url = OpsTraceManager.get_trace_config_project_url(tracing_config, tracing_provider) + elif tracing_provider == "langfuse": project_key = OpsTraceManager.get_trace_config_project_key(tracing_config, tracing_provider) project_url = "{host}/project/{key}".format(host=tracing_config.get("host"), key=project_key) elif tracing_provider in ("langsmith", "opik"): diff --git a/api/services/plugin/data_migration.py b/api/services/plugin/data_migration.py index 1c5abfecba..5324036414 100644 --- a/api/services/plugin/data_migration.py +++ b/api/services/plugin/data_migration.py @@ -3,7 +3,7 @@ import logging import click -from core.entities import DEFAULT_PLUGIN_ID +from core.plugin.entities.plugin import GenericProviderID, ModelProviderID, ToolProviderID from models.engine import db logger = logging.getLogger(__name__) @@ -12,17 +12,17 @@ logger = logging.getLogger(__name__) class PluginDataMigration: @classmethod def migrate(cls) -> None: - cls.migrate_db_records("providers", "provider_name") # large table - cls.migrate_db_records("provider_models", "provider_name") - cls.migrate_db_records("provider_orders", "provider_name") - cls.migrate_db_records("tenant_default_models", "provider_name") - cls.migrate_db_records("tenant_preferred_model_providers", "provider_name") - cls.migrate_db_records("provider_model_settings", "provider_name") - cls.migrate_db_records("load_balancing_model_configs", "provider_name") + cls.migrate_db_records("providers", "provider_name", ModelProviderID) # large table + cls.migrate_db_records("provider_models", "provider_name", ModelProviderID) + cls.migrate_db_records("provider_orders", "provider_name", ModelProviderID) + cls.migrate_db_records("tenant_default_models", "provider_name", ModelProviderID) + cls.migrate_db_records("tenant_preferred_model_providers", "provider_name", ModelProviderID) + cls.migrate_db_records("provider_model_settings", "provider_name", ModelProviderID) + cls.migrate_db_records("load_balancing_model_configs", "provider_name", ModelProviderID) cls.migrate_datasets() - cls.migrate_db_records("embeddings", "provider_name") # large table - cls.migrate_db_records("dataset_collection_bindings", "provider_name") - cls.migrate_db_records("tool_builtin_providers", "provider") + cls.migrate_db_records("embeddings", "provider_name", ModelProviderID) # large table + cls.migrate_db_records("dataset_collection_bindings", "provider_name", ModelProviderID) + cls.migrate_db_records("tool_builtin_providers", "provider", ToolProviderID) @classmethod def migrate_datasets(cls) -> None: @@ -66,9 +66,10 @@ limit 1000""" fg="white", ) ) - retrieval_model["reranking_model"]["reranking_provider_name"] = ( - f"{DEFAULT_PLUGIN_ID}/{retrieval_model['reranking_model']['reranking_provider_name']}/{retrieval_model['reranking_model']['reranking_provider_name']}" - ) + # update google to langgenius/gemini/google etc. + retrieval_model["reranking_model"]["reranking_provider_name"] = ModelProviderID( + retrieval_model["reranking_model"]["reranking_provider_name"] + ).to_string() retrieval_model_changed = True click.echo( @@ -86,9 +87,11 @@ limit 1000""" update_retrieval_model_sql = ", retrieval_model = :retrieval_model" params["retrieval_model"] = json.dumps(retrieval_model) + params["provider_name"] = ModelProviderID(provider_name).to_string() + sql = f"""update {table_name} set {provider_column_name} = - concat('{DEFAULT_PLUGIN_ID}/', {provider_column_name}, '/', {provider_column_name}) + :provider_name {update_retrieval_model_sql} where id = :record_id""" conn.execute(db.text(sql), params) @@ -122,7 +125,9 @@ limit 1000""" ) @classmethod - def migrate_db_records(cls, table_name: str, provider_column_name: str) -> None: + def migrate_db_records( + cls, table_name: str, provider_column_name: str, provider_cls: type[GenericProviderID] + ) -> None: click.echo(click.style(f"Migrating [{table_name}] data for plugin", fg="white")) processed_count = 0 @@ -166,7 +171,8 @@ limit 1000""" ) try: - updated_value = f"{DEFAULT_PLUGIN_ID}/{provider_name}/{provider_name}" + # update jina to langgenius/jina_tool/jina etc. + updated_value = provider_cls(provider_name).to_string() batch_updates.append((updated_value, record_id)) except Exception as e: failed_ids.append(record_id) diff --git a/api/services/plugin/oauth_service.py b/api/services/plugin/oauth_service.py index 461247419b..b84dd0afc5 100644 --- a/api/services/plugin/oauth_service.py +++ b/api/services/plugin/oauth_service.py @@ -1,7 +1,53 @@ +import json +import uuid + from core.plugin.impl.base import BasePluginClient +from extensions.ext_redis import redis_client + + +class OAuthProxyService(BasePluginClient): + # Default max age for proxy context parameter in seconds + __MAX_AGE__ = 5 * 60 # 5 minutes + __KEY_PREFIX__ = "oauth_proxy_context:" + + @staticmethod + def create_proxy_context(user_id: str, tenant_id: str, plugin_id: str, provider: str): + """ + Create a proxy context for an OAuth 2.0 authorization request. + + This parameter is a crucial security measure to prevent Cross-Site Request + Forgery (CSRF) attacks. It works by generating a unique nonce and storing it + in a distributed cache (Redis) along with the user's session context. + The returned nonce should be included as the 'proxy_context' parameter in the + authorization URL. Upon callback, the `use_proxy_context` method + is used to verify the state, ensuring the request's integrity and authenticity, + and mitigating replay attacks. + """ + context_id = str(uuid.uuid4()) + data = { + "user_id": user_id, + "plugin_id": plugin_id, + "tenant_id": tenant_id, + "provider": provider, + } + redis_client.setex( + f"{OAuthProxyService.__KEY_PREFIX__}{context_id}", + OAuthProxyService.__MAX_AGE__, + json.dumps(data), + ) + return context_id -class OAuthService(BasePluginClient): - @classmethod - def get_authorization_url(cls, tenant_id: str, user_id: str, provider_name: str) -> str: - return "1234567890" + @staticmethod + def use_proxy_context(context_id: str): + """ + Validate the proxy context parameter. + This checks if the context_id is valid and not expired. + """ + if not context_id: + raise ValueError("context_id is required") + # get data from redis + data = redis_client.getdel(f"{OAuthProxyService.__KEY_PREFIX__}{context_id}") + if not data: + raise ValueError("context_id is invalid") + return json.loads(data) diff --git a/api/services/plugin/plugin_parameter_service.py b/api/services/plugin/plugin_parameter_service.py new file mode 100644 index 0000000000..393213c0e2 --- /dev/null +++ b/api/services/plugin/plugin_parameter_service.py @@ -0,0 +1,74 @@ +from collections.abc import Mapping, Sequence +from typing import Any, Literal + +from sqlalchemy.orm import Session + +from core.plugin.entities.parameters import PluginParameterOption +from core.plugin.impl.dynamic_select import DynamicSelectClient +from core.tools.tool_manager import ToolManager +from core.tools.utils.configuration import ProviderConfigEncrypter +from extensions.ext_database import db +from models.tools import BuiltinToolProvider + + +class PluginParameterService: + @staticmethod + def get_dynamic_select_options( + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + action: str, + parameter: str, + provider_type: Literal["tool"], + ) -> Sequence[PluginParameterOption]: + """ + Get dynamic select options for a plugin parameter. + + Args: + tenant_id: The tenant ID. + plugin_id: The plugin ID. + provider: The provider name. + action: The action name. + parameter: The parameter name. + """ + credentials: Mapping[str, Any] = {} + + match provider_type: + case "tool": + provider_controller = ToolManager.get_builtin_provider(provider, tenant_id) + # init tool configuration + tool_configuration = ProviderConfigEncrypter( + tenant_id=tenant_id, + config=[x.to_basic_provider_config() for x in provider_controller.get_credentials_schema()], + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.entity.identity.name, + ) + + # check if credentials are required + if not provider_controller.need_credentials: + credentials = {} + else: + # fetch credentials from db + with Session(db.engine) as session: + db_record = ( + session.query(BuiltinToolProvider) + .filter( + BuiltinToolProvider.tenant_id == tenant_id, + BuiltinToolProvider.provider == provider, + ) + .first() + ) + + if db_record is None: + raise ValueError(f"Builtin provider {provider} not found when fetching credentials") + + credentials = tool_configuration.decrypt(db_record.credentials) + case _: + raise ValueError(f"Invalid provider type: {provider_type}") + + return ( + DynamicSelectClient() + .fetch_dynamic_select_options(tenant_id, user_id, plugin_id, provider, action, credentials, parameter) + .options + ) diff --git a/api/services/vector_service.py b/api/services/vector_service.py index 19e37f4ee3..9165139193 100644 --- a/api/services/vector_service.py +++ b/api/services/vector_service.py @@ -97,16 +97,16 @@ class VectorService: vector = Vector(dataset=dataset) vector.delete_by_ids([segment.index_node_id]) vector.add_texts([document], duplicate_check=True) - - # update keyword index - keyword = Keyword(dataset) - keyword.delete_by_ids([segment.index_node_id]) - - # save keyword index - if keywords and len(keywords) > 0: - keyword.add_texts([document], keywords_list=[keywords]) else: - keyword.add_texts([document]) + # update keyword index + keyword = Keyword(dataset) + keyword.delete_by_ids([segment.index_node_id]) + + # save keyword index + if keywords and len(keywords) > 0: + keyword.add_texts([document], keywords_list=[keywords]) + else: + keyword.add_texts([document]) @classmethod def generate_child_chunks( diff --git a/api/services/workflow_app_service.py b/api/services/workflow_app_service.py index 6b30a70372..6eabf03018 100644 --- a/api/services/workflow_app_service.py +++ b/api/services/workflow_app_service.py @@ -5,7 +5,7 @@ from sqlalchemy import and_, func, or_, select from sqlalchemy.orm import Session from core.workflow.entities.workflow_execution import WorkflowExecutionStatus -from models import App, EndUser, WorkflowAppLog, WorkflowRun +from models import Account, App, EndUser, WorkflowAppLog, WorkflowRun from models.enums import CreatorUserRole @@ -21,6 +21,8 @@ class WorkflowAppService: created_at_after: datetime | None = None, page: int = 1, limit: int = 20, + created_by_end_user_session_id: str | None = None, + created_by_account: str | None = None, ) -> dict: """ Get paginate workflow app logs using SQLAlchemy 2.0 style @@ -32,6 +34,8 @@ class WorkflowAppService: :param created_at_after: filter logs created after this timestamp :param page: page number :param limit: items per page + :param created_by_end_user_session_id: filter by end user session id + :param created_by_account: filter by account email :return: Pagination object """ # Build base statement using SQLAlchemy 2.0 style @@ -71,6 +75,26 @@ class WorkflowAppService: if created_at_after: stmt = stmt.where(WorkflowAppLog.created_at >= created_at_after) + # Filter by end user session id or account email + if created_by_end_user_session_id: + stmt = stmt.join( + EndUser, + and_( + WorkflowAppLog.created_by == EndUser.id, + WorkflowAppLog.created_by_role == CreatorUserRole.END_USER, + EndUser.session_id == created_by_end_user_session_id, + ), + ) + if created_by_account: + stmt = stmt.join( + Account, + and_( + WorkflowAppLog.created_by == Account.id, + WorkflowAppLog.created_by_role == CreatorUserRole.ACCOUNT, + Account.email == created_by_account, + ), + ) + stmt = stmt.order_by(WorkflowAppLog.created_at.desc()) # Get total count using the same filters diff --git a/api/services/workflow_draft_variable_service.py b/api/services/workflow_draft_variable_service.py new file mode 100644 index 0000000000..44fd72b5e4 --- /dev/null +++ b/api/services/workflow_draft_variable_service.py @@ -0,0 +1,727 @@ +import dataclasses +import datetime +import logging +from collections.abc import Mapping, Sequence +from enum import StrEnum +from typing import Any, ClassVar + +from sqlalchemy import Engine, orm, select +from sqlalchemy.dialects.postgresql import insert +from sqlalchemy.orm import Session +from sqlalchemy.sql.expression import and_, or_ + +from core.app.entities.app_invoke_entities import InvokeFrom +from core.file.models import File +from core.variables import Segment, StringSegment, Variable +from core.variables.consts import MIN_SELECTORS_LENGTH +from core.variables.segments import ArrayFileSegment, FileSegment +from core.variables.types import SegmentType +from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, ENVIRONMENT_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID +from core.workflow.enums import SystemVariableKey +from core.workflow.nodes import NodeType +from core.workflow.nodes.variable_assigner.common.helpers import get_updated_variables +from core.workflow.variable_loader import VariableLoader +from factories.file_factory import StorageKeyLoader +from factories.variable_factory import build_segment, segment_to_variable +from models import App, Conversation +from models.enums import DraftVariableType +from models.workflow import Workflow, WorkflowDraftVariable, WorkflowNodeExecutionModel, is_system_variable_editable + +_logger = logging.getLogger(__name__) + + +@dataclasses.dataclass(frozen=True) +class WorkflowDraftVariableList: + variables: list[WorkflowDraftVariable] + total: int | None = None + + +class WorkflowDraftVariableError(Exception): + pass + + +class VariableResetError(WorkflowDraftVariableError): + pass + + +class UpdateNotSupportedError(WorkflowDraftVariableError): + pass + + +class DraftVarLoader(VariableLoader): + # This implements the VariableLoader interface for loading draft variables. + # + # ref: core.workflow.variable_loader.VariableLoader + + # Database engine used for loading variables. + _engine: Engine + # Application ID for which variables are being loaded. + _app_id: str + _tenant_id: str + _fallback_variables: Sequence[Variable] + + def __init__( + self, + engine: Engine, + app_id: str, + tenant_id: str, + fallback_variables: Sequence[Variable] | None = None, + ) -> None: + self._engine = engine + self._app_id = app_id + self._tenant_id = tenant_id + self._fallback_variables = fallback_variables or [] + + def _selector_to_tuple(self, selector: Sequence[str]) -> tuple[str, str]: + return (selector[0], selector[1]) + + def load_variables(self, selectors: list[list[str]]) -> list[Variable]: + if not selectors: + return [] + + # Map each selector (as a tuple via `_selector_to_tuple`) to its corresponding Variable instance. + variable_by_selector: dict[tuple[str, str], Variable] = {} + + with Session(bind=self._engine, expire_on_commit=False) as session: + srv = WorkflowDraftVariableService(session) + draft_vars = srv.get_draft_variables_by_selectors(self._app_id, selectors) + + for draft_var in draft_vars: + segment = draft_var.get_value() + variable = segment_to_variable( + segment=segment, + selector=draft_var.get_selector(), + id=draft_var.id, + name=draft_var.name, + description=draft_var.description, + ) + selector_tuple = self._selector_to_tuple(variable.selector) + variable_by_selector[selector_tuple] = variable + + # Important: + files: list[File] = [] + for draft_var in draft_vars: + value = draft_var.get_value() + if isinstance(value, FileSegment): + files.append(value.value) + elif isinstance(value, ArrayFileSegment): + files.extend(value.value) + with Session(bind=self._engine) as session: + storage_key_loader = StorageKeyLoader(session, tenant_id=self._tenant_id) + storage_key_loader.load_storage_keys(files) + + return list(variable_by_selector.values()) + + +class WorkflowDraftVariableService: + _session: Session + + def __init__(self, session: Session) -> None: + self._session = session + + def get_variable(self, variable_id: str) -> WorkflowDraftVariable | None: + return self._session.query(WorkflowDraftVariable).filter(WorkflowDraftVariable.id == variable_id).first() + + def get_draft_variables_by_selectors( + self, + app_id: str, + selectors: Sequence[list[str]], + ) -> list[WorkflowDraftVariable]: + ors = [] + for selector in selectors: + assert len(selector) >= MIN_SELECTORS_LENGTH, f"Invalid selector to get: {selector}" + node_id, name = selector[:2] + ors.append(and_(WorkflowDraftVariable.node_id == node_id, WorkflowDraftVariable.name == name)) + + # NOTE(QuantumGhost): Although the number of `or` expressions may be large, as long as + # each expression includes conditions on both `node_id` and `name` (which are covered by the unique index), + # PostgreSQL can efficiently retrieve the results using a bitmap index scan. + # + # Alternatively, a `SELECT` statement could be constructed for each selector and + # combined using `UNION` to fetch all rows. + # Benchmarking indicates that both approaches yield comparable performance. + variables = ( + self._session.query(WorkflowDraftVariable).where(WorkflowDraftVariable.app_id == app_id, or_(*ors)).all() + ) + return variables + + def list_variables_without_values(self, app_id: str, page: int, limit: int) -> WorkflowDraftVariableList: + criteria = WorkflowDraftVariable.app_id == app_id + total = None + query = self._session.query(WorkflowDraftVariable).filter(criteria) + if page == 1: + total = query.count() + variables = ( + # Do not load the `value` field. + query.options(orm.defer(WorkflowDraftVariable.value)) + .order_by(WorkflowDraftVariable.created_at.desc()) + .limit(limit) + .offset((page - 1) * limit) + .all() + ) + + return WorkflowDraftVariableList(variables=variables, total=total) + + def _list_node_variables(self, app_id: str, node_id: str) -> WorkflowDraftVariableList: + criteria = ( + WorkflowDraftVariable.app_id == app_id, + WorkflowDraftVariable.node_id == node_id, + ) + query = self._session.query(WorkflowDraftVariable).filter(*criteria) + variables = query.order_by(WorkflowDraftVariable.created_at.desc()).all() + return WorkflowDraftVariableList(variables=variables) + + def list_node_variables(self, app_id: str, node_id: str) -> WorkflowDraftVariableList: + return self._list_node_variables(app_id, node_id) + + def list_conversation_variables(self, app_id: str) -> WorkflowDraftVariableList: + return self._list_node_variables(app_id, CONVERSATION_VARIABLE_NODE_ID) + + def list_system_variables(self, app_id: str) -> WorkflowDraftVariableList: + return self._list_node_variables(app_id, SYSTEM_VARIABLE_NODE_ID) + + def get_conversation_variable(self, app_id: str, name: str) -> WorkflowDraftVariable | None: + return self._get_variable(app_id=app_id, node_id=CONVERSATION_VARIABLE_NODE_ID, name=name) + + def get_system_variable(self, app_id: str, name: str) -> WorkflowDraftVariable | None: + return self._get_variable(app_id=app_id, node_id=SYSTEM_VARIABLE_NODE_ID, name=name) + + def get_node_variable(self, app_id: str, node_id: str, name: str) -> WorkflowDraftVariable | None: + return self._get_variable(app_id, node_id, name) + + def _get_variable(self, app_id: str, node_id: str, name: str) -> WorkflowDraftVariable | None: + variable = ( + self._session.query(WorkflowDraftVariable) + .where( + WorkflowDraftVariable.app_id == app_id, + WorkflowDraftVariable.node_id == node_id, + WorkflowDraftVariable.name == name, + ) + .first() + ) + return variable + + def update_variable( + self, + variable: WorkflowDraftVariable, + name: str | None = None, + value: Segment | None = None, + ) -> WorkflowDraftVariable: + if not variable.editable: + raise UpdateNotSupportedError(f"variable not support updating, id={variable.id}") + if name is not None: + variable.set_name(name) + if value is not None: + variable.set_value(value) + variable.last_edited_at = datetime.datetime.now(datetime.UTC).replace(tzinfo=None) + self._session.flush() + return variable + + def _reset_conv_var(self, workflow: Workflow, variable: WorkflowDraftVariable) -> WorkflowDraftVariable | None: + conv_var_by_name = {i.name: i for i in workflow.conversation_variables} + conv_var = conv_var_by_name.get(variable.name) + + if conv_var is None: + self._session.delete(instance=variable) + self._session.flush() + _logger.warning( + "Conversation variable not found for draft variable, id=%s, name=%s", variable.id, variable.name + ) + return None + + variable.set_value(conv_var) + variable.last_edited_at = None + self._session.add(variable) + self._session.flush() + return variable + + def _reset_node_var_or_sys_var( + self, workflow: Workflow, variable: WorkflowDraftVariable + ) -> WorkflowDraftVariable | None: + # If a variable does not allow updating, it makes no sence to resetting it. + if not variable.editable: + return variable + # No execution record for this variable, delete the variable instead. + if variable.node_execution_id is None: + self._session.delete(instance=variable) + self._session.flush() + _logger.warning("draft variable has no node_execution_id, id=%s, name=%s", variable.id, variable.name) + return None + + query = select(WorkflowNodeExecutionModel).where(WorkflowNodeExecutionModel.id == variable.node_execution_id) + node_exec = self._session.scalars(query).first() + if node_exec is None: + _logger.warning( + "Node exectution not found for draft variable, id=%s, name=%s, node_execution_id=%s", + variable.id, + variable.name, + variable.node_execution_id, + ) + self._session.delete(instance=variable) + self._session.flush() + return None + + outputs_dict = node_exec.outputs_dict or {} + # a sentinel value used to check the absent of the output variable key. + absent = object() + + if variable.get_variable_type() == DraftVariableType.NODE: + # Get node type for proper value extraction + node_config = workflow.get_node_config_by_id(variable.node_id) + node_type = workflow.get_node_type_from_node_config(node_config) + + # Note: Based on the implementation in `_build_from_variable_assigner_mapping`, + # VariableAssignerNode (both v1 and v2) can only create conversation draft variables. + # For consistency, we should simply return when processing VARIABLE_ASSIGNER nodes. + # + # This implementation must remain synchronized with the `_build_from_variable_assigner_mapping` + # and `save` methods. + if node_type == NodeType.VARIABLE_ASSIGNER: + return variable + output_value = outputs_dict.get(variable.name, absent) + else: + output_value = outputs_dict.get(f"sys.{variable.name}", absent) + + # We cannot use `is None` to check the existence of an output variable here as + # the value of the output may be `None`. + if output_value is absent: + # If variable not found in execution data, delete the variable + self._session.delete(instance=variable) + self._session.flush() + return None + value_seg = WorkflowDraftVariable.build_segment_with_type(variable.value_type, output_value) + # Extract variable value using unified logic + variable.set_value(value_seg) + variable.last_edited_at = None # Reset to indicate this is a reset operation + self._session.flush() + return variable + + def reset_variable(self, workflow: Workflow, variable: WorkflowDraftVariable) -> WorkflowDraftVariable | None: + variable_type = variable.get_variable_type() + if variable_type == DraftVariableType.CONVERSATION: + return self._reset_conv_var(workflow, variable) + else: + return self._reset_node_var_or_sys_var(workflow, variable) + + def delete_variable(self, variable: WorkflowDraftVariable): + self._session.delete(variable) + + def delete_workflow_variables(self, app_id: str): + ( + self._session.query(WorkflowDraftVariable) + .filter(WorkflowDraftVariable.app_id == app_id) + .delete(synchronize_session=False) + ) + + def delete_node_variables(self, app_id: str, node_id: str): + return self._delete_node_variables(app_id, node_id) + + def _delete_node_variables(self, app_id: str, node_id: str): + self._session.query(WorkflowDraftVariable).where( + WorkflowDraftVariable.app_id == app_id, + WorkflowDraftVariable.node_id == node_id, + ).delete() + + def _get_conversation_id_from_draft_variable(self, app_id: str) -> str | None: + draft_var = self._get_variable( + app_id=app_id, + node_id=SYSTEM_VARIABLE_NODE_ID, + name=str(SystemVariableKey.CONVERSATION_ID), + ) + if draft_var is None: + return None + segment = draft_var.get_value() + if not isinstance(segment, StringSegment): + _logger.warning( + "sys.conversation_id variable is not a string: app_id=%s, id=%s", + app_id, + draft_var.id, + ) + return None + return segment.value + + def get_or_create_conversation( + self, + account_id: str, + app: App, + workflow: Workflow, + ) -> str: + """ + get_or_create_conversation creates and returns the ID of a conversation for debugging. + + If a conversation already exists, as determined by the following criteria, its ID is returned: + - The system variable `sys.conversation_id` exists in the draft variable table, and + - A corresponding conversation record is found in the database. + + If no such conversation exists, a new conversation is created and its ID is returned. + """ + conv_id = self._get_conversation_id_from_draft_variable(workflow.app_id) + + if conv_id is not None: + conversation = ( + self._session.query(Conversation) + .filter( + Conversation.id == conv_id, + Conversation.app_id == workflow.app_id, + ) + .first() + ) + # Only return the conversation ID if it exists and is valid (has a correspond conversation record in DB). + if conversation is not None: + return conv_id + conversation = Conversation( + app_id=workflow.app_id, + app_model_config_id=app.app_model_config_id, + model_provider=None, + model_id="", + override_model_configs=None, + mode=app.mode, + name="Draft Debugging Conversation", + inputs={}, + introduction="", + system_instruction="", + system_instruction_tokens=0, + status="normal", + invoke_from=InvokeFrom.DEBUGGER.value, + from_source="console", + from_end_user_id=None, + from_account_id=account_id, + ) + + self._session.add(conversation) + self._session.flush() + return conversation.id + + def prefill_conversation_variable_default_values(self, workflow: Workflow): + """""" + draft_conv_vars: list[WorkflowDraftVariable] = [] + for conv_var in workflow.conversation_variables: + draft_var = WorkflowDraftVariable.new_conversation_variable( + app_id=workflow.app_id, + name=conv_var.name, + value=conv_var, + description=conv_var.description, + ) + draft_conv_vars.append(draft_var) + _batch_upsert_draft_varaible( + self._session, + draft_conv_vars, + policy=_UpsertPolicy.IGNORE, + ) + + +class _UpsertPolicy(StrEnum): + IGNORE = "ignore" + OVERWRITE = "overwrite" + + +def _batch_upsert_draft_varaible( + session: Session, + draft_vars: Sequence[WorkflowDraftVariable], + policy: _UpsertPolicy = _UpsertPolicy.OVERWRITE, +) -> None: + if not draft_vars: + return None + # Although we could use SQLAlchemy ORM operations here, we choose not to for several reasons: + # + # 1. The variable saving process involves writing multiple rows to the + # `workflow_draft_variables` table. Batch insertion significantly improves performance. + # 2. Using the ORM would require either: + # + # a. Checking for the existence of each variable before insertion, + # resulting in 2n SQL statements for n variables and potential concurrency issues. + # b. Attempting insertion first, then updating if a unique index violation occurs, + # which still results in n to 2n SQL statements. + # + # Both approaches are inefficient and suboptimal. + # 3. We do not need to retrieve the results of the SQL execution or populate ORM + # model instances with the returned values. + # 4. Batch insertion with `ON CONFLICT DO UPDATE` allows us to insert or update all + # variables in a single SQL statement, avoiding the issues above. + # + # For these reasons, we use the SQLAlchemy query builder and rely on dialect-specific + # insert operations instead of the ORM layer. + stmt = insert(WorkflowDraftVariable).values([_model_to_insertion_dict(v) for v in draft_vars]) + if policy == _UpsertPolicy.OVERWRITE: + stmt = stmt.on_conflict_do_update( + index_elements=WorkflowDraftVariable.unique_app_id_node_id_name(), + set_={ + # Refresh creation timestamp to ensure updated variables + # appear first in chronologically sorted result sets. + "created_at": stmt.excluded.created_at, + "updated_at": stmt.excluded.updated_at, + "last_edited_at": stmt.excluded.last_edited_at, + "description": stmt.excluded.description, + "value_type": stmt.excluded.value_type, + "value": stmt.excluded.value, + "visible": stmt.excluded.visible, + "editable": stmt.excluded.editable, + "node_execution_id": stmt.excluded.node_execution_id, + }, + ) + elif _UpsertPolicy.IGNORE: + stmt = stmt.on_conflict_do_nothing(index_elements=WorkflowDraftVariable.unique_app_id_node_id_name()) + else: + raise Exception("Invalid value for update policy.") + session.execute(stmt) + + +def _model_to_insertion_dict(model: WorkflowDraftVariable) -> dict[str, Any]: + d: dict[str, Any] = { + "app_id": model.app_id, + "last_edited_at": None, + "node_id": model.node_id, + "name": model.name, + "selector": model.selector, + "value_type": model.value_type, + "value": model.value, + "node_execution_id": model.node_execution_id, + } + if model.visible is not None: + d["visible"] = model.visible + if model.editable is not None: + d["editable"] = model.editable + if model.created_at is not None: + d["created_at"] = model.created_at + if model.updated_at is not None: + d["updated_at"] = model.updated_at + if model.description is not None: + d["description"] = model.description + return d + + +def _build_segment_for_serialized_values(v: Any) -> Segment: + """ + Reconstructs Segment objects from serialized values, with special handling + for FileSegment and ArrayFileSegment types. + + This function should only be used when: + 1. No explicit type information is available + 2. The input value is in serialized form (dict or list) + + It detects potential file objects in the serialized data and properly rebuilds the + appropriate segment type. + """ + return build_segment(WorkflowDraftVariable.rebuild_file_types(v)) + + +class DraftVariableSaver: + # _DUMMY_OUTPUT_IDENTITY is a placeholder output for workflow nodes. + # Its sole possible value is `None`. + # + # This is used to signal the execution of a workflow node when it has no other outputs. + _DUMMY_OUTPUT_IDENTITY: ClassVar[str] = "__dummy__" + _DUMMY_OUTPUT_VALUE: ClassVar[None] = None + + # _EXCLUDE_VARIABLE_NAMES_MAPPING maps node types and versions to variable names that + # should be excluded when saving draft variables. This prevents certain internal or + # technical variables from being exposed in the draft environment, particularly those + # that aren't meant to be directly edited or viewed by users. + _EXCLUDE_VARIABLE_NAMES_MAPPING: dict[NodeType, frozenset[str]] = { + NodeType.LLM: frozenset(["finish_reason"]), + NodeType.LOOP: frozenset(["loop_round"]), + } + + # Database session used for persisting draft variables. + _session: Session + + # The application ID associated with the draft variables. + # This should match the `Workflow.app_id` of the workflow to which the current node belongs. + _app_id: str + + # The ID of the node for which DraftVariableSaver is saving output variables. + _node_id: str + + # The type of the current node (see NodeType). + _node_type: NodeType + + # + _node_execution_id: str + + # _enclosing_node_id identifies the container node that the current node belongs to. + # For example, if the current node is an LLM node inside an Iteration node + # or Loop node, then `_enclosing_node_id` refers to the ID of + # the containing Iteration or Loop node. + # + # If the current node is not nested within another node, `_enclosing_node_id` is + # `None`. + _enclosing_node_id: str | None + + def __init__( + self, + session: Session, + app_id: str, + node_id: str, + node_type: NodeType, + node_execution_id: str, + enclosing_node_id: str | None = None, + ): + # Important: `node_execution_id` parameter refers to the primary key (`id`) of the + # WorkflowNodeExecutionModel/WorkflowNodeExecution, not their `node_execution_id` + # field. These are distinct database fields with different purposes. + self._session = session + self._app_id = app_id + self._node_id = node_id + self._node_type = node_type + self._node_execution_id = node_execution_id + self._enclosing_node_id = enclosing_node_id + + def _create_dummy_output_variable(self): + return WorkflowDraftVariable.new_node_variable( + app_id=self._app_id, + node_id=self._node_id, + name=self._DUMMY_OUTPUT_IDENTITY, + node_execution_id=self._node_execution_id, + value=build_segment(self._DUMMY_OUTPUT_VALUE), + visible=False, + editable=False, + ) + + def _should_save_output_variables_for_draft(self) -> bool: + if self._enclosing_node_id is not None and self._node_type != NodeType.VARIABLE_ASSIGNER: + # Currently we do not save output variables for nodes inside loop or iteration. + return False + return True + + def _build_from_variable_assigner_mapping(self, process_data: Mapping[str, Any]) -> list[WorkflowDraftVariable]: + draft_vars: list[WorkflowDraftVariable] = [] + updated_variables = get_updated_variables(process_data) or [] + + for item in updated_variables: + selector = item.selector + if len(selector) < MIN_SELECTORS_LENGTH: + raise Exception("selector too short") + # NOTE(QuantumGhost): only the following two kinds of variable could be updated by + # VariableAssigner: ConversationVariable and iteration variable. + # We only save conversation variable here. + if selector[0] != CONVERSATION_VARIABLE_NODE_ID: + continue + segment = WorkflowDraftVariable.build_segment_with_type(segment_type=item.value_type, value=item.new_value) + draft_vars.append( + WorkflowDraftVariable.new_conversation_variable( + app_id=self._app_id, + name=item.name, + value=segment, + ) + ) + # Add a dummy output variable to indicate that this node is executed. + draft_vars.append(self._create_dummy_output_variable()) + return draft_vars + + def _build_variables_from_start_mapping(self, output: Mapping[str, Any]) -> list[WorkflowDraftVariable]: + draft_vars = [] + has_non_sys_variables = False + for name, value in output.items(): + value_seg = _build_segment_for_serialized_values(value) + node_id, name = self._normalize_variable_for_start_node(name) + # If node_id is not `sys`, it means that the variable is a user-defined input field + # in `Start` node. + if node_id != SYSTEM_VARIABLE_NODE_ID: + draft_vars.append( + WorkflowDraftVariable.new_node_variable( + app_id=self._app_id, + node_id=self._node_id, + name=name, + node_execution_id=self._node_execution_id, + value=value_seg, + visible=True, + editable=True, + ) + ) + has_non_sys_variables = True + else: + if name == SystemVariableKey.FILES: + # Here we know the type of variable must be `array[file]`, we + # just build files from the value. + files = [File.model_validate(v) for v in value] + if files: + value_seg = WorkflowDraftVariable.build_segment_with_type(SegmentType.ARRAY_FILE, files) + else: + value_seg = ArrayFileSegment(value=[]) + + draft_vars.append( + WorkflowDraftVariable.new_sys_variable( + app_id=self._app_id, + name=name, + node_execution_id=self._node_execution_id, + value=value_seg, + editable=self._should_variable_be_editable(node_id, name), + ) + ) + if not has_non_sys_variables: + draft_vars.append(self._create_dummy_output_variable()) + return draft_vars + + def _normalize_variable_for_start_node(self, name: str) -> tuple[str, str]: + if not name.startswith(f"{SYSTEM_VARIABLE_NODE_ID}."): + return self._node_id, name + _, name_ = name.split(".", maxsplit=1) + return SYSTEM_VARIABLE_NODE_ID, name_ + + def _build_variables_from_mapping(self, output: Mapping[str, Any]) -> list[WorkflowDraftVariable]: + draft_vars = [] + for name, value in output.items(): + if not self._should_variable_be_saved(name): + _logger.debug( + "Skip saving variable as it has been excluded by its node_type, name=%s, node_type=%s", + name, + self._node_type, + ) + continue + if isinstance(value, Segment): + value_seg = value + else: + value_seg = _build_segment_for_serialized_values(value) + draft_vars.append( + WorkflowDraftVariable.new_node_variable( + app_id=self._app_id, + node_id=self._node_id, + name=name, + node_execution_id=self._node_execution_id, + value=value_seg, + visible=self._should_variable_be_visible(self._node_id, self._node_type, name), + ) + ) + return draft_vars + + def save( + self, + process_data: Mapping[str, Any] | None = None, + outputs: Mapping[str, Any] | None = None, + ): + draft_vars: list[WorkflowDraftVariable] = [] + if outputs is None: + outputs = {} + if process_data is None: + process_data = {} + if not self._should_save_output_variables_for_draft(): + return + if self._node_type == NodeType.VARIABLE_ASSIGNER: + draft_vars = self._build_from_variable_assigner_mapping(process_data=process_data) + elif self._node_type == NodeType.START: + draft_vars = self._build_variables_from_start_mapping(outputs) + else: + draft_vars = self._build_variables_from_mapping(outputs) + _batch_upsert_draft_varaible(self._session, draft_vars) + + @staticmethod + def _should_variable_be_editable(node_id: str, name: str) -> bool: + if node_id in (CONVERSATION_VARIABLE_NODE_ID, ENVIRONMENT_VARIABLE_NODE_ID): + return False + if node_id == SYSTEM_VARIABLE_NODE_ID and not is_system_variable_editable(name): + return False + return True + + @staticmethod + def _should_variable_be_visible(node_id: str, node_type: NodeType, name: str) -> bool: + if node_type in NodeType.IF_ELSE: + return False + if node_id == SYSTEM_VARIABLE_NODE_ID and not is_system_variable_editable(name): + return False + return True + + def _should_variable_be_saved(self, name: str) -> bool: + exclude_var_names = self._EXCLUDE_VARIABLE_NAMES_MAPPING.get(self._node_type) + if exclude_var_names is None: + return True + return name not in exclude_var_names diff --git a/api/services/workflow_service.py b/api/services/workflow_service.py index bc213ccce6..2be57fd51c 100644 --- a/api/services/workflow_service.py +++ b/api/services/workflow_service.py @@ -1,6 +1,7 @@ import json import time -from collections.abc import Callable, Generator, Sequence +import uuid +from collections.abc import Callable, Generator, Mapping, Sequence from datetime import UTC, datetime from typing import Any, Optional from uuid import uuid4 @@ -8,12 +9,16 @@ from uuid import uuid4 from sqlalchemy import select from sqlalchemy.orm import Session +from core.app.app_config.entities import VariableEntityType from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager +from core.file import File from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository from core.variables import Variable from core.workflow.entities.node_entities import NodeRunResult +from core.workflow.entities.variable_pool import VariablePool from core.workflow.entities.workflow_node_execution import WorkflowNodeExecution, WorkflowNodeExecutionStatus +from core.workflow.enums import SystemVariableKey from core.workflow.errors import WorkflowNodeRunFailedError from core.workflow.graph_engine.entities.event import InNodeEvent from core.workflow.nodes import NodeType @@ -22,9 +27,11 @@ from core.workflow.nodes.enums import ErrorStrategy from core.workflow.nodes.event import RunCompletedEvent from core.workflow.nodes.event.types import NodeEvent from core.workflow.nodes.node_mapping import LATEST_VERSION, NODE_TYPE_CLASSES_MAPPING +from core.workflow.nodes.start.entities import StartNodeData from core.workflow.workflow_entry import WorkflowEntry from events.app_event import app_draft_workflow_was_synced, app_published_workflow_was_updated from extensions.ext_database import db +from factories.file_factory import build_from_mapping, build_from_mappings from models.account import Account from models.model import App, AppMode from models.tools import WorkflowToolProvider @@ -34,10 +41,15 @@ from models.workflow import ( WorkflowNodeExecutionTriggeredFrom, WorkflowType, ) -from services.errors.app import WorkflowHashNotEqualError +from services.errors.app import IsDraftWorkflowError, WorkflowHashNotEqualError from services.workflow.workflow_converter import WorkflowConverter from .errors.workflow_service import DraftWorkflowDeletionError, WorkflowInUseError +from .workflow_draft_variable_service import ( + DraftVariableSaver, + DraftVarLoader, + WorkflowDraftVariableService, +) class WorkflowService: @@ -45,6 +57,33 @@ class WorkflowService: Workflow Service """ + def get_node_last_run(self, app_model: App, workflow: Workflow, node_id: str) -> WorkflowNodeExecutionModel | None: + # TODO(QuantumGhost): This query is not fully covered by index. + criteria = ( + WorkflowNodeExecutionModel.tenant_id == app_model.tenant_id, + WorkflowNodeExecutionModel.app_id == app_model.id, + WorkflowNodeExecutionModel.workflow_id == workflow.id, + WorkflowNodeExecutionModel.node_id == node_id, + ) + node_exec = ( + db.session.query(WorkflowNodeExecutionModel) + .filter(*criteria) + .order_by(WorkflowNodeExecutionModel.created_at.desc()) + .first() + ) + return node_exec + + def is_workflow_exist(self, app_model: App) -> bool: + return ( + db.session.query(Workflow) + .filter( + Workflow.tenant_id == app_model.tenant_id, + Workflow.app_id == app_model.id, + Workflow.version == Workflow.VERSION_DRAFT, + ) + .count() + ) > 0 + def get_draft_workflow(self, app_model: App) -> Optional[Workflow]: """ Get draft workflow @@ -61,6 +100,23 @@ class WorkflowService: # return draft workflow return workflow + def get_published_workflow_by_id(self, app_model: App, workflow_id: str) -> Optional[Workflow]: + # fetch published workflow by workflow_id + workflow = ( + db.session.query(Workflow) + .filter( + Workflow.tenant_id == app_model.tenant_id, + Workflow.app_id == app_model.id, + Workflow.id == workflow_id, + ) + .first() + ) + if not workflow: + return None + if workflow.version == Workflow.VERSION_DRAFT: + raise IsDraftWorkflowError(f"Workflow is draft version, id={workflow_id}") + return workflow + def get_published_workflow(self, app_model: App) -> Optional[Workflow]: """ Get published workflow @@ -199,7 +255,7 @@ class WorkflowService: tenant_id=app_model.tenant_id, app_id=app_model.id, type=draft_workflow.type, - version=str(datetime.now(UTC).replace(tzinfo=None)), + version=Workflow.version_from_datetime(datetime.now(UTC).replace(tzinfo=None)), graph=draft_workflow.graph, features=draft_workflow.features, created_by=account.id, @@ -253,26 +309,85 @@ class WorkflowService: return default_config def run_draft_workflow_node( - self, app_model: App, node_id: str, user_inputs: dict, account: Account + self, + app_model: App, + draft_workflow: Workflow, + node_id: str, + user_inputs: Mapping[str, Any], + account: Account, + query: str = "", + files: Sequence[File] | None = None, ) -> WorkflowNodeExecutionModel: """ Run draft workflow node """ - # fetch draft workflow by app_model - draft_workflow = self.get_draft_workflow(app_model=app_model) - if not draft_workflow: - raise ValueError("Workflow not initialized") + files = files or [] + + with Session(bind=db.engine, expire_on_commit=False) as session, session.begin(): + draft_var_srv = WorkflowDraftVariableService(session) + draft_var_srv.prefill_conversation_variable_default_values(draft_workflow) + + node_config = draft_workflow.get_node_config_by_id(node_id) + node_type = Workflow.get_node_type_from_node_config(node_config) + node_data = node_config.get("data", {}) + if node_type == NodeType.START: + with Session(bind=db.engine) as session, session.begin(): + draft_var_srv = WorkflowDraftVariableService(session) + conversation_id = draft_var_srv.get_or_create_conversation( + account_id=account.id, + app=app_model, + workflow=draft_workflow, + ) + start_data = StartNodeData.model_validate(node_data) + user_inputs = _rebuild_file_for_user_inputs_in_start_node( + tenant_id=draft_workflow.tenant_id, start_node_data=start_data, user_inputs=user_inputs + ) + # init variable pool + variable_pool = _setup_variable_pool( + query=query, + files=files or [], + user_id=account.id, + user_inputs=user_inputs, + workflow=draft_workflow, + # NOTE(QuantumGhost): We rely on `DraftVarLoader` to load conversation variables. + conversation_variables=[], + node_type=node_type, + conversation_id=conversation_id, + ) + + else: + variable_pool = VariablePool( + system_variables={}, + user_inputs=user_inputs, + environment_variables=draft_workflow.environment_variables, + conversation_variables=[], + ) + + variable_loader = DraftVarLoader( + engine=db.engine, + app_id=app_model.id, + tenant_id=app_model.tenant_id, + ) + + eclosing_node_type_and_id = draft_workflow.get_enclosing_node_type_and_id(node_config) + if eclosing_node_type_and_id: + _, enclosing_node_id = eclosing_node_type_and_id + else: + enclosing_node_id = None + + run = WorkflowEntry.single_step_run( + workflow=draft_workflow, + node_id=node_id, + user_inputs=user_inputs, + user_id=account.id, + variable_pool=variable_pool, + variable_loader=variable_loader, + ) # run draft workflow node start_at = time.perf_counter() - node_execution = self._handle_node_run_result( - invoke_node_fn=lambda: WorkflowEntry.single_step_run( - workflow=draft_workflow, - node_id=node_id, - user_inputs=user_inputs, - user_id=account.id, - ), + invoke_node_fn=lambda: run, start_at=start_at, node_id=node_id, ) @@ -292,6 +407,17 @@ class WorkflowService: # Convert node_execution to WorkflowNodeExecution after save workflow_node_execution = repository.to_db_model(node_execution) + with Session(bind=db.engine) as session, session.begin(): + draft_var_saver = DraftVariableSaver( + session=session, + app_id=app_model.id, + node_id=workflow_node_execution.node_id, + node_type=NodeType(workflow_node_execution.node_type), + enclosing_node_id=enclosing_node_id, + node_execution_id=node_execution.id, + ) + draft_var_saver.save(process_data=node_execution.process_data, outputs=node_execution.outputs) + session.commit() return workflow_node_execution def run_free_workflow_node( @@ -332,7 +458,7 @@ class WorkflowService: node_run_result = event.run_result # sign output files - node_run_result.outputs = WorkflowEntry.handle_special_values(node_run_result.outputs) + # node_run_result.outputs = WorkflowEntry.handle_special_values(node_run_result.outputs) break if not node_run_result: @@ -394,7 +520,7 @@ class WorkflowService: if node_run_result.process_data else None ) - outputs = WorkflowEntry.handle_special_values(node_run_result.outputs) if node_run_result.outputs else None + outputs = node_run_result.outputs node_execution.inputs = inputs node_execution.process_data = process_data @@ -531,3 +657,83 @@ class WorkflowService: session.delete(workflow) return True + + +def _setup_variable_pool( + query: str, + files: Sequence[File], + user_id: str, + user_inputs: Mapping[str, Any], + workflow: Workflow, + node_type: NodeType, + conversation_id: str, + conversation_variables: list[Variable], +): + # Only inject system variables for START node type. + if node_type == NodeType.START: + # Create a variable pool. + system_inputs: dict[SystemVariableKey, Any] = { + # From inputs: + SystemVariableKey.FILES: files, + SystemVariableKey.USER_ID: user_id, + # From workflow model + SystemVariableKey.APP_ID: workflow.app_id, + SystemVariableKey.WORKFLOW_ID: workflow.id, + # Randomly generated. + SystemVariableKey.WORKFLOW_EXECUTION_ID: str(uuid.uuid4()), + } + + # Only add chatflow-specific variables for non-workflow types + if workflow.type != WorkflowType.WORKFLOW.value: + system_inputs.update( + { + SystemVariableKey.QUERY: query, + SystemVariableKey.CONVERSATION_ID: conversation_id, + SystemVariableKey.DIALOGUE_COUNT: 0, + } + ) + else: + system_inputs = {} + + # init variable pool + variable_pool = VariablePool( + system_variables=system_inputs, + user_inputs=user_inputs, + environment_variables=workflow.environment_variables, + conversation_variables=conversation_variables, + ) + + return variable_pool + + +def _rebuild_file_for_user_inputs_in_start_node( + tenant_id: str, start_node_data: StartNodeData, user_inputs: Mapping[str, Any] +) -> Mapping[str, Any]: + inputs_copy = dict(user_inputs) + + for variable in start_node_data.variables: + if variable.type not in (VariableEntityType.FILE, VariableEntityType.FILE_LIST): + continue + if variable.variable not in user_inputs: + continue + value = user_inputs[variable.variable] + file = _rebuild_single_file(tenant_id=tenant_id, value=value, variable_entity_type=variable.type) + inputs_copy[variable.variable] = file + return inputs_copy + + +def _rebuild_single_file(tenant_id: str, value: Any, variable_entity_type: VariableEntityType) -> File | Sequence[File]: + if variable_entity_type == VariableEntityType.FILE: + if not isinstance(value, dict): + raise ValueError(f"expected dict for file object, got {type(value)}") + return build_from_mapping(mapping=value, tenant_id=tenant_id) + elif variable_entity_type == VariableEntityType.FILE_LIST: + if not isinstance(value, list): + raise ValueError(f"expected list for file list object, got {type(value)}") + if len(value) == 0: + return [] + if not isinstance(value[0], dict): + raise ValueError(f"expected dict for first element in the file list, got {type(value)}") + return build_from_mappings(mappings=value, tenant_id=tenant_id) + else: + raise Exception("unreachable") diff --git a/api/tests/integration_tests/.env.example b/api/tests/integration_tests/.env.example index 9e40a8494d..4046096c27 100644 --- a/api/tests/integration_tests/.env.example +++ b/api/tests/integration_tests/.env.example @@ -1,107 +1,217 @@ -# OpenAI API Key -OPENAI_API_KEY= +FLASK_APP=app.py +FLASK_DEBUG=0 +SECRET_KEY='uhySf6a3aZuvRNfAlcr47paOw9TRYBY6j8ZHXpVw1yx5RP27Yj3w2uvI' + +CONSOLE_API_URL=http://127.0.0.1:5001 +CONSOLE_WEB_URL=http://127.0.0.1:3000 + +# Service API base URL +SERVICE_API_URL=http://127.0.0.1:5001 + +# Web APP base URL +APP_WEB_URL=http://127.0.0.1:3000 + +# Files URL +FILES_URL=http://127.0.0.1:5001 + +# The time in seconds after the signature is rejected +FILES_ACCESS_TIMEOUT=300 + +# Access token expiration time in minutes +ACCESS_TOKEN_EXPIRE_MINUTES=60 + +# Refresh token expiration time in days +REFRESH_TOKEN_EXPIRE_DAYS=30 + +# celery configuration +CELERY_BROKER_URL=redis://:difyai123456@localhost:6379/1 + +# redis configuration +REDIS_HOST=localhost +REDIS_PORT=6379 +REDIS_USERNAME= +REDIS_PASSWORD=difyai123456 +REDIS_USE_SSL=false +REDIS_DB=0 + +# PostgreSQL database configuration +DB_USERNAME=postgres +DB_PASSWORD=difyai123456 +DB_HOST=localhost +DB_PORT=5432 +DB_DATABASE=dify + +# Storage configuration +# use for store upload files, private keys... +# storage type: opendal, s3, aliyun-oss, azure-blob, baidu-obs, google-storage, huawei-obs, oci-storage, tencent-cos, volcengine-tos, supabase +STORAGE_TYPE=opendal + +# Apache OpenDAL storage configuration, refer to https://github.com/apache/opendal +OPENDAL_SCHEME=fs +OPENDAL_FS_ROOT=storage + +# CORS configuration +WEB_API_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,* +CONSOLE_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,* + +# Vector database configuration +# support: weaviate, qdrant, milvus, myscale, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector, couchbase, vikingdb, upstash, lindorm, oceanbase +VECTOR_STORE=weaviate +# Weaviate configuration +WEAVIATE_ENDPOINT=http://localhost:8080 +WEAVIATE_API_KEY=WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih +WEAVIATE_GRPC_ENABLED=false +WEAVIATE_BATCH_SIZE=100 + + +# Upload configuration +UPLOAD_FILE_SIZE_LIMIT=15 +UPLOAD_FILE_BATCH_LIMIT=5 +UPLOAD_IMAGE_FILE_SIZE_LIMIT=10 +UPLOAD_VIDEO_FILE_SIZE_LIMIT=100 +UPLOAD_AUDIO_FILE_SIZE_LIMIT=50 + +# Model configuration +MULTIMODAL_SEND_FORMAT=base64 +PROMPT_GENERATION_MAX_TOKENS=4096 +CODE_GENERATION_MAX_TOKENS=1024 + +# Mail configuration, support: resend, smtp +MAIL_TYPE= +MAIL_DEFAULT_SEND_FROM=no-reply +RESEND_API_KEY= +RESEND_API_URL=https://api.resend.com +# smtp configuration +SMTP_SERVER=smtp.example.com +SMTP_PORT=465 +SMTP_USERNAME=123 +SMTP_PASSWORD=abc +SMTP_USE_TLS=true +SMTP_OPPORTUNISTIC_TLS=false + +# Sentry configuration +SENTRY_DSN= + +# DEBUG +DEBUG=false +SQLALCHEMY_ECHO=false + +# Notion import configuration, support public and internal +NOTION_INTEGRATION_TYPE=public +NOTION_CLIENT_SECRET=you-client-secret +NOTION_CLIENT_ID=you-client-id +NOTION_INTERNAL_SECRET=you-internal-secret + +ETL_TYPE=dify +UNSTRUCTURED_API_URL= +UNSTRUCTURED_API_KEY= +SCARF_NO_ANALYTICS=false + +#ssrf +SSRF_PROXY_HTTP_URL= +SSRF_PROXY_HTTPS_URL= +SSRF_DEFAULT_MAX_RETRIES=3 +SSRF_DEFAULT_TIME_OUT=5 +SSRF_DEFAULT_CONNECT_TIME_OUT=5 +SSRF_DEFAULT_READ_TIME_OUT=5 +SSRF_DEFAULT_WRITE_TIME_OUT=5 + +BATCH_UPLOAD_LIMIT=10 +KEYWORD_DATA_SOURCE_TYPE=database + +# Workflow file upload limit +WORKFLOW_FILE_UPLOAD_LIMIT=10 -# Azure OpenAI API Base Endpoint & API Key -AZURE_OPENAI_API_BASE= -AZURE_OPENAI_API_KEY= - -# Anthropic API Key -ANTHROPIC_API_KEY= - -# Replicate API Key -REPLICATE_API_KEY= - -# Hugging Face API Key -HUGGINGFACE_API_KEY= -HUGGINGFACE_TEXT_GEN_ENDPOINT_URL= -HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL= -HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL= - -# Minimax Credentials -MINIMAX_API_KEY= -MINIMAX_GROUP_ID= - -# Spark Credentials -SPARK_APP_ID= -SPARK_API_KEY= -SPARK_API_SECRET= - -# Tongyi Credentials -TONGYI_DASHSCOPE_API_KEY= - -# Wenxin Credentials -WENXIN_API_KEY= -WENXIN_SECRET_KEY= - -# ZhipuAI Credentials -ZHIPUAI_API_KEY= - -# Baichuan Credentials -BAICHUAN_API_KEY= -BAICHUAN_SECRET_KEY= - -# ChatGLM Credentials -CHATGLM_API_BASE= - -# Xinference Credentials -XINFERENCE_SERVER_URL= -XINFERENCE_GENERATION_MODEL_UID= -XINFERENCE_CHAT_MODEL_UID= -XINFERENCE_EMBEDDINGS_MODEL_UID= -XINFERENCE_RERANK_MODEL_UID= - -# OpenLLM Credentials -OPENLLM_SERVER_URL= - -# LocalAI Credentials -LOCALAI_SERVER_URL= - -# Cohere Credentials -COHERE_API_KEY= - -# Jina Credentials -JINA_API_KEY= - -# Ollama Credentials -OLLAMA_BASE_URL= +# CODE EXECUTION CONFIGURATION +CODE_EXECUTION_ENDPOINT=http://127.0.0.1:8194 +CODE_EXECUTION_API_KEY=dify-sandbox +CODE_MAX_NUMBER=9223372036854775807 +CODE_MIN_NUMBER=-9223372036854775808 +CODE_MAX_STRING_LENGTH=80000 +TEMPLATE_TRANSFORM_MAX_LENGTH=80000 +CODE_MAX_STRING_ARRAY_LENGTH=30 +CODE_MAX_OBJECT_ARRAY_LENGTH=30 +CODE_MAX_NUMBER_ARRAY_LENGTH=1000 + +# API Tool configuration +API_TOOL_DEFAULT_CONNECT_TIMEOUT=10 +API_TOOL_DEFAULT_READ_TIMEOUT=60 + +# HTTP Node configuration +HTTP_REQUEST_MAX_CONNECT_TIMEOUT=300 +HTTP_REQUEST_MAX_READ_TIMEOUT=600 +HTTP_REQUEST_MAX_WRITE_TIMEOUT=600 +HTTP_REQUEST_NODE_MAX_BINARY_SIZE=10485760 +HTTP_REQUEST_NODE_MAX_TEXT_SIZE=1048576 + +# Respect X-* headers to redirect clients +RESPECT_XFORWARD_HEADERS_ENABLED=false + +# Log file path +LOG_FILE= +# Log file max size, the unit is MB +LOG_FILE_MAX_SIZE=20 +# Log file max backup count +LOG_FILE_BACKUP_COUNT=5 +# Log dateformat +LOG_DATEFORMAT=%Y-%m-%d %H:%M:%S +# Log Timezone +LOG_TZ=UTC +# Log format +LOG_FORMAT=%(asctime)s,%(msecs)d %(levelname)-2s [%(filename)s:%(lineno)d] %(req_id)s %(message)s + +# Indexing configuration +INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH=4000 + +# Workflow runtime configuration +WORKFLOW_MAX_EXECUTION_STEPS=500 +WORKFLOW_MAX_EXECUTION_TIME=1200 +WORKFLOW_CALL_MAX_DEPTH=5 +WORKFLOW_PARALLEL_DEPTH_LIMIT=3 +MAX_VARIABLE_SIZE=204800 + +# App configuration +APP_MAX_EXECUTION_TIME=1200 +APP_MAX_ACTIVE_REQUESTS=0 + +# Celery beat configuration +CELERY_BEAT_SCHEDULER_TIME=1 + +# Position configuration +POSITION_TOOL_PINS= +POSITION_TOOL_INCLUDES= +POSITION_TOOL_EXCLUDES= + +POSITION_PROVIDER_PINS= +POSITION_PROVIDER_INCLUDES= +POSITION_PROVIDER_EXCLUDES= -# Together API Key -TOGETHER_API_KEY= +# Plugin configuration +PLUGIN_DAEMON_KEY=lYkiYYT6owG+71oLerGzA7GXCgOT++6ovaezWAjpCjf+Sjc3ZtU+qUEi +PLUGIN_DAEMON_URL=http://127.0.0.1:5002 +PLUGIN_REMOTE_INSTALL_PORT=5003 +PLUGIN_REMOTE_INSTALL_HOST=localhost +PLUGIN_MAX_PACKAGE_SIZE=15728640 +INNER_API_KEY_FOR_PLUGIN=QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1 -# Mock Switch -MOCK_SWITCH=false +# Marketplace configuration +MARKETPLACE_ENABLED=true +MARKETPLACE_API_URL=https://marketplace.dify.ai -# CODE EXECUTION CONFIGURATION -CODE_EXECUTION_ENDPOINT= -CODE_EXECUTION_API_KEY= +# Endpoint configuration +ENDPOINT_URL_TEMPLATE=http://localhost:5002/e/{hook_id} -# Volcengine MaaS Credentials -VOLC_API_KEY= -VOLC_SECRET_KEY= -VOLC_MODEL_ENDPOINT_ID= -VOLC_EMBEDDING_ENDPOINT_ID= +# Reset password token expiry minutes +RESET_PASSWORD_TOKEN_EXPIRY_MINUTES=5 -# 360 AI Credentials -ZHINAO_API_KEY= +CREATE_TIDB_SERVICE_JOB_ENABLED=false -# Plugin configuration -PLUGIN_DAEMON_KEY= -PLUGIN_DAEMON_URL= +# Maximum number of submitted thread count in a ThreadPool for parallel node execution +MAX_SUBMIT_COUNT=100 +# Lockout duration in seconds +LOGIN_LOCKOUT_DURATION=86400 -# Marketplace configuration -MARKETPLACE_API_URL= -# VESSL AI Credentials -VESSL_AI_MODEL_NAME= -VESSL_AI_API_KEY= -VESSL_AI_ENDPOINT_URL= - -# GPUStack Credentials -GPUSTACK_SERVER_URL= -GPUSTACK_API_KEY= - -# Gitee AI Credentials -GITEE_AI_API_KEY= - -# xAI Credentials -XAI_API_KEY= -XAI_API_BASE= +HTTP_PROXY='http://127.0.0.1:1092' +HTTPS_PROXY='http://127.0.0.1:1092' +NO_PROXY='localhost,127.0.0.1' +LOG_LEVEL=INFO diff --git a/api/tests/integration_tests/conftest.py b/api/tests/integration_tests/conftest.py index 6e3ab4b74b..d9f90f992e 100644 --- a/api/tests/integration_tests/conftest.py +++ b/api/tests/integration_tests/conftest.py @@ -1,19 +1,91 @@ -import os +import pathlib +import random +import secrets +from collections.abc import Generator -# Getting the absolute path of the current file's directory -ABS_PATH = os.path.dirname(os.path.abspath(__file__)) +import pytest +from flask import Flask +from flask.testing import FlaskClient +from sqlalchemy.orm import Session -# Getting the absolute path of the project's root directory -PROJECT_DIR = os.path.abspath(os.path.join(ABS_PATH, os.pardir, os.pardir)) +from app_factory import create_app +from models import Account, DifySetup, Tenant, TenantAccountJoin, db +from services.account_service import AccountService, RegisterService # Loading the .env file if it exists def _load_env() -> None: - dotenv_path = os.path.join(PROJECT_DIR, "tests", "integration_tests", ".env") - if os.path.exists(dotenv_path): + current_file_path = pathlib.Path(__file__).absolute() + # Items later in the list have higher precedence. + files_to_load = [".env", "vdb.env"] + + env_file_paths = [current_file_path.parent / i for i in files_to_load] + for path in env_file_paths: + if not path.exists(): + continue + from dotenv import load_dotenv - load_dotenv(dotenv_path) + # Set `override=True` to ensure values from `vdb.env` take priority over values from `.env` + load_dotenv(str(path), override=True) _load_env() + +_CACHED_APP = create_app() + + +@pytest.fixture +def flask_app() -> Flask: + return _CACHED_APP + + +@pytest.fixture(scope="session") +def setup_account(request) -> Generator[Account, None, None]: + """`dify_setup` completes the setup process for the Dify application. + + It creates `Account` and `Tenant`, and inserts a `DifySetup` record into the database. + + Most tests in the `controllers` package may require dify has been successfully setup. + """ + with _CACHED_APP.test_request_context(): + rand_suffix = random.randint(int(1e6), int(1e7)) # noqa + name = f"test-user-{rand_suffix}" + email = f"{name}@example.com" + RegisterService.setup( + email=email, + name=name, + password=secrets.token_hex(16), + ip_address="localhost", + ) + + with _CACHED_APP.test_request_context(): + with Session(bind=db.engine, expire_on_commit=False) as session: + account = session.query(Account).filter_by(email=email).one() + + yield account + + with _CACHED_APP.test_request_context(): + db.session.query(DifySetup).delete() + db.session.query(TenantAccountJoin).delete() + db.session.query(Account).delete() + db.session.query(Tenant).delete() + db.session.commit() + + +@pytest.fixture +def flask_req_ctx(): + with _CACHED_APP.test_request_context(): + yield + + +@pytest.fixture +def auth_header(setup_account) -> dict[str, str]: + token = AccountService.get_account_jwt_token(setup_account) + return {"Authorization": f"Bearer {token}"} + + +@pytest.fixture +def test_client() -> Generator[FlaskClient, None, None]: + with _CACHED_APP.test_client() as client: + yield client diff --git a/api/tests/integration_tests/controllers/app_fixture.py b/api/tests/integration_tests/controllers/app_fixture.py deleted file mode 100644 index 32e8c11d19..0000000000 --- a/api/tests/integration_tests/controllers/app_fixture.py +++ /dev/null @@ -1,25 +0,0 @@ -import pytest - -from app_factory import create_app -from configs import dify_config - -mock_user = type( - "MockUser", - (object,), - { - "is_authenticated": True, - "id": "123", - "is_editor": True, - "is_dataset_editor": True, - "status": "active", - "get_id": "123", - "current_tenant_id": "9d2074fc-6f86-45a9-b09d-6ecc63b9056b", - }, -) - - -@pytest.fixture -def app(): - app = create_app() - dify_config.LOGIN_DISABLED = True - return app diff --git a/api/tests/integration_tests/controllers/console/__init__.py b/api/tests/integration_tests/controllers/console/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/tests/integration_tests/controllers/console/app/__init__.py b/api/tests/integration_tests/controllers/console/app/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/tests/integration_tests/controllers/console/app/test_workflow_draft_variable.py b/api/tests/integration_tests/controllers/console/app/test_workflow_draft_variable.py new file mode 100644 index 0000000000..038f37af5f --- /dev/null +++ b/api/tests/integration_tests/controllers/console/app/test_workflow_draft_variable.py @@ -0,0 +1,47 @@ +import uuid +from unittest import mock + +from controllers.console.app import workflow_draft_variable as draft_variable_api +from controllers.console.app import wraps +from factories.variable_factory import build_segment +from models import App, AppMode +from models.workflow import WorkflowDraftVariable +from services.workflow_draft_variable_service import WorkflowDraftVariableList, WorkflowDraftVariableService + + +def _get_mock_srv_class() -> type[WorkflowDraftVariableService]: + return mock.create_autospec(WorkflowDraftVariableService) + + +class TestWorkflowDraftNodeVariableListApi: + def test_get(self, test_client, auth_header, monkeypatch): + srv_class = _get_mock_srv_class() + mock_app_model: App = App() + mock_app_model.id = str(uuid.uuid4()) + test_node_id = "test_node_id" + mock_app_model.mode = AppMode.ADVANCED_CHAT + mock_load_app_model = mock.Mock(return_value=mock_app_model) + + monkeypatch.setattr(draft_variable_api, "WorkflowDraftVariableService", srv_class) + monkeypatch.setattr(wraps, "_load_app_model", mock_load_app_model) + + var1 = WorkflowDraftVariable.new_node_variable( + app_id="test_app_1", + node_id="test_node_1", + name="str_var", + value=build_segment("str_value"), + node_execution_id=str(uuid.uuid4()), + ) + srv_instance = mock.create_autospec(WorkflowDraftVariableService, instance=True) + srv_class.return_value = srv_instance + srv_instance.list_node_variables.return_value = WorkflowDraftVariableList(variables=[var1]) + + response = test_client.get( + f"/console/api/apps/{mock_app_model.id}/workflows/draft/nodes/{test_node_id}/variables", + headers=auth_header, + ) + assert response.status_code == 200 + response_dict = response.json + assert isinstance(response_dict, dict) + assert "items" in response_dict + assert len(response_dict["items"]) == 1 diff --git a/api/tests/integration_tests/controllers/test_controllers.py b/api/tests/integration_tests/controllers/test_controllers.py deleted file mode 100644 index 276ad3a7ed..0000000000 --- a/api/tests/integration_tests/controllers/test_controllers.py +++ /dev/null @@ -1,9 +0,0 @@ -from unittest.mock import patch - -from app_fixture import mock_user # type: ignore - - -def test_post_requires_login(app): - with app.test_client() as client, patch("flask_login.utils._get_user", mock_user): - response = client.get("/console/api/data-source/integrates") - assert response.status_code == 200 diff --git a/api/tests/integration_tests/factories/__init__.py b/api/tests/integration_tests/factories/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/tests/integration_tests/factories/test_storage_key_loader.py b/api/tests/integration_tests/factories/test_storage_key_loader.py new file mode 100644 index 0000000000..fecb3f6d95 --- /dev/null +++ b/api/tests/integration_tests/factories/test_storage_key_loader.py @@ -0,0 +1,371 @@ +import unittest +from datetime import UTC, datetime +from typing import Optional +from unittest.mock import patch +from uuid import uuid4 + +import pytest +from sqlalchemy.orm import Session + +from core.file import File, FileTransferMethod, FileType +from extensions.ext_database import db +from factories.file_factory import StorageKeyLoader +from models import ToolFile, UploadFile +from models.enums import CreatorUserRole + + +@pytest.mark.usefixtures("flask_req_ctx") +class TestStorageKeyLoader(unittest.TestCase): + """ + Integration tests for StorageKeyLoader class. + + Tests the batched loading of storage keys from the database for files + with different transfer methods: LOCAL_FILE, REMOTE_URL, and TOOL_FILE. + """ + + def setUp(self): + """Set up test data before each test method.""" + self.session = db.session() + self.tenant_id = str(uuid4()) + self.user_id = str(uuid4()) + self.conversation_id = str(uuid4()) + + # Create test data that will be cleaned up after each test + self.test_upload_files = [] + self.test_tool_files = [] + + # Create StorageKeyLoader instance + self.loader = StorageKeyLoader(self.session, self.tenant_id) + + def tearDown(self): + """Clean up test data after each test method.""" + self.session.rollback() + + def _create_upload_file( + self, file_id: Optional[str] = None, storage_key: Optional[str] = None, tenant_id: Optional[str] = None + ) -> UploadFile: + """Helper method to create an UploadFile record for testing.""" + if file_id is None: + file_id = str(uuid4()) + if storage_key is None: + storage_key = f"test_storage_key_{uuid4()}" + if tenant_id is None: + tenant_id = self.tenant_id + + upload_file = UploadFile( + tenant_id=tenant_id, + storage_type="local", + key=storage_key, + name="test_file.txt", + size=1024, + extension=".txt", + mime_type="text/plain", + created_by_role=CreatorUserRole.ACCOUNT, + created_by=self.user_id, + created_at=datetime.now(UTC), + used=False, + ) + upload_file.id = file_id + + self.session.add(upload_file) + self.session.flush() + self.test_upload_files.append(upload_file) + + return upload_file + + def _create_tool_file( + self, file_id: Optional[str] = None, file_key: Optional[str] = None, tenant_id: Optional[str] = None + ) -> ToolFile: + """Helper method to create a ToolFile record for testing.""" + if file_id is None: + file_id = str(uuid4()) + if file_key is None: + file_key = f"test_file_key_{uuid4()}" + if tenant_id is None: + tenant_id = self.tenant_id + + tool_file = ToolFile() + tool_file.id = file_id + tool_file.user_id = self.user_id + tool_file.tenant_id = tenant_id + tool_file.conversation_id = self.conversation_id + tool_file.file_key = file_key + tool_file.mimetype = "text/plain" + tool_file.original_url = "http://example.com/file.txt" + tool_file.name = "test_tool_file.txt" + tool_file.size = 2048 + + self.session.add(tool_file) + self.session.flush() + self.test_tool_files.append(tool_file) + + return tool_file + + def _create_file( + self, related_id: str, transfer_method: FileTransferMethod, tenant_id: Optional[str] = None + ) -> File: + """Helper method to create a File object for testing.""" + if tenant_id is None: + tenant_id = self.tenant_id + + # Set related_id for LOCAL_FILE and TOOL_FILE transfer methods + file_related_id = None + remote_url = None + + if transfer_method in (FileTransferMethod.LOCAL_FILE, FileTransferMethod.TOOL_FILE): + file_related_id = related_id + elif transfer_method == FileTransferMethod.REMOTE_URL: + remote_url = "https://example.com/test_file.txt" + file_related_id = related_id + + return File( + id=str(uuid4()), # Generate new UUID for File.id + tenant_id=tenant_id, + type=FileType.DOCUMENT, + transfer_method=transfer_method, + related_id=file_related_id, + remote_url=remote_url, + filename="test_file.txt", + extension=".txt", + mime_type="text/plain", + size=1024, + storage_key="initial_key", + ) + + def test_load_storage_keys_local_file(self): + """Test loading storage keys for LOCAL_FILE transfer method.""" + # Create test data + upload_file = self._create_upload_file() + file = self._create_file(related_id=upload_file.id, transfer_method=FileTransferMethod.LOCAL_FILE) + + # Load storage keys + self.loader.load_storage_keys([file]) + + # Verify storage key was loaded correctly + assert file._storage_key == upload_file.key + + def test_load_storage_keys_remote_url(self): + """Test loading storage keys for REMOTE_URL transfer method.""" + # Create test data + upload_file = self._create_upload_file() + file = self._create_file(related_id=upload_file.id, transfer_method=FileTransferMethod.REMOTE_URL) + + # Load storage keys + self.loader.load_storage_keys([file]) + + # Verify storage key was loaded correctly + assert file._storage_key == upload_file.key + + def test_load_storage_keys_tool_file(self): + """Test loading storage keys for TOOL_FILE transfer method.""" + # Create test data + tool_file = self._create_tool_file() + file = self._create_file(related_id=tool_file.id, transfer_method=FileTransferMethod.TOOL_FILE) + + # Load storage keys + self.loader.load_storage_keys([file]) + + # Verify storage key was loaded correctly + assert file._storage_key == tool_file.file_key + + def test_load_storage_keys_mixed_methods(self): + """Test batch loading with mixed transfer methods.""" + # Create test data for different transfer methods + upload_file1 = self._create_upload_file() + upload_file2 = self._create_upload_file() + tool_file = self._create_tool_file() + + file1 = self._create_file(related_id=upload_file1.id, transfer_method=FileTransferMethod.LOCAL_FILE) + file2 = self._create_file(related_id=upload_file2.id, transfer_method=FileTransferMethod.REMOTE_URL) + file3 = self._create_file(related_id=tool_file.id, transfer_method=FileTransferMethod.TOOL_FILE) + + files = [file1, file2, file3] + + # Load storage keys + self.loader.load_storage_keys(files) + + # Verify all storage keys were loaded correctly + assert file1._storage_key == upload_file1.key + assert file2._storage_key == upload_file2.key + assert file3._storage_key == tool_file.file_key + + def test_load_storage_keys_empty_list(self): + """Test with empty file list.""" + # Should not raise any exceptions + self.loader.load_storage_keys([]) + + def test_load_storage_keys_tenant_mismatch(self): + """Test tenant_id validation.""" + # Create file with different tenant_id + upload_file = self._create_upload_file() + file = self._create_file( + related_id=upload_file.id, transfer_method=FileTransferMethod.LOCAL_FILE, tenant_id=str(uuid4()) + ) + + # Should raise ValueError for tenant mismatch + with pytest.raises(ValueError) as context: + self.loader.load_storage_keys([file]) + + assert "invalid file, expected tenant_id" in str(context.value) + + def test_load_storage_keys_missing_file_id(self): + """Test with None file.related_id.""" + # Create a file with valid parameters first, then manually set related_id to None + file = self._create_file(related_id=str(uuid4()), transfer_method=FileTransferMethod.LOCAL_FILE) + file.related_id = None + + # Should raise ValueError for None file related_id + with pytest.raises(ValueError) as context: + self.loader.load_storage_keys([file]) + + assert str(context.value) == "file id should not be None." + + def test_load_storage_keys_nonexistent_upload_file_records(self): + """Test with missing UploadFile database records.""" + # Create file with non-existent upload file id + non_existent_id = str(uuid4()) + file = self._create_file(related_id=non_existent_id, transfer_method=FileTransferMethod.LOCAL_FILE) + + # Should raise ValueError for missing record + with pytest.raises(ValueError): + self.loader.load_storage_keys([file]) + + def test_load_storage_keys_nonexistent_tool_file_records(self): + """Test with missing ToolFile database records.""" + # Create file with non-existent tool file id + non_existent_id = str(uuid4()) + file = self._create_file(related_id=non_existent_id, transfer_method=FileTransferMethod.TOOL_FILE) + + # Should raise ValueError for missing record + with pytest.raises(ValueError): + self.loader.load_storage_keys([file]) + + def test_load_storage_keys_invalid_uuid(self): + """Test with invalid UUID format.""" + # Create a file with valid parameters first, then manually set invalid related_id + file = self._create_file(related_id=str(uuid4()), transfer_method=FileTransferMethod.LOCAL_FILE) + file.related_id = "invalid-uuid-format" + + # Should raise ValueError for invalid UUID + with pytest.raises(ValueError): + self.loader.load_storage_keys([file]) + + def test_load_storage_keys_batch_efficiency(self): + """Test batched operations use efficient queries.""" + # Create multiple files of different types + upload_files = [self._create_upload_file() for _ in range(3)] + tool_files = [self._create_tool_file() for _ in range(2)] + + files = [] + files.extend( + [self._create_file(related_id=uf.id, transfer_method=FileTransferMethod.LOCAL_FILE) for uf in upload_files] + ) + files.extend( + [self._create_file(related_id=tf.id, transfer_method=FileTransferMethod.TOOL_FILE) for tf in tool_files] + ) + + # Mock the session to count queries + with patch.object(self.session, "scalars", wraps=self.session.scalars) as mock_scalars: + self.loader.load_storage_keys(files) + + # Should make exactly 2 queries (one for upload_files, one for tool_files) + assert mock_scalars.call_count == 2 + + # Verify all storage keys were loaded correctly + for i, file in enumerate(files[:3]): + assert file._storage_key == upload_files[i].key + for i, file in enumerate(files[3:]): + assert file._storage_key == tool_files[i].file_key + + def test_load_storage_keys_tenant_isolation(self): + """Test that tenant isolation works correctly.""" + # Create files for different tenants + other_tenant_id = str(uuid4()) + + # Create upload file for current tenant + upload_file_current = self._create_upload_file() + file_current = self._create_file( + related_id=upload_file_current.id, transfer_method=FileTransferMethod.LOCAL_FILE + ) + + # Create upload file for other tenant (but don't add to cleanup list) + upload_file_other = UploadFile( + tenant_id=other_tenant_id, + storage_type="local", + key="other_tenant_key", + name="other_file.txt", + size=1024, + extension=".txt", + mime_type="text/plain", + created_by_role=CreatorUserRole.ACCOUNT, + created_by=self.user_id, + created_at=datetime.now(UTC), + used=False, + ) + upload_file_other.id = str(uuid4()) + self.session.add(upload_file_other) + self.session.flush() + + # Create file for other tenant but try to load with current tenant's loader + file_other = self._create_file( + related_id=upload_file_other.id, transfer_method=FileTransferMethod.LOCAL_FILE, tenant_id=other_tenant_id + ) + + # Should raise ValueError due to tenant mismatch + with pytest.raises(ValueError) as context: + self.loader.load_storage_keys([file_other]) + + assert "invalid file, expected tenant_id" in str(context.value) + + # Current tenant's file should still work + self.loader.load_storage_keys([file_current]) + assert file_current._storage_key == upload_file_current.key + + def test_load_storage_keys_mixed_tenant_batch(self): + """Test batch with mixed tenant files (should fail on first mismatch).""" + # Create files for current tenant + upload_file_current = self._create_upload_file() + file_current = self._create_file( + related_id=upload_file_current.id, transfer_method=FileTransferMethod.LOCAL_FILE + ) + + # Create file for different tenant + other_tenant_id = str(uuid4()) + file_other = self._create_file( + related_id=str(uuid4()), transfer_method=FileTransferMethod.LOCAL_FILE, tenant_id=other_tenant_id + ) + + # Should raise ValueError on tenant mismatch + with pytest.raises(ValueError) as context: + self.loader.load_storage_keys([file_current, file_other]) + + assert "invalid file, expected tenant_id" in str(context.value) + + def test_load_storage_keys_duplicate_file_ids(self): + """Test handling of duplicate file IDs in the batch.""" + # Create upload file + upload_file = self._create_upload_file() + + # Create two File objects with same related_id + file1 = self._create_file(related_id=upload_file.id, transfer_method=FileTransferMethod.LOCAL_FILE) + file2 = self._create_file(related_id=upload_file.id, transfer_method=FileTransferMethod.LOCAL_FILE) + + # Should handle duplicates gracefully + self.loader.load_storage_keys([file1, file2]) + + # Both files should have the same storage key + assert file1._storage_key == upload_file.key + assert file2._storage_key == upload_file.key + + def test_load_storage_keys_session_isolation(self): + """Test that the loader uses the provided session correctly.""" + # Create test data + upload_file = self._create_upload_file() + file = self._create_file(related_id=upload_file.id, transfer_method=FileTransferMethod.LOCAL_FILE) + + # Create loader with different session (same underlying connection) + + with Session(bind=db.engine) as other_session: + other_loader = StorageKeyLoader(other_session, self.tenant_id) + with pytest.raises(ValueError): + other_loader.load_storage_keys([file]) diff --git a/api/tests/integration_tests/services/__init__.py b/api/tests/integration_tests/services/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/tests/integration_tests/services/test_workflow_draft_variable_service.py b/api/tests/integration_tests/services/test_workflow_draft_variable_service.py new file mode 100644 index 0000000000..30cd2e60cb --- /dev/null +++ b/api/tests/integration_tests/services/test_workflow_draft_variable_service.py @@ -0,0 +1,501 @@ +import json +import unittest +import uuid + +import pytest +from sqlalchemy.orm import Session + +from core.variables.variables import StringVariable +from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID +from core.workflow.nodes import NodeType +from factories.variable_factory import build_segment +from libs import datetime_utils +from models import db +from models.workflow import Workflow, WorkflowDraftVariable, WorkflowNodeExecutionModel +from services.workflow_draft_variable_service import DraftVarLoader, VariableResetError, WorkflowDraftVariableService + + +@pytest.mark.usefixtures("flask_req_ctx") +class TestWorkflowDraftVariableService(unittest.TestCase): + _test_app_id: str + _session: Session + _node1_id = "test_node_1" + _node2_id = "test_node_2" + _node_exec_id = str(uuid.uuid4()) + + def setUp(self): + self._test_app_id = str(uuid.uuid4()) + self._session: Session = db.session() + sys_var = WorkflowDraftVariable.new_sys_variable( + app_id=self._test_app_id, + name="sys_var", + value=build_segment("sys_value"), + node_execution_id=self._node_exec_id, + ) + conv_var = WorkflowDraftVariable.new_conversation_variable( + app_id=self._test_app_id, + name="conv_var", + value=build_segment("conv_value"), + ) + node2_vars = [ + WorkflowDraftVariable.new_node_variable( + app_id=self._test_app_id, + node_id=self._node2_id, + name="int_var", + value=build_segment(1), + visible=False, + node_execution_id=self._node_exec_id, + ), + WorkflowDraftVariable.new_node_variable( + app_id=self._test_app_id, + node_id=self._node2_id, + name="str_var", + value=build_segment("str_value"), + visible=True, + node_execution_id=self._node_exec_id, + ), + ] + node1_var = WorkflowDraftVariable.new_node_variable( + app_id=self._test_app_id, + node_id=self._node1_id, + name="str_var", + value=build_segment("str_value"), + visible=True, + node_execution_id=self._node_exec_id, + ) + _variables = list(node2_vars) + _variables.extend( + [ + node1_var, + sys_var, + conv_var, + ] + ) + + db.session.add_all(_variables) + db.session.flush() + self._variable_ids = [v.id for v in _variables] + self._node1_str_var_id = node1_var.id + self._sys_var_id = sys_var.id + self._conv_var_id = conv_var.id + self._node2_var_ids = [v.id for v in node2_vars] + + def _get_test_srv(self) -> WorkflowDraftVariableService: + return WorkflowDraftVariableService(session=self._session) + + def tearDown(self): + self._session.rollback() + + def test_list_variables(self): + srv = self._get_test_srv() + var_list = srv.list_variables_without_values(self._test_app_id, page=1, limit=2) + assert var_list.total == 5 + assert len(var_list.variables) == 2 + page1_var_ids = {v.id for v in var_list.variables} + assert page1_var_ids.issubset(self._variable_ids) + + var_list_2 = srv.list_variables_without_values(self._test_app_id, page=2, limit=2) + assert var_list_2.total is None + assert len(var_list_2.variables) == 2 + page2_var_ids = {v.id for v in var_list_2.variables} + assert page2_var_ids.isdisjoint(page1_var_ids) + assert page2_var_ids.issubset(self._variable_ids) + + def test_get_node_variable(self): + srv = self._get_test_srv() + node_var = srv.get_node_variable(self._test_app_id, self._node1_id, "str_var") + assert node_var is not None + assert node_var.id == self._node1_str_var_id + assert node_var.name == "str_var" + assert node_var.get_value() == build_segment("str_value") + + def test_get_system_variable(self): + srv = self._get_test_srv() + sys_var = srv.get_system_variable(self._test_app_id, "sys_var") + assert sys_var is not None + assert sys_var.id == self._sys_var_id + assert sys_var.name == "sys_var" + assert sys_var.get_value() == build_segment("sys_value") + + def test_get_conversation_variable(self): + srv = self._get_test_srv() + conv_var = srv.get_conversation_variable(self._test_app_id, "conv_var") + assert conv_var is not None + assert conv_var.id == self._conv_var_id + assert conv_var.name == "conv_var" + assert conv_var.get_value() == build_segment("conv_value") + + def test_delete_node_variables(self): + srv = self._get_test_srv() + srv.delete_node_variables(self._test_app_id, self._node2_id) + node2_var_count = ( + self._session.query(WorkflowDraftVariable) + .where( + WorkflowDraftVariable.app_id == self._test_app_id, + WorkflowDraftVariable.node_id == self._node2_id, + ) + .count() + ) + assert node2_var_count == 0 + + def test_delete_variable(self): + srv = self._get_test_srv() + node_1_var = ( + self._session.query(WorkflowDraftVariable).where(WorkflowDraftVariable.id == self._node1_str_var_id).one() + ) + srv.delete_variable(node_1_var) + exists = bool( + self._session.query(WorkflowDraftVariable).where(WorkflowDraftVariable.id == self._node1_str_var_id).first() + ) + assert exists is False + + def test__list_node_variables(self): + srv = self._get_test_srv() + node_vars = srv._list_node_variables(self._test_app_id, self._node2_id) + assert len(node_vars.variables) == 2 + assert {v.id for v in node_vars.variables} == set(self._node2_var_ids) + + def test_get_draft_variables_by_selectors(self): + srv = self._get_test_srv() + selectors = [ + [self._node1_id, "str_var"], + [self._node2_id, "str_var"], + [self._node2_id, "int_var"], + ] + variables = srv.get_draft_variables_by_selectors(self._test_app_id, selectors) + assert len(variables) == 3 + assert {v.id for v in variables} == {self._node1_str_var_id} | set(self._node2_var_ids) + + +@pytest.mark.usefixtures("flask_req_ctx") +class TestDraftVariableLoader(unittest.TestCase): + _test_app_id: str + _test_tenant_id: str + + _node1_id = "test_loader_node_1" + _node_exec_id = str(uuid.uuid4()) + + def setUp(self): + self._test_app_id = str(uuid.uuid4()) + self._test_tenant_id = str(uuid.uuid4()) + sys_var = WorkflowDraftVariable.new_sys_variable( + app_id=self._test_app_id, + name="sys_var", + value=build_segment("sys_value"), + node_execution_id=self._node_exec_id, + ) + conv_var = WorkflowDraftVariable.new_conversation_variable( + app_id=self._test_app_id, + name="conv_var", + value=build_segment("conv_value"), + ) + node_var = WorkflowDraftVariable.new_node_variable( + app_id=self._test_app_id, + node_id=self._node1_id, + name="str_var", + value=build_segment("str_value"), + visible=True, + node_execution_id=self._node_exec_id, + ) + _variables = [ + node_var, + sys_var, + conv_var, + ] + + with Session(bind=db.engine, expire_on_commit=False) as session: + session.add_all(_variables) + session.flush() + session.commit() + self._variable_ids = [v.id for v in _variables] + self._node_var_id = node_var.id + self._sys_var_id = sys_var.id + self._conv_var_id = conv_var.id + + def tearDown(self): + with Session(bind=db.engine, expire_on_commit=False) as session: + session.query(WorkflowDraftVariable).filter(WorkflowDraftVariable.app_id == self._test_app_id).delete( + synchronize_session=False + ) + session.commit() + + def test_variable_loader_with_empty_selector(self): + var_loader = DraftVarLoader(engine=db.engine, app_id=self._test_app_id, tenant_id=self._test_tenant_id) + variables = var_loader.load_variables([]) + assert len(variables) == 0 + + def test_variable_loader_with_non_empty_selector(self): + var_loader = DraftVarLoader(engine=db.engine, app_id=self._test_app_id, tenant_id=self._test_tenant_id) + variables = var_loader.load_variables( + [ + [SYSTEM_VARIABLE_NODE_ID, "sys_var"], + [CONVERSATION_VARIABLE_NODE_ID, "conv_var"], + [self._node1_id, "str_var"], + ] + ) + assert len(variables) == 3 + conv_var = next(v for v in variables if v.selector[0] == CONVERSATION_VARIABLE_NODE_ID) + assert conv_var.id == self._conv_var_id + sys_var = next(v for v in variables if v.selector[0] == SYSTEM_VARIABLE_NODE_ID) + assert sys_var.id == self._sys_var_id + node1_var = next(v for v in variables if v.selector[0] == self._node1_id) + assert node1_var.id == self._node_var_id + + +@pytest.mark.usefixtures("flask_req_ctx") +class TestWorkflowDraftVariableServiceResetVariable(unittest.TestCase): + """Integration tests for reset_variable functionality using real database""" + + _test_app_id: str + _test_tenant_id: str + _test_workflow_id: str + _session: Session + _node_id = "test_reset_node" + _node_exec_id: str + _workflow_node_exec_id: str + + def setUp(self): + self._test_app_id = str(uuid.uuid4()) + self._test_tenant_id = str(uuid.uuid4()) + self._test_workflow_id = str(uuid.uuid4()) + self._node_exec_id = str(uuid.uuid4()) + self._workflow_node_exec_id = str(uuid.uuid4()) + self._session: Session = db.session() + + # Create a workflow node execution record with outputs + # Note: The WorkflowNodeExecutionModel.id should match the node_execution_id in WorkflowDraftVariable + self._workflow_node_execution = WorkflowNodeExecutionModel( + id=self._node_exec_id, # This should match the node_execution_id in the variable + tenant_id=self._test_tenant_id, + app_id=self._test_app_id, + workflow_id=self._test_workflow_id, + triggered_from="workflow-run", + workflow_run_id=str(uuid.uuid4()), + index=1, + node_execution_id=self._node_exec_id, + node_id=self._node_id, + node_type=NodeType.LLM.value, + title="Test Node", + inputs='{"input": "test input"}', + process_data='{"test_var": "process_value", "other_var": "other_process"}', + outputs='{"test_var": "output_value", "other_var": "other_output"}', + status="succeeded", + elapsed_time=1.5, + created_by_role="account", + created_by=str(uuid.uuid4()), + ) + + # Create conversation variables for the workflow + self._conv_variables = [ + StringVariable( + id=str(uuid.uuid4()), + name="conv_var_1", + description="Test conversation variable 1", + value="default_value_1", + ), + StringVariable( + id=str(uuid.uuid4()), + name="conv_var_2", + description="Test conversation variable 2", + value="default_value_2", + ), + ] + + # Create test variables + self._node_var_with_exec = WorkflowDraftVariable.new_node_variable( + app_id=self._test_app_id, + node_id=self._node_id, + name="test_var", + value=build_segment("old_value"), + node_execution_id=self._node_exec_id, + ) + self._node_var_with_exec.last_edited_at = datetime_utils.naive_utc_now() + + self._node_var_without_exec = WorkflowDraftVariable.new_node_variable( + app_id=self._test_app_id, + node_id=self._node_id, + name="no_exec_var", + value=build_segment("some_value"), + node_execution_id="temp_exec_id", + ) + # Manually set node_execution_id to None after creation + self._node_var_without_exec.node_execution_id = None + + self._node_var_missing_exec = WorkflowDraftVariable.new_node_variable( + app_id=self._test_app_id, + node_id=self._node_id, + name="missing_exec_var", + value=build_segment("some_value"), + node_execution_id=str(uuid.uuid4()), # Use a valid UUID that doesn't exist in database + ) + + self._conv_var = WorkflowDraftVariable.new_conversation_variable( + app_id=self._test_app_id, + name="conv_var_1", + value=build_segment("old_conv_value"), + ) + self._conv_var.last_edited_at = datetime_utils.naive_utc_now() + + # Add all to database + db.session.add_all( + [ + self._workflow_node_execution, + self._node_var_with_exec, + self._node_var_without_exec, + self._node_var_missing_exec, + self._conv_var, + ] + ) + db.session.flush() + + # Store IDs for assertions + self._node_var_with_exec_id = self._node_var_with_exec.id + self._node_var_without_exec_id = self._node_var_without_exec.id + self._node_var_missing_exec_id = self._node_var_missing_exec.id + self._conv_var_id = self._conv_var.id + + def _get_test_srv(self) -> WorkflowDraftVariableService: + return WorkflowDraftVariableService(session=self._session) + + def _create_mock_workflow(self) -> Workflow: + """Create a real workflow with conversation variables and graph""" + conversation_vars = self._conv_variables + + # Create a simple graph with the test node + graph = { + "nodes": [{"id": "test_reset_node", "type": "llm", "title": "Test Node", "data": {"type": "llm"}}], + "edges": [], + } + + workflow = Workflow.new( + tenant_id=str(uuid.uuid4()), + app_id=self._test_app_id, + type="workflow", + version="1.0", + graph=json.dumps(graph), + features="{}", + created_by=str(uuid.uuid4()), + environment_variables=[], + conversation_variables=conversation_vars, + ) + return workflow + + def tearDown(self): + self._session.rollback() + + def test_reset_node_variable_with_valid_execution_record(self): + """Test resetting a node variable with valid execution record - should restore from execution""" + srv = self._get_test_srv() + mock_workflow = self._create_mock_workflow() + + # Get the variable before reset + variable = srv.get_variable(self._node_var_with_exec_id) + assert variable is not None + assert variable.get_value().value == "old_value" + assert variable.last_edited_at is not None + + # Reset the variable + result = srv.reset_variable(mock_workflow, variable) + + # Should return the updated variable + assert result is not None + assert result.id == self._node_var_with_exec_id + assert result.node_execution_id == self._workflow_node_execution.id + assert result.last_edited_at is None # Should be reset to None + + # The returned variable should have the updated value from execution record + assert result.get_value().value == "output_value" + + # Verify the variable was updated in database + updated_variable = srv.get_variable(self._node_var_with_exec_id) + assert updated_variable is not None + # The value should be updated from the execution record's outputs + assert updated_variable.get_value().value == "output_value" + assert updated_variable.last_edited_at is None + assert updated_variable.node_execution_id == self._workflow_node_execution.id + + def test_reset_node_variable_with_no_execution_id(self): + """Test resetting a node variable with no execution ID - should delete variable""" + srv = self._get_test_srv() + mock_workflow = self._create_mock_workflow() + + # Get the variable before reset + variable = srv.get_variable(self._node_var_without_exec_id) + assert variable is not None + + # Reset the variable + result = srv.reset_variable(mock_workflow, variable) + + # Should return None (variable deleted) + assert result is None + + # Verify the variable was deleted + deleted_variable = srv.get_variable(self._node_var_without_exec_id) + assert deleted_variable is None + + def test_reset_node_variable_with_missing_execution_record(self): + """Test resetting a node variable when execution record doesn't exist""" + srv = self._get_test_srv() + mock_workflow = self._create_mock_workflow() + + # Get the variable before reset + variable = srv.get_variable(self._node_var_missing_exec_id) + assert variable is not None + + # Reset the variable + result = srv.reset_variable(mock_workflow, variable) + + # Should return None (variable deleted) + assert result is None + + # Verify the variable was deleted + deleted_variable = srv.get_variable(self._node_var_missing_exec_id) + assert deleted_variable is None + + def test_reset_conversation_variable(self): + """Test resetting a conversation variable""" + srv = self._get_test_srv() + mock_workflow = self._create_mock_workflow() + + # Get the variable before reset + variable = srv.get_variable(self._conv_var_id) + assert variable is not None + assert variable.get_value().value == "old_conv_value" + assert variable.last_edited_at is not None + + # Reset the variable + result = srv.reset_variable(mock_workflow, variable) + + # Should return the updated variable + assert result is not None + assert result.id == self._conv_var_id + assert result.last_edited_at is None # Should be reset to None + + # Verify the variable was updated with default value from workflow + updated_variable = srv.get_variable(self._conv_var_id) + assert updated_variable is not None + # The value should be updated from the workflow's conversation variable default + assert updated_variable.get_value().value == "default_value_1" + assert updated_variable.last_edited_at is None + + def test_reset_system_variable_raises_error(self): + """Test that resetting a system variable raises an error""" + srv = self._get_test_srv() + mock_workflow = self._create_mock_workflow() + + # Create a system variable + sys_var = WorkflowDraftVariable.new_sys_variable( + app_id=self._test_app_id, + name="sys_var", + value=build_segment("sys_value"), + node_execution_id=self._node_exec_id, + ) + db.session.add(sys_var) + db.session.flush() + + # Attempt to reset the system variable + with pytest.raises(VariableResetError) as exc_info: + srv.reset_variable(mock_workflow, sys_var) + + assert "cannot reset system variable" in str(exc_info.value) + assert sys_var.id in str(exc_info.value) diff --git a/api/tests/integration_tests/vdb/matrixone/__init__.py b/api/tests/integration_tests/vdb/matrixone/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/tests/integration_tests/vdb/matrixone/test_matrixone.py b/api/tests/integration_tests/vdb/matrixone/test_matrixone.py new file mode 100644 index 0000000000..c8b19ef3ad --- /dev/null +++ b/api/tests/integration_tests/vdb/matrixone/test_matrixone.py @@ -0,0 +1,25 @@ +from core.rag.datasource.vdb.matrixone.matrixone_vector import MatrixoneConfig, MatrixoneVector +from tests.integration_tests.vdb.test_vector_store import ( + AbstractVectorTest, + get_example_text, + setup_mock_redis, +) + + +class MatrixoneVectorTest(AbstractVectorTest): + def __init__(self): + super().__init__() + self.vector = MatrixoneVector( + collection_name=self.collection_name, + config=MatrixoneConfig( + host="localhost", port=6001, user="dump", password="111", database="dify", metric="l2" + ), + ) + + def get_ids_by_metadata_field(self): + ids = self.vector.get_ids_by_metadata_field(key="document_id", value=self.example_doc_id) + assert len(ids) == 1 + + +def test_matrixone_vector(setup_mock_redis): + MatrixoneVectorTest().run_all_tests() diff --git a/api/tests/integration_tests/workflow/nodes/test_llm.py b/api/tests/integration_tests/workflow/nodes/test_llm.py index 6aa48b1cbb..389d1071f3 100644 --- a/api/tests/integration_tests/workflow/nodes/test_llm.py +++ b/api/tests/integration_tests/workflow/nodes/test_llm.py @@ -8,9 +8,8 @@ from unittest.mock import MagicMock, patch import pytest -from app_factory import create_app -from configs import dify_config from core.app.entities.app_invoke_entities import InvokeFrom +from core.llm_generator.output_parser.structured_output import _parse_structured_output from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage from core.model_runtime.entities.message_entities import AssistantPromptMessage from core.workflow.entities.variable_pool import VariablePool @@ -30,21 +29,6 @@ from tests.integration_tests.model_runtime.__mock.plugin_daemon import setup_mod from tests.integration_tests.workflow.nodes.__mock.code_executor import setup_code_executor_mock -@pytest.fixture(scope="session") -def app(): - # Set up storage configuration - os.environ["STORAGE_TYPE"] = "opendal" - os.environ["OPENDAL_SCHEME"] = "fs" - os.environ["OPENDAL_FS_ROOT"] = "storage" - - # Ensure storage directory exists - os.makedirs("storage", exist_ok=True) - - app = create_app() - dify_config.LOGIN_DISABLED = True - return app - - def init_llm_node(config: dict) -> LLMNode: graph_config = { "edges": [ @@ -102,200 +86,101 @@ def init_llm_node(config: dict) -> LLMNode: return node -def test_execute_llm(app): - with app.app_context(): - node = init_llm_node( - config={ - "id": "llm", - "data": { - "title": "123", - "type": "llm", - "model": { - "provider": "langgenius/openai/openai", - "name": "gpt-3.5-turbo", - "mode": "chat", - "completion_params": {}, - }, - "prompt_template": [ - { - "role": "system", - "text": "you are a helpful assistant.\ntoday's weather is {{#abc.output#}}.", - }, - {"role": "user", "text": "{{#sys.query#}}"}, - ], - "memory": None, - "context": {"enabled": False}, - "vision": {"enabled": False}, +def test_execute_llm(flask_req_ctx): + node = init_llm_node( + config={ + "id": "llm", + "data": { + "title": "123", + "type": "llm", + "model": { + "provider": "langgenius/openai/openai", + "name": "gpt-3.5-turbo", + "mode": "chat", + "completion_params": {}, }, + "prompt_template": [ + { + "role": "system", + "text": "you are a helpful assistant.\ntoday's weather is {{#abc.output#}}.", + }, + {"role": "user", "text": "{{#sys.query#}}"}, + ], + "memory": None, + "context": {"enabled": False}, + "vision": {"enabled": False}, }, - ) - - credentials = {"openai_api_key": os.environ.get("OPENAI_API_KEY")} - - # Create a proper LLM result with real entities - mock_usage = LLMUsage( - prompt_tokens=30, - prompt_unit_price=Decimal("0.001"), - prompt_price_unit=Decimal("1000"), - prompt_price=Decimal("0.00003"), - completion_tokens=20, - completion_unit_price=Decimal("0.002"), - completion_price_unit=Decimal("1000"), - completion_price=Decimal("0.00004"), - total_tokens=50, - total_price=Decimal("0.00007"), - currency="USD", - latency=0.5, - ) - - mock_message = AssistantPromptMessage(content="This is a test response from the mocked LLM.") - - mock_llm_result = LLMResult( - model="gpt-3.5-turbo", - prompt_messages=[], - message=mock_message, - usage=mock_usage, - ) - - # Create a simple mock model instance that doesn't call real providers - mock_model_instance = MagicMock() - mock_model_instance.invoke_llm.return_value = mock_llm_result - - # Create a simple mock model config with required attributes - mock_model_config = MagicMock() - mock_model_config.mode = "chat" - mock_model_config.provider = "langgenius/openai/openai" - mock_model_config.model = "gpt-3.5-turbo" - mock_model_config.provider_model_bundle.configuration.tenant_id = "9d2074fc-6f86-45a9-b09d-6ecc63b9056b" - - # Mock the _fetch_model_config method - def mock_fetch_model_config_func(_node_data_model): - return mock_model_instance, mock_model_config - - # Also mock ModelManager.get_model_instance to avoid database calls - def mock_get_model_instance(_self, **kwargs): - return mock_model_instance - - with ( - patch.object(node, "_fetch_model_config", mock_fetch_model_config_func), - patch("core.model_manager.ModelManager.get_model_instance", mock_get_model_instance), - ): - # execute node - result = node._run() - assert isinstance(result, Generator) - - for item in result: - if isinstance(item, RunCompletedEvent): - assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert item.run_result.process_data is not None - assert item.run_result.outputs is not None - assert item.run_result.outputs.get("text") is not None - assert item.run_result.outputs.get("usage", {})["total_tokens"] > 0 + }, + ) + + credentials = {"openai_api_key": os.environ.get("OPENAI_API_KEY")} + + # Create a proper LLM result with real entities + mock_usage = LLMUsage( + prompt_tokens=30, + prompt_unit_price=Decimal("0.001"), + prompt_price_unit=Decimal("1000"), + prompt_price=Decimal("0.00003"), + completion_tokens=20, + completion_unit_price=Decimal("0.002"), + completion_price_unit=Decimal("1000"), + completion_price=Decimal("0.00004"), + total_tokens=50, + total_price=Decimal("0.00007"), + currency="USD", + latency=0.5, + ) + + mock_message = AssistantPromptMessage(content="This is a test response from the mocked LLM.") + + mock_llm_result = LLMResult( + model="gpt-3.5-turbo", + prompt_messages=[], + message=mock_message, + usage=mock_usage, + ) + + # Create a simple mock model instance that doesn't call real providers + mock_model_instance = MagicMock() + mock_model_instance.invoke_llm.return_value = mock_llm_result + + # Create a simple mock model config with required attributes + mock_model_config = MagicMock() + mock_model_config.mode = "chat" + mock_model_config.provider = "langgenius/openai/openai" + mock_model_config.model = "gpt-3.5-turbo" + mock_model_config.provider_model_bundle.configuration.tenant_id = "9d2074fc-6f86-45a9-b09d-6ecc63b9056b" + + # Mock the _fetch_model_config method + def mock_fetch_model_config_func(_node_data_model): + return mock_model_instance, mock_model_config + + # Also mock ModelManager.get_model_instance to avoid database calls + def mock_get_model_instance(_self, **kwargs): + return mock_model_instance + + with ( + patch.object(node, "_fetch_model_config", mock_fetch_model_config_func), + patch("core.model_manager.ModelManager.get_model_instance", mock_get_model_instance), + ): + # execute node + result = node._run() + assert isinstance(result, Generator) + + for item in result: + if isinstance(item, RunCompletedEvent): + assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED + assert item.run_result.process_data is not None + assert item.run_result.outputs is not None + assert item.run_result.outputs.get("text") is not None + assert item.run_result.outputs.get("usage", {})["total_tokens"] > 0 @pytest.mark.parametrize("setup_code_executor_mock", [["none"]], indirect=True) -def test_execute_llm_with_jinja2(app, setup_code_executor_mock): +def test_execute_llm_with_jinja2(flask_req_ctx, setup_code_executor_mock): """ Test execute LLM node with jinja2 """ - with app.app_context(): - node = init_llm_node( - config={ - "id": "llm", - "data": { - "title": "123", - "type": "llm", - "model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}}, - "prompt_config": { - "jinja2_variables": [ - {"variable": "sys_query", "value_selector": ["sys", "query"]}, - {"variable": "output", "value_selector": ["abc", "output"]}, - ] - }, - "prompt_template": [ - { - "role": "system", - "text": "you are a helpful assistant.\ntoday's weather is {{#abc.output#}}", - "jinja2_text": "you are a helpful assistant.\ntoday's weather is {{output}}.", - "edition_type": "jinja2", - }, - { - "role": "user", - "text": "{{#sys.query#}}", - "jinja2_text": "{{sys_query}}", - "edition_type": "basic", - }, - ], - "memory": None, - "context": {"enabled": False}, - "vision": {"enabled": False}, - }, - }, - ) - - # Mock db.session.close() - db.session.close = MagicMock() - - # Create a proper LLM result with real entities - mock_usage = LLMUsage( - prompt_tokens=30, - prompt_unit_price=Decimal("0.001"), - prompt_price_unit=Decimal("1000"), - prompt_price=Decimal("0.00003"), - completion_tokens=20, - completion_unit_price=Decimal("0.002"), - completion_price_unit=Decimal("1000"), - completion_price=Decimal("0.00004"), - total_tokens=50, - total_price=Decimal("0.00007"), - currency="USD", - latency=0.5, - ) - - mock_message = AssistantPromptMessage(content="Test response: sunny weather and what's the weather today?") - - mock_llm_result = LLMResult( - model="gpt-3.5-turbo", - prompt_messages=[], - message=mock_message, - usage=mock_usage, - ) - - # Create a simple mock model instance that doesn't call real providers - mock_model_instance = MagicMock() - mock_model_instance.invoke_llm.return_value = mock_llm_result - - # Create a simple mock model config with required attributes - mock_model_config = MagicMock() - mock_model_config.mode = "chat" - mock_model_config.provider = "openai" - mock_model_config.model = "gpt-3.5-turbo" - mock_model_config.provider_model_bundle.configuration.tenant_id = "9d2074fc-6f86-45a9-b09d-6ecc63b9056b" - - # Mock the _fetch_model_config method - def mock_fetch_model_config_func(_node_data_model): - return mock_model_instance, mock_model_config - - # Also mock ModelManager.get_model_instance to avoid database calls - def mock_get_model_instance(_self, **kwargs): - return mock_model_instance - - with ( - patch.object(node, "_fetch_model_config", mock_fetch_model_config_func), - patch("core.model_manager.ModelManager.get_model_instance", mock_get_model_instance), - ): - # execute node - result = node._run() - - for item in result: - if isinstance(item, RunCompletedEvent): - assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert item.run_result.process_data is not None - assert "sunny" in json.dumps(item.run_result.process_data) - assert "what's the weather today?" in json.dumps(item.run_result.process_data) - - -def test_extract_json(): node = init_llm_node( config={ "id": "llm", @@ -304,21 +189,95 @@ def test_extract_json(): "type": "llm", "model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}}, "prompt_config": { - "structured_output": { - "enabled": True, - "schema": { - "type": "object", - "properties": {"name": {"type": "string"}, "age": {"type": "number"}}, - }, - } + "jinja2_variables": [ + {"variable": "sys_query", "value_selector": ["sys", "query"]}, + {"variable": "output", "value_selector": ["abc", "output"]}, + ] }, - "prompt_template": [{"role": "user", "text": "{{#sys.query#}}"}], + "prompt_template": [ + { + "role": "system", + "text": "you are a helpful assistant.\ntoday's weather is {{#abc.output#}}", + "jinja2_text": "you are a helpful assistant.\ntoday's weather is {{output}}.", + "edition_type": "jinja2", + }, + { + "role": "user", + "text": "{{#sys.query#}}", + "jinja2_text": "{{sys_query}}", + "edition_type": "basic", + }, + ], "memory": None, "context": {"enabled": False}, "vision": {"enabled": False}, }, }, ) + + # Mock db.session.close() + db.session.close = MagicMock() + + # Create a proper LLM result with real entities + mock_usage = LLMUsage( + prompt_tokens=30, + prompt_unit_price=Decimal("0.001"), + prompt_price_unit=Decimal("1000"), + prompt_price=Decimal("0.00003"), + completion_tokens=20, + completion_unit_price=Decimal("0.002"), + completion_price_unit=Decimal("1000"), + completion_price=Decimal("0.00004"), + total_tokens=50, + total_price=Decimal("0.00007"), + currency="USD", + latency=0.5, + ) + + mock_message = AssistantPromptMessage(content="Test response: sunny weather and what's the weather today?") + + mock_llm_result = LLMResult( + model="gpt-3.5-turbo", + prompt_messages=[], + message=mock_message, + usage=mock_usage, + ) + + # Create a simple mock model instance that doesn't call real providers + mock_model_instance = MagicMock() + mock_model_instance.invoke_llm.return_value = mock_llm_result + + # Create a simple mock model config with required attributes + mock_model_config = MagicMock() + mock_model_config.mode = "chat" + mock_model_config.provider = "openai" + mock_model_config.model = "gpt-3.5-turbo" + mock_model_config.provider_model_bundle.configuration.tenant_id = "9d2074fc-6f86-45a9-b09d-6ecc63b9056b" + + # Mock the _fetch_model_config method + def mock_fetch_model_config_func(_node_data_model): + return mock_model_instance, mock_model_config + + # Also mock ModelManager.get_model_instance to avoid database calls + def mock_get_model_instance(_self, **kwargs): + return mock_model_instance + + with ( + patch.object(node, "_fetch_model_config", mock_fetch_model_config_func), + patch("core.model_manager.ModelManager.get_model_instance", mock_get_model_instance), + ): + # execute node + result = node._run() + + for item in result: + if isinstance(item, RunCompletedEvent): + assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED + assert item.run_result.process_data is not None + assert "sunny" in json.dumps(item.run_result.process_data) + assert "what's the weather today?" in json.dumps(item.run_result.process_data) + + +def test_extract_json(): llm_texts = [ '\n\n{"name": "test", "age": 123', # resoning model (deepseek-r1) '{"name":"test","age":123}', # json schema model (gpt-4o) @@ -327,4 +286,4 @@ def test_extract_json(): '{"name":"test",age:123}', # without quotes (qwen-2.5-0.5b) ] result = {"name": "test", "age": 123} - assert all(node._parse_structured_output(item) == result for item in llm_texts) + assert all(_parse_structured_output(item) == result for item in llm_texts) diff --git a/api/tests/unit_tests/configs/test_dify_config.py b/api/tests/unit_tests/configs/test_dify_config.py index cac0a688cd..b70c8830ed 100644 --- a/api/tests/unit_tests/configs/test_dify_config.py +++ b/api/tests/unit_tests/configs/test_dify_config.py @@ -1,6 +1,7 @@ import os from flask import Flask +from packaging.version import Version from yarl import URL from configs.app_config import DifyConfig @@ -40,6 +41,9 @@ def test_dify_config(monkeypatch): assert config.WORKFLOW_PARALLEL_DEPTH_LIMIT == 3 + # values from pyproject.toml + assert Version(config.project.version) >= Version("1.0.0") + # NOTE: If there is a `.env` file in your Workspace, this test might not succeed as expected. # This is due to `pymilvus` loading all the variables from the `.env` file into `os.environ`. diff --git a/api/tests/unit_tests/conftest.py b/api/tests/unit_tests/conftest.py index e09acc4c39..077ffe3408 100644 --- a/api/tests/unit_tests/conftest.py +++ b/api/tests/unit_tests/conftest.py @@ -1,4 +1,5 @@ import os +from unittest.mock import MagicMock, patch import pytest from flask import Flask @@ -11,6 +12,24 @@ PROJECT_DIR = os.path.abspath(os.path.join(ABS_PATH, os.pardir, os.pardir)) CACHED_APP = Flask(__name__) +# set global mock for Redis client +redis_mock = MagicMock() +redis_mock.get = MagicMock(return_value=None) +redis_mock.setex = MagicMock() +redis_mock.setnx = MagicMock() +redis_mock.delete = MagicMock() +redis_mock.lock = MagicMock() +redis_mock.exists = MagicMock(return_value=False) +redis_mock.set = MagicMock() +redis_mock.expire = MagicMock() +redis_mock.hgetall = MagicMock(return_value={}) +redis_mock.hdel = MagicMock() +redis_mock.incr = MagicMock(return_value=1) + +# apply the mock to the Redis client in the Flask app +redis_patcher = patch("extensions.ext_redis.redis_client", redis_mock) +redis_patcher.start() + @pytest.fixture def app() -> Flask: @@ -21,3 +40,19 @@ def app() -> Flask: def _provide_app_context(app: Flask): with app.app_context(): yield + + +@pytest.fixture(autouse=True) +def reset_redis_mock(): + """reset the Redis mock before each test""" + redis_mock.reset_mock() + redis_mock.get.return_value = None + redis_mock.setex.return_value = None + redis_mock.setnx.return_value = None + redis_mock.delete.return_value = None + redis_mock.exists.return_value = False + redis_mock.set.return_value = None + redis_mock.expire.return_value = None + redis_mock.hgetall.return_value = {} + redis_mock.hdel.return_value = None + redis_mock.incr.return_value = 1 diff --git a/api/tests/unit_tests/controllers/console/app/workflow_draft_variables_test.py b/api/tests/unit_tests/controllers/console/app/workflow_draft_variables_test.py new file mode 100644 index 0000000000..f26be6702a --- /dev/null +++ b/api/tests/unit_tests/controllers/console/app/workflow_draft_variables_test.py @@ -0,0 +1,302 @@ +import datetime +import uuid +from collections import OrderedDict +from typing import Any, NamedTuple + +from flask_restful import marshal + +from controllers.console.app.workflow_draft_variable import ( + _WORKFLOW_DRAFT_VARIABLE_FIELDS, + _WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS, + _WORKFLOW_DRAFT_VARIABLE_LIST_WITHOUT_VALUE_FIELDS, + _WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS, +) +from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID +from factories.variable_factory import build_segment +from models.workflow import WorkflowDraftVariable +from services.workflow_draft_variable_service import WorkflowDraftVariableList + +_TEST_APP_ID = "test_app_id" +_TEST_NODE_EXEC_ID = str(uuid.uuid4()) + + +class TestWorkflowDraftVariableFields: + def test_conversation_variable(self): + conv_var = WorkflowDraftVariable.new_conversation_variable( + app_id=_TEST_APP_ID, name="conv_var", value=build_segment(1) + ) + + conv_var.id = str(uuid.uuid4()) + conv_var.visible = True + + expected_without_value: OrderedDict[str, Any] = OrderedDict( + { + "id": str(conv_var.id), + "type": conv_var.get_variable_type().value, + "name": "conv_var", + "description": "", + "selector": [CONVERSATION_VARIABLE_NODE_ID, "conv_var"], + "value_type": "number", + "edited": False, + "visible": True, + } + ) + + assert marshal(conv_var, _WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS) == expected_without_value + expected_with_value = expected_without_value.copy() + expected_with_value["value"] = 1 + assert marshal(conv_var, _WORKFLOW_DRAFT_VARIABLE_FIELDS) == expected_with_value + + def test_create_sys_variable(self): + sys_var = WorkflowDraftVariable.new_sys_variable( + app_id=_TEST_APP_ID, + name="sys_var", + value=build_segment("a"), + editable=True, + node_execution_id=_TEST_NODE_EXEC_ID, + ) + + sys_var.id = str(uuid.uuid4()) + sys_var.last_edited_at = datetime.datetime.now(datetime.UTC).replace(tzinfo=None) + sys_var.visible = True + + expected_without_value = OrderedDict( + { + "id": str(sys_var.id), + "type": sys_var.get_variable_type().value, + "name": "sys_var", + "description": "", + "selector": [SYSTEM_VARIABLE_NODE_ID, "sys_var"], + "value_type": "string", + "edited": True, + "visible": True, + } + ) + assert marshal(sys_var, _WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS) == expected_without_value + expected_with_value = expected_without_value.copy() + expected_with_value["value"] = "a" + assert marshal(sys_var, _WORKFLOW_DRAFT_VARIABLE_FIELDS) == expected_with_value + + def test_node_variable(self): + node_var = WorkflowDraftVariable.new_node_variable( + app_id=_TEST_APP_ID, + node_id="test_node", + name="node_var", + value=build_segment([1, "a"]), + visible=False, + node_execution_id=_TEST_NODE_EXEC_ID, + ) + + node_var.id = str(uuid.uuid4()) + node_var.last_edited_at = datetime.datetime.now(datetime.UTC).replace(tzinfo=None) + + expected_without_value: OrderedDict[str, Any] = OrderedDict( + { + "id": str(node_var.id), + "type": node_var.get_variable_type().value, + "name": "node_var", + "description": "", + "selector": ["test_node", "node_var"], + "value_type": "array[any]", + "edited": True, + "visible": False, + } + ) + + assert marshal(node_var, _WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS) == expected_without_value + expected_with_value = expected_without_value.copy() + expected_with_value["value"] = [1, "a"] + assert marshal(node_var, _WORKFLOW_DRAFT_VARIABLE_FIELDS) == expected_with_value + + +class TestWorkflowDraftVariableList: + def test_workflow_draft_variable_list(self): + class TestCase(NamedTuple): + name: str + var_list: WorkflowDraftVariableList + expected: dict + + node_var = WorkflowDraftVariable.new_node_variable( + app_id=_TEST_APP_ID, + node_id="test_node", + name="test_var", + value=build_segment("a"), + visible=True, + node_execution_id=_TEST_NODE_EXEC_ID, + ) + node_var.id = str(uuid.uuid4()) + node_var_dict = OrderedDict( + { + "id": str(node_var.id), + "type": node_var.get_variable_type().value, + "name": "test_var", + "description": "", + "selector": ["test_node", "test_var"], + "value_type": "string", + "edited": False, + "visible": True, + } + ) + + cases = [ + TestCase( + name="empty variable list", + var_list=WorkflowDraftVariableList(variables=[]), + expected=OrderedDict( + { + "items": [], + "total": None, + } + ), + ), + TestCase( + name="empty variable list with total", + var_list=WorkflowDraftVariableList(variables=[], total=10), + expected=OrderedDict( + { + "items": [], + "total": 10, + } + ), + ), + TestCase( + name="non-empty variable list", + var_list=WorkflowDraftVariableList(variables=[node_var], total=None), + expected=OrderedDict( + { + "items": [node_var_dict], + "total": None, + } + ), + ), + TestCase( + name="non-empty variable list with total", + var_list=WorkflowDraftVariableList(variables=[node_var], total=10), + expected=OrderedDict( + { + "items": [node_var_dict], + "total": 10, + } + ), + ), + ] + + for idx, case in enumerate(cases, 1): + assert marshal(case.var_list, _WORKFLOW_DRAFT_VARIABLE_LIST_WITHOUT_VALUE_FIELDS) == case.expected, ( + f"Test case {idx} failed, {case.name=}" + ) + + +def test_workflow_node_variables_fields(): + conv_var = WorkflowDraftVariable.new_conversation_variable( + app_id=_TEST_APP_ID, name="conv_var", value=build_segment(1) + ) + resp = marshal(WorkflowDraftVariableList(variables=[conv_var]), _WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS) + assert isinstance(resp, dict) + assert len(resp["items"]) == 1 + item_dict = resp["items"][0] + assert item_dict["name"] == "conv_var" + assert item_dict["value"] == 1 + + +def test_workflow_file_variable_with_signed_url(): + """Test that File type variables include signed URLs in API responses.""" + from core.file.enums import FileTransferMethod, FileType + from core.file.models import File + + # Create a File object with LOCAL_FILE transfer method (which generates signed URLs) + test_file = File( + id="test_file_id", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.LOCAL_FILE, + related_id="test_upload_file_id", + filename="test.jpg", + extension=".jpg", + mime_type="image/jpeg", + size=12345, + ) + + # Create a WorkflowDraftVariable with the File + file_var = WorkflowDraftVariable.new_node_variable( + app_id=_TEST_APP_ID, + node_id="test_node", + name="file_var", + value=build_segment(test_file), + node_execution_id=_TEST_NODE_EXEC_ID, + ) + + # Marshal the variable using the API fields + resp = marshal(WorkflowDraftVariableList(variables=[file_var]), _WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS) + + # Verify the response structure + assert isinstance(resp, dict) + assert len(resp["items"]) == 1 + item_dict = resp["items"][0] + assert item_dict["name"] == "file_var" + + # Verify the value is a dict (File.to_dict() result) and contains expected fields + value = item_dict["value"] + assert isinstance(value, dict) + + # Verify the File fields are preserved + assert value["id"] == test_file.id + assert value["filename"] == test_file.filename + assert value["type"] == test_file.type.value + assert value["transfer_method"] == test_file.transfer_method.value + assert value["size"] == test_file.size + + # Verify the URL is present (it should be a signed URL for LOCAL_FILE transfer method) + remote_url = value["remote_url"] + assert remote_url is not None + + assert isinstance(remote_url, str) + # For LOCAL_FILE, the URL should contain signature parameters + assert "timestamp=" in remote_url + assert "nonce=" in remote_url + assert "sign=" in remote_url + + +def test_workflow_file_variable_remote_url(): + """Test that File type variables with REMOTE_URL transfer method return the remote URL.""" + from core.file.enums import FileTransferMethod, FileType + from core.file.models import File + + # Create a File object with REMOTE_URL transfer method + test_file = File( + id="test_file_id", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://example.com/test.jpg", + filename="test.jpg", + extension=".jpg", + mime_type="image/jpeg", + size=12345, + ) + + # Create a WorkflowDraftVariable with the File + file_var = WorkflowDraftVariable.new_node_variable( + app_id=_TEST_APP_ID, + node_id="test_node", + name="file_var", + value=build_segment(test_file), + node_execution_id=_TEST_NODE_EXEC_ID, + ) + + # Marshal the variable using the API fields + resp = marshal(WorkflowDraftVariableList(variables=[file_var]), _WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS) + + # Verify the response structure + assert isinstance(resp, dict) + assert len(resp["items"]) == 1 + item_dict = resp["items"][0] + assert item_dict["name"] == "file_var" + + # Verify the value is a dict (File.to_dict() result) and contains expected fields + value = item_dict["value"] + assert isinstance(value, dict) + remote_url = value["remote_url"] + + # For REMOTE_URL, the URL should be the original remote URL + assert remote_url == test_file.remote_url diff --git a/api/tests/unit_tests/core/app/apps/common/test_workflow_response_converter.py b/api/tests/unit_tests/core/app/apps/common/test_workflow_response_converter.py new file mode 100644 index 0000000000..b88a57bfd4 --- /dev/null +++ b/api/tests/unit_tests/core/app/apps/common/test_workflow_response_converter.py @@ -0,0 +1,259 @@ +from collections.abc import Mapping, Sequence + +from core.app.apps.common.workflow_response_converter import WorkflowResponseConverter +from core.file import FILE_MODEL_IDENTITY, File, FileTransferMethod, FileType +from core.variables.segments import ArrayFileSegment, FileSegment + + +class TestWorkflowResponseConverterFetchFilesFromVariableValue: + """Test class for WorkflowResponseConverter._fetch_files_from_variable_value method""" + + def create_test_file(self, file_id: str = "test_file_1") -> File: + """Create a test File object""" + return File( + id=file_id, + tenant_id="test_tenant", + type=FileType.DOCUMENT, + transfer_method=FileTransferMethod.LOCAL_FILE, + related_id="related_123", + filename=f"{file_id}.txt", + extension=".txt", + mime_type="text/plain", + size=1024, + storage_key="storage_key_123", + ) + + def create_file_dict(self, file_id: str = "test_file_dict") -> dict: + """Create a file dictionary with correct dify_model_identity""" + return { + "dify_model_identity": FILE_MODEL_IDENTITY, + "id": file_id, + "tenant_id": "test_tenant", + "type": "document", + "transfer_method": "local_file", + "related_id": "related_456", + "filename": f"{file_id}.txt", + "extension": ".txt", + "mime_type": "text/plain", + "size": 2048, + "url": "http://example.com/file.txt", + } + + def test_fetch_files_from_variable_value_with_none(self): + """Test with None input""" + # The method signature expects Union[dict, list, Segment], but implementation handles None + # We'll test the actual behavior by passing an empty dict instead + result = WorkflowResponseConverter._fetch_files_from_variable_value(None) # type: ignore + assert result == [] + + def test_fetch_files_from_variable_value_with_empty_dict(self): + """Test with empty dictionary""" + result = WorkflowResponseConverter._fetch_files_from_variable_value({}) + assert result == [] + + def test_fetch_files_from_variable_value_with_empty_list(self): + """Test with empty list""" + result = WorkflowResponseConverter._fetch_files_from_variable_value([]) + assert result == [] + + def test_fetch_files_from_variable_value_with_file_segment(self): + """Test with valid FileSegment""" + test_file = self.create_test_file("segment_file") + file_segment = FileSegment(value=test_file) + + result = WorkflowResponseConverter._fetch_files_from_variable_value(file_segment) + + assert len(result) == 1 + assert isinstance(result[0], dict) + assert result[0]["id"] == "segment_file" + assert result[0]["dify_model_identity"] == FILE_MODEL_IDENTITY + + def test_fetch_files_from_variable_value_with_array_file_segment_single(self): + """Test with ArrayFileSegment containing single file""" + test_file = self.create_test_file("array_file_1") + array_segment = ArrayFileSegment(value=[test_file]) + + result = WorkflowResponseConverter._fetch_files_from_variable_value(array_segment) + + assert len(result) == 1 + assert isinstance(result[0], dict) + assert result[0]["id"] == "array_file_1" + + def test_fetch_files_from_variable_value_with_array_file_segment_multiple(self): + """Test with ArrayFileSegment containing multiple files""" + test_file_1 = self.create_test_file("array_file_1") + test_file_2 = self.create_test_file("array_file_2") + array_segment = ArrayFileSegment(value=[test_file_1, test_file_2]) + + result = WorkflowResponseConverter._fetch_files_from_variable_value(array_segment) + + assert len(result) == 2 + assert result[0]["id"] == "array_file_1" + assert result[1]["id"] == "array_file_2" + + def test_fetch_files_from_variable_value_with_array_file_segment_empty(self): + """Test with ArrayFileSegment containing empty array""" + array_segment = ArrayFileSegment(value=[]) + + result = WorkflowResponseConverter._fetch_files_from_variable_value(array_segment) + + assert result == [] + + def test_fetch_files_from_variable_value_with_list_of_file_dicts(self): + """Test with list containing file dictionaries""" + file_dict_1 = self.create_file_dict("list_file_1") + file_dict_2 = self.create_file_dict("list_file_2") + test_list = [file_dict_1, file_dict_2] + + result = WorkflowResponseConverter._fetch_files_from_variable_value(test_list) + + assert len(result) == 2 + assert result[0]["id"] == "list_file_1" + assert result[1]["id"] == "list_file_2" + + def test_fetch_files_from_variable_value_with_list_of_file_objects(self): + """Test with list containing File objects""" + file_obj_1 = self.create_test_file("list_obj_1") + file_obj_2 = self.create_test_file("list_obj_2") + test_list = [file_obj_1, file_obj_2] + + result = WorkflowResponseConverter._fetch_files_from_variable_value(test_list) + + assert len(result) == 2 + assert result[0]["id"] == "list_obj_1" + assert result[1]["id"] == "list_obj_2" + + def test_fetch_files_from_variable_value_with_list_mixed_valid_invalid(self): + """Test with list containing mix of valid files and invalid items""" + file_dict = self.create_file_dict("mixed_file") + invalid_dict = {"not_a_file": "value"} + test_list = [file_dict, invalid_dict, "string_item", 123] + + result = WorkflowResponseConverter._fetch_files_from_variable_value(test_list) + + assert len(result) == 1 + assert result[0]["id"] == "mixed_file" + + def test_fetch_files_from_variable_value_with_list_nested_structures(self): + """Test with list containing nested structures""" + file_dict = self.create_file_dict("nested_file") + nested_list = [file_dict, ["inner_list"]] + test_list = [nested_list, {"nested": "dict"}] + + result = WorkflowResponseConverter._fetch_files_from_variable_value(test_list) + + # Should not process nested structures in list items + assert result == [] + + def test_fetch_files_from_variable_value_with_dict_incorrect_identity(self): + """Test with dictionary having incorrect dify_model_identity""" + invalid_dict = {"dify_model_identity": "wrong_identity", "id": "invalid_file", "filename": "test.txt"} + + result = WorkflowResponseConverter._fetch_files_from_variable_value(invalid_dict) + + assert result == [] + + def test_fetch_files_from_variable_value_with_dict_missing_identity(self): + """Test with dictionary missing dify_model_identity""" + invalid_dict = {"id": "no_identity_file", "filename": "test.txt"} + + result = WorkflowResponseConverter._fetch_files_from_variable_value(invalid_dict) + + assert result == [] + + def test_fetch_files_from_variable_value_with_dict_file_object(self): + """Test with dictionary containing File object""" + file_obj = self.create_test_file("dict_obj_file") + test_dict = {"file_key": file_obj} + + result = WorkflowResponseConverter._fetch_files_from_variable_value(test_dict) + + # Should not extract File objects from dict values + assert result == [] + + def test_fetch_files_from_variable_value_with_mixed_data_types(self): + """Test with various mixed data types""" + mixed_data = {"string": "text", "number": 42, "boolean": True, "null": None, "dify_model_identity": "wrong"} + + result = WorkflowResponseConverter._fetch_files_from_variable_value(mixed_data) + + assert result == [] + + def test_fetch_files_from_variable_value_with_invalid_objects(self): + """Test with invalid objects that are not supported types""" + # Test with an invalid dict that doesn't match expected patterns + invalid_dict = {"custom_key": "custom_value"} + + result = WorkflowResponseConverter._fetch_files_from_variable_value(invalid_dict) + + assert result == [] + + def test_fetch_files_from_variable_value_with_string_input(self): + """Test with string input (unsupported type)""" + # Since method expects Union[dict, list, Segment], test with empty list instead + result = WorkflowResponseConverter._fetch_files_from_variable_value([]) + + assert result == [] + + def test_fetch_files_from_variable_value_with_number_input(self): + """Test with number input (unsupported type)""" + # Test with list containing numbers (should be ignored) + result = WorkflowResponseConverter._fetch_files_from_variable_value([42, "string", None]) + + assert result == [] + + def test_fetch_files_from_variable_value_return_type_is_sequence(self): + """Test that return type is Sequence[Mapping[str, Any]]""" + file_dict = self.create_file_dict("type_test_file") + + result = WorkflowResponseConverter._fetch_files_from_variable_value(file_dict) + + assert isinstance(result, Sequence) + assert len(result) == 1 + assert isinstance(result[0], Mapping) + assert all(isinstance(key, str) for key in result[0]) + + def test_fetch_files_from_variable_value_preserves_file_properties(self): + """Test that all file properties are preserved in the result""" + original_file = self.create_test_file("property_test") + file_segment = FileSegment(value=original_file) + + result = WorkflowResponseConverter._fetch_files_from_variable_value(file_segment) + + assert len(result) == 1 + file_dict = result[0] + assert file_dict["id"] == "property_test" + assert file_dict["tenant_id"] == "test_tenant" + assert file_dict["type"] == "document" + assert file_dict["transfer_method"] == "local_file" + assert file_dict["filename"] == "property_test.txt" + assert file_dict["extension"] == ".txt" + assert file_dict["mime_type"] == "text/plain" + assert file_dict["size"] == 1024 + + def test_fetch_files_from_variable_value_with_complex_nested_scenario(self): + """Test complex scenario with nested valid and invalid data""" + file_dict = self.create_file_dict("complex_file") + file_obj = self.create_test_file("complex_obj") + + # Complex nested structure + complex_data = [ + file_dict, # Valid file dict + file_obj, # Valid file object + { # Invalid dict + "not_file": "data", + "nested": {"deep": "value"}, + }, + [ # Nested list (should be ignored) + self.create_file_dict("nested_file") + ], + "string", # Invalid string + None, # None value + 42, # Invalid number + ] + + result = WorkflowResponseConverter._fetch_files_from_variable_value(complex_data) + + assert len(result) == 2 + assert result[0]["id"] == "complex_file" + assert result[1]["id"] == "complex_obj" diff --git a/api/tests/unit_tests/core/app/segments/test_factory.py b/api/tests/unit_tests/core/app/segments/test_factory.py deleted file mode 100644 index e6e289c12a..0000000000 --- a/api/tests/unit_tests/core/app/segments/test_factory.py +++ /dev/null @@ -1,165 +0,0 @@ -from uuid import uuid4 - -import pytest - -from core.variables import ( - ArrayNumberVariable, - ArrayObjectVariable, - ArrayStringVariable, - FloatVariable, - IntegerVariable, - ObjectSegment, - SecretVariable, - StringVariable, -) -from core.variables.exc import VariableError -from core.variables.segments import ArrayAnySegment -from factories import variable_factory - - -def test_string_variable(): - test_data = {"value_type": "string", "name": "test_text", "value": "Hello, World!"} - result = variable_factory.build_conversation_variable_from_mapping(test_data) - assert isinstance(result, StringVariable) - - -def test_integer_variable(): - test_data = {"value_type": "number", "name": "test_int", "value": 42} - result = variable_factory.build_conversation_variable_from_mapping(test_data) - assert isinstance(result, IntegerVariable) - - -def test_float_variable(): - test_data = {"value_type": "number", "name": "test_float", "value": 3.14} - result = variable_factory.build_conversation_variable_from_mapping(test_data) - assert isinstance(result, FloatVariable) - - -def test_secret_variable(): - test_data = {"value_type": "secret", "name": "test_secret", "value": "secret_value"} - result = variable_factory.build_conversation_variable_from_mapping(test_data) - assert isinstance(result, SecretVariable) - - -def test_invalid_value_type(): - test_data = {"value_type": "unknown", "name": "test_invalid", "value": "value"} - with pytest.raises(VariableError): - variable_factory.build_conversation_variable_from_mapping(test_data) - - -def test_build_a_blank_string(): - result = variable_factory.build_conversation_variable_from_mapping( - { - "value_type": "string", - "name": "blank", - "value": "", - } - ) - assert isinstance(result, StringVariable) - assert result.value == "" - - -def test_build_a_object_variable_with_none_value(): - var = variable_factory.build_segment( - { - "key1": None, - } - ) - assert isinstance(var, ObjectSegment) - assert var.value["key1"] is None - - -def test_object_variable(): - mapping = { - "id": str(uuid4()), - "value_type": "object", - "name": "test_object", - "description": "Description of the variable.", - "value": { - "key1": "text", - "key2": 2, - }, - } - variable = variable_factory.build_conversation_variable_from_mapping(mapping) - assert isinstance(variable, ObjectSegment) - assert isinstance(variable.value["key1"], str) - assert isinstance(variable.value["key2"], int) - - -def test_array_string_variable(): - mapping = { - "id": str(uuid4()), - "value_type": "array[string]", - "name": "test_array", - "description": "Description of the variable.", - "value": [ - "text", - "text", - ], - } - variable = variable_factory.build_conversation_variable_from_mapping(mapping) - assert isinstance(variable, ArrayStringVariable) - assert isinstance(variable.value[0], str) - assert isinstance(variable.value[1], str) - - -def test_array_number_variable(): - mapping = { - "id": str(uuid4()), - "value_type": "array[number]", - "name": "test_array", - "description": "Description of the variable.", - "value": [ - 1, - 2.0, - ], - } - variable = variable_factory.build_conversation_variable_from_mapping(mapping) - assert isinstance(variable, ArrayNumberVariable) - assert isinstance(variable.value[0], int) - assert isinstance(variable.value[1], float) - - -def test_array_object_variable(): - mapping = { - "id": str(uuid4()), - "value_type": "array[object]", - "name": "test_array", - "description": "Description of the variable.", - "value": [ - { - "key1": "text", - "key2": 1, - }, - { - "key1": "text", - "key2": 1, - }, - ], - } - variable = variable_factory.build_conversation_variable_from_mapping(mapping) - assert isinstance(variable, ArrayObjectVariable) - assert isinstance(variable.value[0], dict) - assert isinstance(variable.value[1], dict) - assert isinstance(variable.value[0]["key1"], str) - assert isinstance(variable.value[0]["key2"], int) - assert isinstance(variable.value[1]["key1"], str) - assert isinstance(variable.value[1]["key2"], int) - - -def test_variable_cannot_large_than_200_kb(): - with pytest.raises(VariableError): - variable_factory.build_conversation_variable_from_mapping( - { - "id": str(uuid4()), - "value_type": "string", - "name": "test_text", - "value": "a" * 1024 * 201, - } - ) - - -def test_array_none_variable(): - var = variable_factory.build_segment([None, None, None, None]) - assert isinstance(var, ArrayAnySegment) - assert var.value == [None, None, None, None] diff --git a/api/tests/unit_tests/core/file/test_models.py b/api/tests/unit_tests/core/file/test_models.py new file mode 100644 index 0000000000..3ada2087c6 --- /dev/null +++ b/api/tests/unit_tests/core/file/test_models.py @@ -0,0 +1,25 @@ +from core.file import File, FileTransferMethod, FileType + + +def test_file(): + file = File( + id="test-file", + tenant_id="test-tenant-id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.TOOL_FILE, + related_id="test-related-id", + filename="image.png", + extension=".png", + mime_type="image/png", + size=67, + storage_key="test-storage-key", + url="https://example.com/image.png", + ) + assert file.tenant_id == "test-tenant-id" + assert file.type == FileType.IMAGE + assert file.transfer_method == FileTransferMethod.TOOL_FILE + assert file.related_id == "test-related-id" + assert file.filename == "image.png" + assert file.extension == ".png" + assert file.mime_type == "image/png" + assert file.size == 67 diff --git a/api/tests/unit_tests/core/helper/test_url_signer.py b/api/tests/unit_tests/core/helper/test_url_signer.py new file mode 100644 index 0000000000..5af24777de --- /dev/null +++ b/api/tests/unit_tests/core/helper/test_url_signer.py @@ -0,0 +1,194 @@ +from unittest.mock import patch +from urllib.parse import parse_qs, urlparse + +import pytest + +from core.helper.url_signer import SignedUrlParams, UrlSigner + + +class TestUrlSigner: + """Test cases for UrlSigner class""" + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + def test_should_generate_signed_url_params(self): + """Test generation of signed URL parameters with all required fields""" + sign_key = "test-sign-key" + prefix = "test-prefix" + + params = UrlSigner.get_signed_url_params(sign_key, prefix) + + # Verify the returned object and required fields + assert isinstance(params, SignedUrlParams) + assert params.sign_key == sign_key + assert params.timestamp is not None + assert params.nonce is not None + assert params.sign is not None + + # Verify nonce format (32 character hex string) + assert len(params.nonce) == 32 + assert all(c in "0123456789abcdef" for c in params.nonce) + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + def test_should_generate_complete_signed_url(self): + """Test generation of complete signed URL with query parameters""" + base_url = "https://example.com/api/test" + sign_key = "test-sign-key" + prefix = "test-prefix" + + signed_url = UrlSigner.get_signed_url(base_url, sign_key, prefix) + + # Parse URL and verify structure + parsed = urlparse(signed_url) + assert f"{parsed.scheme}://{parsed.netloc}{parsed.path}" == base_url + + # Verify query parameters + query_params = parse_qs(parsed.query) + assert "timestamp" in query_params + assert "nonce" in query_params + assert "sign" in query_params + + # Verify each parameter has exactly one value + assert len(query_params["timestamp"]) == 1 + assert len(query_params["nonce"]) == 1 + assert len(query_params["sign"]) == 1 + + # Verify parameter values are not empty + assert query_params["timestamp"][0] + assert query_params["nonce"][0] + assert query_params["sign"][0] + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + def test_should_verify_valid_signature(self): + """Test verification of valid signature""" + sign_key = "test-sign-key" + prefix = "test-prefix" + + # Generate and verify signature + params = UrlSigner.get_signed_url_params(sign_key, prefix) + + is_valid = UrlSigner.verify( + sign_key=sign_key, timestamp=params.timestamp, nonce=params.nonce, sign=params.sign, prefix=prefix + ) + + assert is_valid is True + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + @pytest.mark.parametrize( + ("field", "modifier"), + [ + ("sign_key", lambda _: "wrong-sign-key"), + ("timestamp", lambda t: str(int(t) + 1000)), + ("nonce", lambda _: "different-nonce-123456789012345"), + ("prefix", lambda _: "wrong-prefix"), + ("sign", lambda s: s + "tampered"), + ], + ) + def test_should_reject_invalid_signature_params(self, field, modifier): + """Test signature verification rejects invalid parameters""" + sign_key = "test-sign-key" + prefix = "test-prefix" + + # Generate valid signed parameters + params = UrlSigner.get_signed_url_params(sign_key, prefix) + + # Prepare verification parameters + verify_params = { + "sign_key": sign_key, + "timestamp": params.timestamp, + "nonce": params.nonce, + "sign": params.sign, + "prefix": prefix, + } + + # Modify the specific field + verify_params[field] = modifier(verify_params[field]) + + # Verify should fail + is_valid = UrlSigner.verify(**verify_params) + assert is_valid is False + + @patch("configs.dify_config.SECRET_KEY", None) + def test_should_raise_error_without_secret_key(self): + """Test that signing fails when SECRET_KEY is not configured""" + with pytest.raises(Exception) as exc_info: + UrlSigner.get_signed_url_params("key", "prefix") + + assert "SECRET_KEY is not set" in str(exc_info.value) + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + def test_should_generate_unique_signatures(self): + """Test that different inputs produce different signatures""" + params1 = UrlSigner.get_signed_url_params("key1", "prefix1") + params2 = UrlSigner.get_signed_url_params("key2", "prefix2") + + # Different inputs should produce different signatures + assert params1.sign != params2.sign + assert params1.nonce != params2.nonce + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + def test_should_handle_special_characters(self): + """Test handling of special characters in parameters""" + special_cases = [ + "test with spaces", + "test/with/slashes", + "test中文字符", + ] + + for sign_key in special_cases: + params = UrlSigner.get_signed_url_params(sign_key, "prefix") + + # Should generate valid signature and verify correctly + is_valid = UrlSigner.verify( + sign_key=sign_key, timestamp=params.timestamp, nonce=params.nonce, sign=params.sign, prefix="prefix" + ) + assert is_valid is True + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + def test_should_ensure_nonce_randomness(self): + """Test that nonce is random for each generation - critical for security""" + sign_key = "test-sign-key" + prefix = "test-prefix" + + # Generate multiple nonces + nonces = set() + for _ in range(5): + params = UrlSigner.get_signed_url_params(sign_key, prefix) + nonces.add(params.nonce) + + # All nonces should be unique + assert len(nonces) == 5 + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + @patch("time.time", return_value=1234567890) + @patch("os.urandom", return_value=b"\xab\xcd\xef\x12\x34\x56\x78\x90\xab\xcd\xef\x12\x34\x56\x78\x90") + def test_should_produce_consistent_signatures(self, mock_urandom, mock_time): + """Test that same inputs produce same signature - ensures deterministic behavior""" + sign_key = "test-sign-key" + prefix = "test-prefix" + + # Generate signature multiple times with same inputs (time and nonce are mocked) + params1 = UrlSigner.get_signed_url_params(sign_key, prefix) + params2 = UrlSigner.get_signed_url_params(sign_key, prefix) + + # With mocked time and random, should produce identical results + assert params1.timestamp == params2.timestamp + assert params1.nonce == params2.nonce + assert params1.sign == params2.sign + + # Verify the signature is valid + assert UrlSigner.verify( + sign_key=sign_key, timestamp=params1.timestamp, nonce=params1.nonce, sign=params1.sign, prefix=prefix + ) + + @patch("configs.dify_config.SECRET_KEY", "test-secret-key-12345") + def test_should_handle_empty_strings(self): + """Test handling of empty string parameters - common edge case""" + # Empty sign_key and prefix should still work + params = UrlSigner.get_signed_url_params("", "") + assert params.sign is not None + + # Should verify correctly + is_valid = UrlSigner.verify( + sign_key="", timestamp=params.timestamp, nonce=params.nonce, sign=params.sign, prefix="" + ) + assert is_valid is True diff --git a/api/tests/unit_tests/core/ops/__init__.py b/api/tests/unit_tests/core/ops/__init__.py new file mode 100644 index 0000000000..bb92ccdec7 --- /dev/null +++ b/api/tests/unit_tests/core/ops/__init__.py @@ -0,0 +1 @@ +# Unit tests for core ops module diff --git a/api/tests/unit_tests/core/ops/test_config_entity.py b/api/tests/unit_tests/core/ops/test_config_entity.py new file mode 100644 index 0000000000..81cb04548d --- /dev/null +++ b/api/tests/unit_tests/core/ops/test_config_entity.py @@ -0,0 +1,385 @@ +import pytest +from pydantic import ValidationError + +from core.ops.entities.config_entity import ( + AliyunConfig, + ArizeConfig, + LangfuseConfig, + LangSmithConfig, + OpikConfig, + PhoenixConfig, + TracingProviderEnum, + WeaveConfig, +) + + +class TestTracingProviderEnum: + """Test cases for TracingProviderEnum""" + + def test_enum_values(self): + """Test that all expected enum values are present""" + assert TracingProviderEnum.ARIZE == "arize" + assert TracingProviderEnum.PHOENIX == "phoenix" + assert TracingProviderEnum.LANGFUSE == "langfuse" + assert TracingProviderEnum.LANGSMITH == "langsmith" + assert TracingProviderEnum.OPIK == "opik" + assert TracingProviderEnum.WEAVE == "weave" + assert TracingProviderEnum.ALIYUN == "aliyun" + + +class TestArizeConfig: + """Test cases for ArizeConfig""" + + def test_valid_config(self): + """Test valid Arize configuration""" + config = ArizeConfig( + api_key="test_key", space_id="test_space", project="test_project", endpoint="https://custom.arize.com" + ) + assert config.api_key == "test_key" + assert config.space_id == "test_space" + assert config.project == "test_project" + assert config.endpoint == "https://custom.arize.com" + + def test_default_values(self): + """Test default values are set correctly""" + config = ArizeConfig() + assert config.api_key is None + assert config.space_id is None + assert config.project is None + assert config.endpoint == "https://otlp.arize.com" + + def test_project_validation_empty(self): + """Test project validation with empty value""" + config = ArizeConfig(project="") + assert config.project == "default" + + def test_project_validation_none(self): + """Test project validation with None value""" + config = ArizeConfig(project=None) + assert config.project == "default" + + def test_endpoint_validation_empty(self): + """Test endpoint validation with empty value""" + config = ArizeConfig(endpoint="") + assert config.endpoint == "https://otlp.arize.com" + + def test_endpoint_validation_with_path(self): + """Test endpoint validation normalizes URL by removing path""" + config = ArizeConfig(endpoint="https://custom.arize.com/api/v1") + assert config.endpoint == "https://custom.arize.com" + + def test_endpoint_validation_invalid_scheme(self): + """Test endpoint validation rejects invalid schemes""" + with pytest.raises(ValidationError, match="URL scheme must be one of"): + ArizeConfig(endpoint="ftp://invalid.com") + + def test_endpoint_validation_no_scheme(self): + """Test endpoint validation rejects URLs without scheme""" + with pytest.raises(ValidationError, match="URL scheme must be one of"): + ArizeConfig(endpoint="invalid.com") + + +class TestPhoenixConfig: + """Test cases for PhoenixConfig""" + + def test_valid_config(self): + """Test valid Phoenix configuration""" + config = PhoenixConfig(api_key="test_key", project="test_project", endpoint="https://custom.phoenix.com") + assert config.api_key == "test_key" + assert config.project == "test_project" + assert config.endpoint == "https://custom.phoenix.com" + + def test_default_values(self): + """Test default values are set correctly""" + config = PhoenixConfig() + assert config.api_key is None + assert config.project is None + assert config.endpoint == "https://app.phoenix.arize.com" + + def test_project_validation_empty(self): + """Test project validation with empty value""" + config = PhoenixConfig(project="") + assert config.project == "default" + + def test_endpoint_validation_with_path(self): + """Test endpoint validation normalizes URL by removing path""" + config = PhoenixConfig(endpoint="https://custom.phoenix.com/api/v1") + assert config.endpoint == "https://custom.phoenix.com" + + +class TestLangfuseConfig: + """Test cases for LangfuseConfig""" + + def test_valid_config(self): + """Test valid Langfuse configuration""" + config = LangfuseConfig(public_key="public_key", secret_key="secret_key", host="https://custom.langfuse.com") + assert config.public_key == "public_key" + assert config.secret_key == "secret_key" + assert config.host == "https://custom.langfuse.com" + + def test_default_values(self): + """Test default values are set correctly""" + config = LangfuseConfig(public_key="public", secret_key="secret") + assert config.host == "https://api.langfuse.com" + + def test_missing_required_fields(self): + """Test that required fields are enforced""" + with pytest.raises(ValidationError): + LangfuseConfig() + + with pytest.raises(ValidationError): + LangfuseConfig(public_key="public") + + with pytest.raises(ValidationError): + LangfuseConfig(secret_key="secret") + + def test_host_validation_empty(self): + """Test host validation with empty value""" + config = LangfuseConfig(public_key="public", secret_key="secret", host="") + assert config.host == "https://api.langfuse.com" + + +class TestLangSmithConfig: + """Test cases for LangSmithConfig""" + + def test_valid_config(self): + """Test valid LangSmith configuration""" + config = LangSmithConfig(api_key="test_key", project="test_project", endpoint="https://custom.smith.com") + assert config.api_key == "test_key" + assert config.project == "test_project" + assert config.endpoint == "https://custom.smith.com" + + def test_default_values(self): + """Test default values are set correctly""" + config = LangSmithConfig(api_key="key", project="project") + assert config.endpoint == "https://api.smith.langchain.com" + + def test_missing_required_fields(self): + """Test that required fields are enforced""" + with pytest.raises(ValidationError): + LangSmithConfig() + + with pytest.raises(ValidationError): + LangSmithConfig(api_key="key") + + with pytest.raises(ValidationError): + LangSmithConfig(project="project") + + def test_endpoint_validation_https_only(self): + """Test endpoint validation only allows HTTPS""" + with pytest.raises(ValidationError, match="URL scheme must be one of"): + LangSmithConfig(api_key="key", project="project", endpoint="http://insecure.com") + + +class TestOpikConfig: + """Test cases for OpikConfig""" + + def test_valid_config(self): + """Test valid Opik configuration""" + config = OpikConfig( + api_key="test_key", + project="test_project", + workspace="test_workspace", + url="https://custom.comet.com/opik/api/", + ) + assert config.api_key == "test_key" + assert config.project == "test_project" + assert config.workspace == "test_workspace" + assert config.url == "https://custom.comet.com/opik/api/" + + def test_default_values(self): + """Test default values are set correctly""" + config = OpikConfig() + assert config.api_key is None + assert config.project is None + assert config.workspace is None + assert config.url == "https://www.comet.com/opik/api/" + + def test_project_validation_empty(self): + """Test project validation with empty value""" + config = OpikConfig(project="") + assert config.project == "Default Project" + + def test_url_validation_empty(self): + """Test URL validation with empty value""" + config = OpikConfig(url="") + assert config.url == "https://www.comet.com/opik/api/" + + def test_url_validation_missing_suffix(self): + """Test URL validation requires /api/ suffix""" + with pytest.raises(ValidationError, match="URL should end with /api/"): + OpikConfig(url="https://custom.comet.com/opik/") + + def test_url_validation_invalid_scheme(self): + """Test URL validation rejects invalid schemes""" + with pytest.raises(ValidationError, match="URL must start with https:// or http://"): + OpikConfig(url="ftp://custom.comet.com/opik/api/") + + +class TestWeaveConfig: + """Test cases for WeaveConfig""" + + def test_valid_config(self): + """Test valid Weave configuration""" + config = WeaveConfig( + api_key="test_key", + entity="test_entity", + project="test_project", + endpoint="https://custom.wandb.ai", + host="https://custom.host.com", + ) + assert config.api_key == "test_key" + assert config.entity == "test_entity" + assert config.project == "test_project" + assert config.endpoint == "https://custom.wandb.ai" + assert config.host == "https://custom.host.com" + + def test_default_values(self): + """Test default values are set correctly""" + config = WeaveConfig(api_key="key", project="project") + assert config.entity is None + assert config.endpoint == "https://trace.wandb.ai" + assert config.host is None + + def test_missing_required_fields(self): + """Test that required fields are enforced""" + with pytest.raises(ValidationError): + WeaveConfig() + + with pytest.raises(ValidationError): + WeaveConfig(api_key="key") + + with pytest.raises(ValidationError): + WeaveConfig(project="project") + + def test_endpoint_validation_https_only(self): + """Test endpoint validation only allows HTTPS""" + with pytest.raises(ValidationError, match="URL scheme must be one of"): + WeaveConfig(api_key="key", project="project", endpoint="http://insecure.wandb.ai") + + def test_host_validation_optional(self): + """Test host validation is optional but validates when provided""" + config = WeaveConfig(api_key="key", project="project", host=None) + assert config.host is None + + config = WeaveConfig(api_key="key", project="project", host="") + assert config.host == "" + + config = WeaveConfig(api_key="key", project="project", host="https://valid.host.com") + assert config.host == "https://valid.host.com" + + def test_host_validation_invalid_scheme(self): + """Test host validation rejects invalid schemes when provided""" + with pytest.raises(ValidationError, match="URL scheme must be one of"): + WeaveConfig(api_key="key", project="project", host="ftp://invalid.host.com") + + +class TestAliyunConfig: + """Test cases for AliyunConfig""" + + def test_valid_config(self): + """Test valid Aliyun configuration""" + config = AliyunConfig( + app_name="test_app", + license_key="test_license_key", + endpoint="https://custom.tracing-analysis-dc-hz.aliyuncs.com", + ) + assert config.app_name == "test_app" + assert config.license_key == "test_license_key" + assert config.endpoint == "https://custom.tracing-analysis-dc-hz.aliyuncs.com" + + def test_default_values(self): + """Test default values are set correctly""" + config = AliyunConfig(license_key="test_license", endpoint="https://tracing-analysis-dc-hz.aliyuncs.com") + assert config.app_name == "dify_app" + + def test_missing_required_fields(self): + """Test that required fields are enforced""" + with pytest.raises(ValidationError): + AliyunConfig() + + with pytest.raises(ValidationError): + AliyunConfig(license_key="test_license") + + with pytest.raises(ValidationError): + AliyunConfig(endpoint="https://tracing-analysis-dc-hz.aliyuncs.com") + + def test_app_name_validation_empty(self): + """Test app_name validation with empty value""" + config = AliyunConfig( + license_key="test_license", endpoint="https://tracing-analysis-dc-hz.aliyuncs.com", app_name="" + ) + assert config.app_name == "dify_app" + + def test_endpoint_validation_empty(self): + """Test endpoint validation with empty value""" + config = AliyunConfig(license_key="test_license", endpoint="") + assert config.endpoint == "https://tracing-analysis-dc-hz.aliyuncs.com" + + def test_endpoint_validation_with_path(self): + """Test endpoint validation normalizes URL by removing path""" + config = AliyunConfig( + license_key="test_license", endpoint="https://tracing-analysis-dc-hz.aliyuncs.com/api/v1/traces" + ) + assert config.endpoint == "https://tracing-analysis-dc-hz.aliyuncs.com" + + def test_endpoint_validation_invalid_scheme(self): + """Test endpoint validation rejects invalid schemes""" + with pytest.raises(ValidationError, match="URL scheme must be one of"): + AliyunConfig(license_key="test_license", endpoint="ftp://invalid.tracing-analysis-dc-hz.aliyuncs.com") + + def test_endpoint_validation_no_scheme(self): + """Test endpoint validation rejects URLs without scheme""" + with pytest.raises(ValidationError, match="URL scheme must be one of"): + AliyunConfig(license_key="test_license", endpoint="invalid.tracing-analysis-dc-hz.aliyuncs.com") + + def test_license_key_required(self): + """Test that license_key is required and cannot be empty""" + with pytest.raises(ValidationError): + AliyunConfig(license_key="", endpoint="https://tracing-analysis-dc-hz.aliyuncs.com") + + +class TestConfigIntegration: + """Integration tests for configuration classes""" + + def test_all_configs_can_be_instantiated(self): + """Test that all config classes can be instantiated with valid data""" + configs = [ + ArizeConfig(api_key="key"), + PhoenixConfig(api_key="key"), + LangfuseConfig(public_key="public", secret_key="secret"), + LangSmithConfig(api_key="key", project="project"), + OpikConfig(api_key="key"), + WeaveConfig(api_key="key", project="project"), + AliyunConfig(license_key="test_license", endpoint="https://tracing-analysis-dc-hz.aliyuncs.com"), + ] + + for config in configs: + assert config is not None + + def test_url_normalization_consistency(self): + """Test that URL normalization works consistently across configs""" + # Test that paths are removed from endpoints + arize_config = ArizeConfig(endpoint="https://arize.com/api/v1/test") + phoenix_config = PhoenixConfig(endpoint="https://phoenix.com/api/v2/") + aliyun_config = AliyunConfig( + license_key="test_license", endpoint="https://tracing-analysis-dc-hz.aliyuncs.com/api/v1/traces" + ) + + assert arize_config.endpoint == "https://arize.com" + assert phoenix_config.endpoint == "https://phoenix.com" + assert aliyun_config.endpoint == "https://tracing-analysis-dc-hz.aliyuncs.com" + + def test_project_default_values(self): + """Test that project default values are set correctly""" + arize_config = ArizeConfig(project="") + phoenix_config = PhoenixConfig(project="") + opik_config = OpikConfig(project="") + aliyun_config = AliyunConfig( + license_key="test_license", endpoint="https://tracing-analysis-dc-hz.aliyuncs.com", app_name="" + ) + + assert arize_config.project == "default" + assert phoenix_config.project == "default" + assert opik_config.project == "Default Project" + assert aliyun_config.app_name == "dify_app" diff --git a/api/tests/unit_tests/core/ops/test_utils.py b/api/tests/unit_tests/core/ops/test_utils.py new file mode 100644 index 0000000000..7cc2772acf --- /dev/null +++ b/api/tests/unit_tests/core/ops/test_utils.py @@ -0,0 +1,138 @@ +import pytest + +from core.ops.utils import validate_project_name, validate_url, validate_url_with_path + + +class TestValidateUrl: + """Test cases for validate_url function""" + + def test_valid_https_url(self): + """Test valid HTTPS URL""" + result = validate_url("https://example.com", "https://default.com") + assert result == "https://example.com" + + def test_valid_http_url(self): + """Test valid HTTP URL""" + result = validate_url("http://example.com", "https://default.com") + assert result == "http://example.com" + + def test_url_with_path_removed(self): + """Test that URL path is removed during normalization""" + result = validate_url("https://example.com/api/v1/test", "https://default.com") + assert result == "https://example.com" + + def test_url_with_query_removed(self): + """Test that URL query parameters are removed""" + result = validate_url("https://example.com?param=value", "https://default.com") + assert result == "https://example.com" + + def test_url_with_fragment_removed(self): + """Test that URL fragments are removed""" + result = validate_url("https://example.com#section", "https://default.com") + assert result == "https://example.com" + + def test_empty_url_returns_default(self): + """Test empty URL returns default""" + result = validate_url("", "https://default.com") + assert result == "https://default.com" + + def test_none_url_returns_default(self): + """Test None URL returns default""" + result = validate_url(None, "https://default.com") + assert result == "https://default.com" + + def test_whitespace_url_returns_default(self): + """Test whitespace URL returns default""" + result = validate_url(" ", "https://default.com") + assert result == "https://default.com" + + def test_invalid_scheme_raises_error(self): + """Test invalid scheme raises ValueError""" + with pytest.raises(ValueError, match="URL scheme must be one of"): + validate_url("ftp://example.com", "https://default.com") + + def test_no_scheme_raises_error(self): + """Test URL without scheme raises ValueError""" + with pytest.raises(ValueError, match="URL scheme must be one of"): + validate_url("example.com", "https://default.com") + + def test_custom_allowed_schemes(self): + """Test custom allowed schemes""" + result = validate_url("https://example.com", "https://default.com", allowed_schemes=("https",)) + assert result == "https://example.com" + + with pytest.raises(ValueError, match="URL scheme must be one of"): + validate_url("http://example.com", "https://default.com", allowed_schemes=("https",)) + + +class TestValidateUrlWithPath: + """Test cases for validate_url_with_path function""" + + def test_valid_url_with_path(self): + """Test valid URL with path""" + result = validate_url_with_path("https://example.com/api/v1", "https://default.com") + assert result == "https://example.com/api/v1" + + def test_valid_url_with_required_suffix(self): + """Test valid URL with required suffix""" + result = validate_url_with_path("https://example.com/api/", "https://default.com", required_suffix="/api/") + assert result == "https://example.com/api/" + + def test_url_without_required_suffix_raises_error(self): + """Test URL without required suffix raises error""" + with pytest.raises(ValueError, match="URL should end with /api/"): + validate_url_with_path("https://example.com/api", "https://default.com", required_suffix="/api/") + + def test_empty_url_returns_default(self): + """Test empty URL returns default""" + result = validate_url_with_path("", "https://default.com") + assert result == "https://default.com" + + def test_none_url_returns_default(self): + """Test None URL returns default""" + result = validate_url_with_path(None, "https://default.com") + assert result == "https://default.com" + + def test_invalid_scheme_raises_error(self): + """Test invalid scheme raises ValueError""" + with pytest.raises(ValueError, match="URL must start with https:// or http://"): + validate_url_with_path("ftp://example.com", "https://default.com") + + def test_no_scheme_raises_error(self): + """Test URL without scheme raises ValueError""" + with pytest.raises(ValueError, match="URL must start with https:// or http://"): + validate_url_with_path("example.com", "https://default.com") + + +class TestValidateProjectName: + """Test cases for validate_project_name function""" + + def test_valid_project_name(self): + """Test valid project name""" + result = validate_project_name("my-project", "default") + assert result == "my-project" + + def test_empty_project_name_returns_default(self): + """Test empty project name returns default""" + result = validate_project_name("", "default") + assert result == "default" + + def test_none_project_name_returns_default(self): + """Test None project name returns default""" + result = validate_project_name(None, "default") + assert result == "default" + + def test_whitespace_project_name_returns_default(self): + """Test whitespace project name returns default""" + result = validate_project_name(" ", "default") + assert result == "default" + + def test_project_name_with_whitespace_trimmed(self): + """Test project name with whitespace is trimmed""" + result = validate_project_name(" my-project ", "default") + assert result == "my-project" + + def test_custom_default_name(self): + """Test custom default name""" + result = validate_project_name("", "Custom Default") + assert result == "Custom Default" diff --git a/api/tests/unit_tests/core/rag/extractor/test_markdown_extractor.py b/api/tests/unit_tests/core/rag/extractor/test_markdown_extractor.py new file mode 100644 index 0000000000..d4cf534c56 --- /dev/null +++ b/api/tests/unit_tests/core/rag/extractor/test_markdown_extractor.py @@ -0,0 +1,22 @@ +from core.rag.extractor.markdown_extractor import MarkdownExtractor + + +def test_markdown_to_tups(): + markdown = """ +this is some text without header + +# title 1 +this is balabala text + +## title 2 +this is more specific text. + """ + extractor = MarkdownExtractor(file_path="dummy_path") + updated_output = extractor.markdown_to_tups(markdown) + assert len(updated_output) == 3 + key, header_value = updated_output[0] + assert key == None + assert header_value.strip() == "this is some text without header" + title_1, value = updated_output[1] + assert title_1.strip() == "title 1" + assert value.strip() == "this is balabala text" diff --git a/api/tests/unit_tests/core/app/segments/test_segment.py b/api/tests/unit_tests/core/variables/test_segment.py similarity index 100% rename from api/tests/unit_tests/core/app/segments/test_segment.py rename to api/tests/unit_tests/core/variables/test_segment.py diff --git a/api/tests/unit_tests/core/app/segments/test_variables.py b/api/tests/unit_tests/core/variables/test_variables.py similarity index 100% rename from api/tests/unit_tests/core/app/segments/test_variables.py rename to api/tests/unit_tests/core/variables/test_variables.py diff --git a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py index 7535ec4866..c288a5fa13 100644 --- a/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py +++ b/api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py @@ -1,3 +1,4 @@ +import time from unittest.mock import patch import pytest @@ -19,6 +20,7 @@ from core.workflow.graph_engine.entities.event import ( NodeRunSucceededEvent, ) from core.workflow.graph_engine.entities.graph import Graph +from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState from core.workflow.graph_engine.entities.runtime_route_state import RouteNodeState from core.workflow.graph_engine.graph_engine import GraphEngine from core.workflow.nodes.code.code_node import CodeNode @@ -172,6 +174,7 @@ def test_run_parallel_in_workflow(mock_close, mock_remove): system_variables={SystemVariableKey.FILES: [], SystemVariableKey.USER_ID: "aaa"}, user_inputs={"query": "hi"} ) + graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) graph_engine = GraphEngine( tenant_id="111", app_id="222", @@ -183,7 +186,7 @@ def test_run_parallel_in_workflow(mock_close, mock_remove): invoke_from=InvokeFrom.WEB_APP, call_depth=0, graph=graph, - variable_pool=variable_pool, + graph_runtime_state=graph_runtime_state, max_execution_steps=500, max_execution_time=1200, ) @@ -299,6 +302,7 @@ def test_run_parallel_in_chatflow(mock_close, mock_remove): user_inputs={}, ) + graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) graph_engine = GraphEngine( tenant_id="111", app_id="222", @@ -310,7 +314,7 @@ def test_run_parallel_in_chatflow(mock_close, mock_remove): invoke_from=InvokeFrom.WEB_APP, call_depth=0, graph=graph, - variable_pool=variable_pool, + graph_runtime_state=graph_runtime_state, max_execution_steps=500, max_execution_time=1200, ) @@ -479,6 +483,7 @@ def test_run_branch(mock_close, mock_remove): user_inputs={"uid": "takato"}, ) + graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) graph_engine = GraphEngine( tenant_id="111", app_id="222", @@ -490,7 +495,7 @@ def test_run_branch(mock_close, mock_remove): invoke_from=InvokeFrom.WEB_APP, call_depth=0, graph=graph, - variable_pool=variable_pool, + graph_runtime_state=graph_runtime_state, max_execution_steps=500, max_execution_time=1200, ) @@ -813,6 +818,7 @@ def test_condition_parallel_correct_output(mock_close, mock_remove, app): system_variables={SystemVariableKey.FILES: [], SystemVariableKey.USER_ID: "aaa"}, user_inputs={"query": "hi"} ) + graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) graph_engine = GraphEngine( tenant_id="111", app_id="222", @@ -824,7 +830,7 @@ def test_condition_parallel_correct_output(mock_close, mock_remove, app): invoke_from=InvokeFrom.WEB_APP, call_depth=0, graph=graph, - variable_pool=variable_pool, + graph_runtime_state=graph_runtime_state, max_execution_steps=500, max_execution_time=1200, ) diff --git a/api/tests/unit_tests/core/workflow/nodes/base/test_base_node.py b/api/tests/unit_tests/core/workflow/nodes/base/test_base_node.py new file mode 100644 index 0000000000..8712b61a23 --- /dev/null +++ b/api/tests/unit_tests/core/workflow/nodes/base/test_base_node.py @@ -0,0 +1,36 @@ +from core.workflow.nodes.base.node import BaseNode +from core.workflow.nodes.enums import NodeType + +# Ensures that all node classes are imported. +from core.workflow.nodes.node_mapping import NODE_TYPE_CLASSES_MAPPING + +_ = NODE_TYPE_CLASSES_MAPPING + + +def _get_all_subclasses(root: type[BaseNode]) -> list[type[BaseNode]]: + subclasses = [] + queue = [root] + while queue: + cls = queue.pop() + + subclasses.extend(cls.__subclasses__()) + queue.extend(cls.__subclasses__()) + + return subclasses + + +def test_ensure_subclasses_of_base_node_has_node_type_and_version_method_defined(): + classes = _get_all_subclasses(BaseNode) # type: ignore + type_version_set: set[tuple[NodeType, str]] = set() + + for cls in classes: + # Validate that 'version' is directly defined in the class (not inherited) by checking the class's __dict__ + assert "version" in cls.__dict__, f"class {cls} should have version method defined (NOT INHERITED.)" + node_type = cls._node_type + node_version = cls.version() + + assert isinstance(cls._node_type, NodeType) + assert isinstance(node_version, str) + node_type_and_version = (node_type, node_version) + assert node_type_and_version not in type_version_set + type_version_set.add(node_type_and_version) diff --git a/api/tests/unit_tests/core/workflow/nodes/iteration/test_iteration.py b/api/tests/unit_tests/core/workflow/nodes/iteration/test_iteration.py index 6d854c950d..362072a3db 100644 --- a/api/tests/unit_tests/core/workflow/nodes/iteration/test_iteration.py +++ b/api/tests/unit_tests/core/workflow/nodes/iteration/test_iteration.py @@ -3,6 +3,7 @@ import uuid from unittest.mock import patch from core.app.entities.app_invoke_entities import InvokeFrom +from core.variables.segments import ArrayAnySegment, ArrayStringSegment from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.variable_pool import VariablePool from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus @@ -197,7 +198,7 @@ def test_run(): count += 1 if isinstance(item, RunCompletedEvent): assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert item.run_result.outputs == {"output": ["dify 123", "dify 123"]} + assert item.run_result.outputs == {"output": ArrayStringSegment(value=["dify 123", "dify 123"])} assert count == 20 @@ -413,7 +414,7 @@ def test_run_parallel(): count += 1 if isinstance(item, RunCompletedEvent): assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert item.run_result.outputs == {"output": ["dify 123", "dify 123"]} + assert item.run_result.outputs == {"output": ArrayStringSegment(value=["dify 123", "dify 123"])} assert count == 32 @@ -654,7 +655,7 @@ def test_iteration_run_in_parallel_mode(): parallel_arr.append(item) if isinstance(item, RunCompletedEvent): assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert item.run_result.outputs == {"output": ["dify 123", "dify 123"]} + assert item.run_result.outputs == {"output": ArrayStringSegment(value=["dify 123", "dify 123"])} assert count == 32 for item in sequential_result: @@ -662,7 +663,7 @@ def test_iteration_run_in_parallel_mode(): count += 1 if isinstance(item, RunCompletedEvent): assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert item.run_result.outputs == {"output": ["dify 123", "dify 123"]} + assert item.run_result.outputs == {"output": ArrayStringSegment(value=["dify 123", "dify 123"])} assert count == 64 @@ -846,7 +847,7 @@ def test_iteration_run_error_handle(): count += 1 if isinstance(item, RunCompletedEvent): assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert item.run_result.outputs == {"output": [None, None]} + assert item.run_result.outputs == {"output": ArrayAnySegment(value=[None, None])} assert count == 14 # execute remove abnormal output @@ -857,5 +858,5 @@ def test_iteration_run_error_handle(): count += 1 if isinstance(item, RunCompletedEvent): assert item.run_result.status == WorkflowNodeExecutionStatus.SUCCEEDED - assert item.run_result.outputs == {"output": []} + assert item.run_result.outputs == {"output": ArrayAnySegment(value=[])} assert count == 14 diff --git a/api/tests/unit_tests/core/workflow/nodes/test_continue_on_error.py b/api/tests/unit_tests/core/workflow/nodes/test_continue_on_error.py index ff60d5974b..a6c553faf0 100644 --- a/api/tests/unit_tests/core/workflow/nodes/test_continue_on_error.py +++ b/api/tests/unit_tests/core/workflow/nodes/test_continue_on_error.py @@ -1,7 +1,9 @@ +import time from unittest.mock import patch from core.app.entities.app_invoke_entities import InvokeFrom from core.workflow.entities.node_entities import NodeRunResult, WorkflowNodeExecutionMetadataKey +from core.workflow.entities.variable_pool import VariablePool from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus from core.workflow.enums import SystemVariableKey from core.workflow.graph_engine.entities.event import ( @@ -11,6 +13,7 @@ from core.workflow.graph_engine.entities.event import ( NodeRunStreamChunkEvent, ) from core.workflow.graph_engine.entities.graph import Graph +from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState from core.workflow.graph_engine.graph_engine import GraphEngine from core.workflow.nodes.event.event import RunCompletedEvent, RunStreamChunkEvent from core.workflow.nodes.llm.node import LLMNode @@ -163,15 +166,16 @@ class ContinueOnErrorTestHelper: def create_test_graph_engine(graph_config: dict, user_inputs: dict | None = None): """Helper method to create a graph engine instance for testing""" graph = Graph.init(graph_config=graph_config) - variable_pool = { - "system_variables": { + variable_pool = VariablePool( + system_variables={ SystemVariableKey.QUERY: "clear", SystemVariableKey.FILES: [], SystemVariableKey.CONVERSATION_ID: "abababa", SystemVariableKey.USER_ID: "aaa", }, - "user_inputs": user_inputs or {"uid": "takato"}, - } + user_inputs=user_inputs or {"uid": "takato"}, + ) + graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()) return GraphEngine( tenant_id="111", @@ -184,7 +188,7 @@ class ContinueOnErrorTestHelper: invoke_from=InvokeFrom.WEB_APP, call_depth=0, graph=graph, - variable_pool=variable_pool, + graph_runtime_state=graph_runtime_state, max_execution_steps=500, max_execution_time=1200, ) diff --git a/api/tests/unit_tests/core/workflow/nodes/test_document_extractor_node.py b/api/tests/unit_tests/core/workflow/nodes/test_document_extractor_node.py index 4cb1aa93f9..66c7818adf 100644 --- a/api/tests/unit_tests/core/workflow/nodes/test_document_extractor_node.py +++ b/api/tests/unit_tests/core/workflow/nodes/test_document_extractor_node.py @@ -7,6 +7,7 @@ from docx.oxml.text.paragraph import CT_P from core.file import File, FileTransferMethod from core.variables import ArrayFileSegment +from core.variables.segments import ArrayStringSegment from core.variables.variables import StringVariable from core.workflow.entities.node_entities import NodeRunResult from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus @@ -69,7 +70,13 @@ def test_run_invalid_variable_type(document_extractor_node, mock_graph_runtime_s @pytest.mark.parametrize( ("mime_type", "file_content", "expected_text", "transfer_method", "extension"), [ - ("text/plain", b"Hello, world!", ["Hello, world!"], FileTransferMethod.LOCAL_FILE, ".txt"), + ( + "text/plain", + b"Hello, world!", + ["Hello, world!"], + FileTransferMethod.LOCAL_FILE, + ".txt", + ), ( "application/pdf", b"%PDF-1.5\n%Test PDF content", @@ -84,7 +91,13 @@ def test_run_invalid_variable_type(document_extractor_node, mock_graph_runtime_s FileTransferMethod.REMOTE_URL, "", ), - ("text/plain", b"Remote content", ["Remote content"], FileTransferMethod.REMOTE_URL, None), + ( + "text/plain", + b"Remote content", + ["Remote content"], + FileTransferMethod.REMOTE_URL, + None, + ), ], ) def test_run_extract_text( @@ -131,7 +144,7 @@ def test_run_extract_text( assert isinstance(result, NodeRunResult) assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED, result.error assert result.outputs is not None - assert result.outputs["text"] == expected_text + assert result.outputs["text"] == ArrayStringSegment(value=expected_text) if transfer_method == FileTransferMethod.REMOTE_URL: mock_ssrf_proxy_get.assert_called_once_with("https://example.com/file.txt") @@ -329,3 +342,26 @@ def test_extract_text_from_excel_all_sheets_fail(mock_excel_file): assert result == "" assert mock_excel_instance.parse.call_count == 2 + + +@patch("pandas.ExcelFile") +def test_extract_text_from_excel_numeric_type_column(mock_excel_file): + """Test extracting text from Excel file with numeric column names.""" + + # Test numeric type column + data = {1: ["Test"], 1.1: ["Test"]} + + df = pd.DataFrame(data) + + # Mock ExcelFile + mock_excel_instance = Mock() + mock_excel_instance.sheet_names = ["Sheet1"] + mock_excel_instance.parse.return_value = df + mock_excel_file.return_value = mock_excel_instance + + file_content = b"fake_excel_content" + result = _extract_text_from_excel(file_content) + + expected_manual = "| 1.0 | 1.1 |\n| --- | --- |\n| Test | Test |\n\n" + + assert expected_manual == result diff --git a/api/tests/unit_tests/core/workflow/nodes/test_list_operator.py b/api/tests/unit_tests/core/workflow/nodes/test_list_operator.py index 77d42e2692..7d3a1d6a2d 100644 --- a/api/tests/unit_tests/core/workflow/nodes/test_list_operator.py +++ b/api/tests/unit_tests/core/workflow/nodes/test_list_operator.py @@ -115,7 +115,7 @@ def test_filter_files_by_type(list_operator_node): }, ] assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED - for expected_file, result_file in zip(expected_files, result.outputs["result"]): + for expected_file, result_file in zip(expected_files, result.outputs["result"].value): assert expected_file["filename"] == result_file.filename assert expected_file["type"] == result_file.type assert expected_file["tenant_id"] == result_file.tenant_id diff --git a/api/tests/unit_tests/core/workflow/nodes/variable_assigner/v1/test_variable_assigner_v1.py b/api/tests/unit_tests/core/workflow/nodes/variable_assigner/v1/test_variable_assigner_v1.py index 9793da129d..deb3e29b86 100644 --- a/api/tests/unit_tests/core/workflow/nodes/variable_assigner/v1/test_variable_assigner_v1.py +++ b/api/tests/unit_tests/core/workflow/nodes/variable_assigner/v1/test_variable_assigner_v1.py @@ -5,6 +5,7 @@ from uuid import uuid4 from core.app.entities.app_invoke_entities import InvokeFrom from core.variables import ArrayStringVariable, StringVariable +from core.workflow.conversation_variable_updater import ConversationVariableUpdater from core.workflow.entities.variable_pool import VariablePool from core.workflow.enums import SystemVariableKey from core.workflow.graph_engine.entities.graph import Graph @@ -63,10 +64,11 @@ def test_overwrite_string_variable(): name="test_string_variable", value="the second value", ) + conversation_id = str(uuid.uuid4()) # construct variable pool variable_pool = VariablePool( - system_variables={SystemVariableKey.CONVERSATION_ID: "conversation_id"}, + system_variables={SystemVariableKey.CONVERSATION_ID: conversation_id}, user_inputs={}, environment_variables=[], conversation_variables=[conversation_variable], @@ -77,6 +79,9 @@ def test_overwrite_string_variable(): input_variable, ) + mock_conv_var_updater = mock.Mock(spec=ConversationVariableUpdater) + mock_conv_var_updater_factory = mock.Mock(return_value=mock_conv_var_updater) + node = VariableAssignerNode( id=str(uuid.uuid4()), graph_init_params=init_params, @@ -91,11 +96,20 @@ def test_overwrite_string_variable(): "input_variable_selector": [DEFAULT_NODE_ID, input_variable.name], }, }, + conv_var_updater_factory=mock_conv_var_updater_factory, ) - with mock.patch("core.workflow.nodes.variable_assigner.common.helpers.update_conversation_variable") as mock_run: - list(node.run()) - mock_run.assert_called_once() + list(node.run()) + expected_var = StringVariable( + id=conversation_variable.id, + name=conversation_variable.name, + description=conversation_variable.description, + selector=conversation_variable.selector, + value_type=conversation_variable.value_type, + value=input_variable.value, + ) + mock_conv_var_updater.update.assert_called_once_with(conversation_id=conversation_id, variable=expected_var) + mock_conv_var_updater.flush.assert_called_once() got = variable_pool.get(["conversation", conversation_variable.name]) assert got is not None @@ -148,9 +162,10 @@ def test_append_variable_to_array(): name="test_string_variable", value="the second value", ) + conversation_id = str(uuid.uuid4()) variable_pool = VariablePool( - system_variables={SystemVariableKey.CONVERSATION_ID: "conversation_id"}, + system_variables={SystemVariableKey.CONVERSATION_ID: conversation_id}, user_inputs={}, environment_variables=[], conversation_variables=[conversation_variable], @@ -160,6 +175,9 @@ def test_append_variable_to_array(): input_variable, ) + mock_conv_var_updater = mock.Mock(spec=ConversationVariableUpdater) + mock_conv_var_updater_factory = mock.Mock(return_value=mock_conv_var_updater) + node = VariableAssignerNode( id=str(uuid.uuid4()), graph_init_params=init_params, @@ -174,11 +192,22 @@ def test_append_variable_to_array(): "input_variable_selector": [DEFAULT_NODE_ID, input_variable.name], }, }, + conv_var_updater_factory=mock_conv_var_updater_factory, ) - with mock.patch("core.workflow.nodes.variable_assigner.common.helpers.update_conversation_variable") as mock_run: - list(node.run()) - mock_run.assert_called_once() + list(node.run()) + expected_value = list(conversation_variable.value) + expected_value.append(input_variable.value) + expected_var = ArrayStringVariable( + id=conversation_variable.id, + name=conversation_variable.name, + description=conversation_variable.description, + selector=conversation_variable.selector, + value_type=conversation_variable.value_type, + value=expected_value, + ) + mock_conv_var_updater.update.assert_called_once_with(conversation_id=conversation_id, variable=expected_var) + mock_conv_var_updater.flush.assert_called_once() got = variable_pool.get(["conversation", conversation_variable.name]) assert got is not None @@ -225,13 +254,17 @@ def test_clear_array(): value=["the first value"], ) + conversation_id = str(uuid.uuid4()) variable_pool = VariablePool( - system_variables={SystemVariableKey.CONVERSATION_ID: "conversation_id"}, + system_variables={SystemVariableKey.CONVERSATION_ID: conversation_id}, user_inputs={}, environment_variables=[], conversation_variables=[conversation_variable], ) + mock_conv_var_updater = mock.Mock(spec=ConversationVariableUpdater) + mock_conv_var_updater_factory = mock.Mock(return_value=mock_conv_var_updater) + node = VariableAssignerNode( id=str(uuid.uuid4()), graph_init_params=init_params, @@ -246,11 +279,20 @@ def test_clear_array(): "input_variable_selector": [], }, }, + conv_var_updater_factory=mock_conv_var_updater_factory, ) - with mock.patch("core.workflow.nodes.variable_assigner.common.helpers.update_conversation_variable") as mock_run: - list(node.run()) - mock_run.assert_called_once() + list(node.run()) + expected_var = ArrayStringVariable( + id=conversation_variable.id, + name=conversation_variable.name, + description=conversation_variable.description, + selector=conversation_variable.selector, + value_type=conversation_variable.value_type, + value=[], + ) + mock_conv_var_updater.update.assert_called_once_with(conversation_id=conversation_id, variable=expected_var) + mock_conv_var_updater.flush.assert_called_once() got = variable_pool.get(["conversation", conversation_variable.name]) assert got is not None diff --git a/api/tests/unit_tests/core/workflow/test_variable_pool.py b/api/tests/unit_tests/core/workflow/test_variable_pool.py index efbcdc760c..bb8d34fad5 100644 --- a/api/tests/unit_tests/core/workflow/test_variable_pool.py +++ b/api/tests/unit_tests/core/workflow/test_variable_pool.py @@ -1,8 +1,12 @@ import pytest +from pydantic import ValidationError from core.file import File, FileTransferMethod, FileType from core.variables import FileSegment, StringSegment +from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, ENVIRONMENT_VARIABLE_NODE_ID from core.workflow.entities.variable_pool import VariablePool +from core.workflow.enums import SystemVariableKey +from factories.variable_factory import build_segment, segment_to_variable @pytest.fixture @@ -44,3 +48,38 @@ def test_use_long_selector(pool): result = pool.get(("node_1", "part_1", "part_2")) assert result is not None assert result.value == "test_value" + + +class TestVariablePool: + def test_constructor(self): + pool = VariablePool() + pool = VariablePool( + variable_dictionary={}, + user_inputs={}, + system_variables={}, + environment_variables=[], + conversation_variables=[], + ) + + pool = VariablePool( + user_inputs={"key": "value"}, + system_variables={SystemVariableKey.WORKFLOW_ID: "test_workflow_id"}, + environment_variables=[ + segment_to_variable( + segment=build_segment(1), + selector=[ENVIRONMENT_VARIABLE_NODE_ID, "env_var_1"], + name="env_var_1", + ) + ], + conversation_variables=[ + segment_to_variable( + segment=build_segment("1"), + selector=[CONVERSATION_VARIABLE_NODE_ID, "conv_var_1"], + name="conv_var_1", + ) + ], + ) + + def test_constructor_with_invalid_system_variable_key(self): + with pytest.raises(ValidationError): + VariablePool(system_variables={"invalid_key": "value"}) # type: ignore diff --git a/api/tests/unit_tests/core/workflow/test_workflow_cycle_manager.py b/api/tests/unit_tests/core/workflow/test_workflow_cycle_manager.py index fddc182594..646de8bf3a 100644 --- a/api/tests/unit_tests/core/workflow/test_workflow_cycle_manager.py +++ b/api/tests/unit_tests/core/workflow/test_workflow_cycle_manager.py @@ -163,7 +163,6 @@ def real_workflow_run(): workflow_run.tenant_id = "test-tenant-id" workflow_run.app_id = "test-app-id" workflow_run.workflow_id = "test-workflow-id" - workflow_run.sequence_number = 1 workflow_run.type = "chat" workflow_run.triggered_from = "app-run" workflow_run.version = "1.0" diff --git a/api/tests/unit_tests/core/workflow/utils/test_variable_template_parser.py b/api/tests/unit_tests/core/workflow/utils/test_variable_template_parser.py index 2f90afcf89..28ef05edde 100644 --- a/api/tests/unit_tests/core/workflow/utils/test_variable_template_parser.py +++ b/api/tests/unit_tests/core/workflow/utils/test_variable_template_parser.py @@ -1,22 +1,10 @@ -from core.variables import SecretVariable +import dataclasses + from core.workflow.entities.variable_entities import VariableSelector -from core.workflow.entities.variable_pool import VariablePool -from core.workflow.enums import SystemVariableKey from core.workflow.utils import variable_template_parser def test_extract_selectors_from_template(): - variable_pool = VariablePool( - system_variables={ - SystemVariableKey("user_id"): "fake-user-id", - }, - user_inputs={}, - environment_variables=[ - SecretVariable(name="secret_key", value="fake-secret-key"), - ], - conversation_variables=[], - ) - variable_pool.add(("node_id", "custom_query"), "fake-user-query") template = ( "Hello, {{#sys.user_id#}}! Your query is {{#node_id.custom_query#}}. And your key is {{#env.secret_key#}}." ) @@ -26,3 +14,35 @@ def test_extract_selectors_from_template(): VariableSelector(variable="#node_id.custom_query#", value_selector=["node_id", "custom_query"]), VariableSelector(variable="#env.secret_key#", value_selector=["env", "secret_key"]), ] + + +def test_invalid_references(): + @dataclasses.dataclass + class TestCase: + name: str + template: str + + cases = [ + TestCase( + name="lack of closing brace", + template="Hello, {{#sys.user_id#", + ), + TestCase( + name="lack of opening brace", + template="Hello, #sys.user_id#}}", + ), + TestCase( + name="lack selector name", + template="Hello, {{#sys#}}", + ), + TestCase( + name="empty node name part", + template="Hello, {{#.user_id#}}", + ), + ] + for idx, c in enumerate(cases, 1): + fail_msg = f"Test case {c.name} failed, index={idx}" + selectors = variable_template_parser.extract_selectors_from_template(c.template) + assert selectors == [], fail_msg + parser = variable_template_parser.VariableTemplateParser(c.template) + assert parser.extract_variable_selectors() == [], fail_msg diff --git a/api/tests/unit_tests/core/workflow/utils/test_variable_utils.py b/api/tests/unit_tests/core/workflow/utils/test_variable_utils.py new file mode 100644 index 0000000000..f1cb937bb3 --- /dev/null +++ b/api/tests/unit_tests/core/workflow/utils/test_variable_utils.py @@ -0,0 +1,148 @@ +from typing import Any + +from core.variables.segments import ObjectSegment, StringSegment +from core.workflow.entities.variable_pool import VariablePool +from core.workflow.utils.variable_utils import append_variables_recursively + + +class TestAppendVariablesRecursively: + """Test cases for append_variables_recursively function""" + + def test_append_simple_dict_value(self): + """Test appending a simple dictionary value""" + pool = VariablePool() + node_id = "test_node" + variable_key_list = ["output"] + variable_value = {"name": "John", "age": 30} + + append_variables_recursively(pool, node_id, variable_key_list, variable_value) + + # Check that the main variable is added + main_var = pool.get([node_id] + variable_key_list) + assert main_var is not None + assert main_var.value == variable_value + + # Check that nested variables are added recursively + name_var = pool.get([node_id] + variable_key_list + ["name"]) + assert name_var is not None + assert name_var.value == "John" + + age_var = pool.get([node_id] + variable_key_list + ["age"]) + assert age_var is not None + assert age_var.value == 30 + + def test_append_object_segment_value(self): + """Test appending an ObjectSegment value""" + pool = VariablePool() + node_id = "test_node" + variable_key_list = ["result"] + + # Create an ObjectSegment + obj_data = {"status": "success", "code": 200} + variable_value = ObjectSegment(value=obj_data) + + append_variables_recursively(pool, node_id, variable_key_list, variable_value) + + # Check that the main variable is added + main_var = pool.get([node_id] + variable_key_list) + assert main_var is not None + assert isinstance(main_var, ObjectSegment) + assert main_var.value == obj_data + + # Check that nested variables are added recursively + status_var = pool.get([node_id] + variable_key_list + ["status"]) + assert status_var is not None + assert status_var.value == "success" + + code_var = pool.get([node_id] + variable_key_list + ["code"]) + assert code_var is not None + assert code_var.value == 200 + + def test_append_nested_dict_value(self): + """Test appending a nested dictionary value""" + pool = VariablePool() + node_id = "test_node" + variable_key_list = ["data"] + + variable_value = { + "user": { + "profile": {"name": "Alice", "email": "alice@example.com"}, + "settings": {"theme": "dark", "notifications": True}, + }, + "metadata": {"version": "1.0", "timestamp": 1234567890}, + } + + append_variables_recursively(pool, node_id, variable_key_list, variable_value) + + # Check deeply nested variables + name_var = pool.get([node_id] + variable_key_list + ["user", "profile", "name"]) + assert name_var is not None + assert name_var.value == "Alice" + + email_var = pool.get([node_id] + variable_key_list + ["user", "profile", "email"]) + assert email_var is not None + assert email_var.value == "alice@example.com" + + theme_var = pool.get([node_id] + variable_key_list + ["user", "settings", "theme"]) + assert theme_var is not None + assert theme_var.value == "dark" + + notifications_var = pool.get([node_id] + variable_key_list + ["user", "settings", "notifications"]) + assert notifications_var is not None + assert notifications_var.value == 1 # Boolean True is converted to integer 1 + + version_var = pool.get([node_id] + variable_key_list + ["metadata", "version"]) + assert version_var is not None + assert version_var.value == "1.0" + + def test_append_non_dict_value(self): + """Test appending a non-dictionary value (should not recurse)""" + pool = VariablePool() + node_id = "test_node" + variable_key_list = ["simple"] + variable_value = "simple_string" + + append_variables_recursively(pool, node_id, variable_key_list, variable_value) + + # Check that only the main variable is added + main_var = pool.get([node_id] + variable_key_list) + assert main_var is not None + assert main_var.value == variable_value + + # Ensure no additional variables are created + assert len(pool.variable_dictionary[node_id]) == 1 + + def test_append_segment_non_object_value(self): + """Test appending a Segment that is not ObjectSegment (should not recurse)""" + pool = VariablePool() + node_id = "test_node" + variable_key_list = ["text"] + variable_value = StringSegment(value="Hello World") + + append_variables_recursively(pool, node_id, variable_key_list, variable_value) + + # Check that only the main variable is added + main_var = pool.get([node_id] + variable_key_list) + assert main_var is not None + assert isinstance(main_var, StringSegment) + assert main_var.value == "Hello World" + + # Ensure no additional variables are created + assert len(pool.variable_dictionary[node_id]) == 1 + + def test_append_empty_dict_value(self): + """Test appending an empty dictionary value""" + pool = VariablePool() + node_id = "test_node" + variable_key_list = ["empty"] + variable_value: dict[str, Any] = {} + + append_variables_recursively(pool, node_id, variable_key_list, variable_value) + + # Check that the main variable is added + main_var = pool.get([node_id] + variable_key_list) + assert main_var is not None + assert main_var.value == {} + + # Ensure only the main variable is created (no recursion for empty dict) + assert len(pool.variable_dictionary[node_id]) == 1 diff --git a/api/tests/unit_tests/factories/test_variable_factory.py b/api/tests/unit_tests/factories/test_variable_factory.py new file mode 100644 index 0000000000..481fbdc91a --- /dev/null +++ b/api/tests/unit_tests/factories/test_variable_factory.py @@ -0,0 +1,865 @@ +import math +from dataclasses import dataclass +from typing import Any +from uuid import uuid4 + +import pytest +from hypothesis import given +from hypothesis import strategies as st + +from core.file import File, FileTransferMethod, FileType +from core.variables import ( + ArrayNumberVariable, + ArrayObjectVariable, + ArrayStringVariable, + FloatVariable, + IntegerVariable, + ObjectSegment, + SecretVariable, + SegmentType, + StringVariable, +) +from core.variables.exc import VariableError +from core.variables.segments import ( + ArrayAnySegment, + ArrayFileSegment, + ArrayNumberSegment, + ArrayObjectSegment, + ArrayStringSegment, + FileSegment, + FloatSegment, + IntegerSegment, + NoneSegment, + ObjectSegment, + StringSegment, +) +from core.variables.types import SegmentType +from factories import variable_factory +from factories.variable_factory import TypeMismatchError, build_segment_with_type + + +def test_string_variable(): + test_data = {"value_type": "string", "name": "test_text", "value": "Hello, World!"} + result = variable_factory.build_conversation_variable_from_mapping(test_data) + assert isinstance(result, StringVariable) + + +def test_integer_variable(): + test_data = {"value_type": "number", "name": "test_int", "value": 42} + result = variable_factory.build_conversation_variable_from_mapping(test_data) + assert isinstance(result, IntegerVariable) + + +def test_float_variable(): + test_data = {"value_type": "number", "name": "test_float", "value": 3.14} + result = variable_factory.build_conversation_variable_from_mapping(test_data) + assert isinstance(result, FloatVariable) + + +def test_secret_variable(): + test_data = {"value_type": "secret", "name": "test_secret", "value": "secret_value"} + result = variable_factory.build_conversation_variable_from_mapping(test_data) + assert isinstance(result, SecretVariable) + + +def test_invalid_value_type(): + test_data = {"value_type": "unknown", "name": "test_invalid", "value": "value"} + with pytest.raises(VariableError): + variable_factory.build_conversation_variable_from_mapping(test_data) + + +def test_build_a_blank_string(): + result = variable_factory.build_conversation_variable_from_mapping( + { + "value_type": "string", + "name": "blank", + "value": "", + } + ) + assert isinstance(result, StringVariable) + assert result.value == "" + + +def test_build_a_object_variable_with_none_value(): + var = variable_factory.build_segment( + { + "key1": None, + } + ) + assert isinstance(var, ObjectSegment) + assert var.value["key1"] is None + + +def test_object_variable(): + mapping = { + "id": str(uuid4()), + "value_type": "object", + "name": "test_object", + "description": "Description of the variable.", + "value": { + "key1": "text", + "key2": 2, + }, + } + variable = variable_factory.build_conversation_variable_from_mapping(mapping) + assert isinstance(variable, ObjectSegment) + assert isinstance(variable.value["key1"], str) + assert isinstance(variable.value["key2"], int) + + +def test_array_string_variable(): + mapping = { + "id": str(uuid4()), + "value_type": "array[string]", + "name": "test_array", + "description": "Description of the variable.", + "value": [ + "text", + "text", + ], + } + variable = variable_factory.build_conversation_variable_from_mapping(mapping) + assert isinstance(variable, ArrayStringVariable) + assert isinstance(variable.value[0], str) + assert isinstance(variable.value[1], str) + + +def test_array_number_variable(): + mapping = { + "id": str(uuid4()), + "value_type": "array[number]", + "name": "test_array", + "description": "Description of the variable.", + "value": [ + 1, + 2.0, + ], + } + variable = variable_factory.build_conversation_variable_from_mapping(mapping) + assert isinstance(variable, ArrayNumberVariable) + assert isinstance(variable.value[0], int) + assert isinstance(variable.value[1], float) + + +def test_array_object_variable(): + mapping = { + "id": str(uuid4()), + "value_type": "array[object]", + "name": "test_array", + "description": "Description of the variable.", + "value": [ + { + "key1": "text", + "key2": 1, + }, + { + "key1": "text", + "key2": 1, + }, + ], + } + variable = variable_factory.build_conversation_variable_from_mapping(mapping) + assert isinstance(variable, ArrayObjectVariable) + assert isinstance(variable.value[0], dict) + assert isinstance(variable.value[1], dict) + assert isinstance(variable.value[0]["key1"], str) + assert isinstance(variable.value[0]["key2"], int) + assert isinstance(variable.value[1]["key1"], str) + assert isinstance(variable.value[1]["key2"], int) + + +def test_variable_cannot_large_than_200_kb(): + with pytest.raises(VariableError): + variable_factory.build_conversation_variable_from_mapping( + { + "id": str(uuid4()), + "value_type": "string", + "name": "test_text", + "value": "a" * 1024 * 201, + } + ) + + +def test_array_none_variable(): + var = variable_factory.build_segment([None, None, None, None]) + assert isinstance(var, ArrayAnySegment) + assert var.value == [None, None, None, None] + + +def test_build_segment_none_type(): + """Test building NoneSegment from None value.""" + segment = variable_factory.build_segment(None) + assert isinstance(segment, NoneSegment) + assert segment.value is None + assert segment.value_type == SegmentType.NONE + + +def test_build_segment_none_type_properties(): + """Test NoneSegment properties and methods.""" + segment = variable_factory.build_segment(None) + assert segment.text == "" + assert segment.log == "" + assert segment.markdown == "" + assert segment.to_object() is None + + +def test_build_segment_array_file_single_file(): + """Test building ArrayFileSegment from list with single file.""" + file = File( + id="test_file_id", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://test.example.com/test-file.png", + filename="test-file", + extension=".png", + mime_type="image/png", + size=1000, + ) + segment = variable_factory.build_segment([file]) + assert isinstance(segment, ArrayFileSegment) + assert len(segment.value) == 1 + assert segment.value[0] == file + assert segment.value_type == SegmentType.ARRAY_FILE + + +def test_build_segment_array_file_multiple_files(): + """Test building ArrayFileSegment from list with multiple files.""" + file1 = File( + id="test_file_id_1", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://test.example.com/test-file1.png", + filename="test-file1", + extension=".png", + mime_type="image/png", + size=1000, + ) + file2 = File( + id="test_file_id_2", + tenant_id="test_tenant_id", + type=FileType.DOCUMENT, + transfer_method=FileTransferMethod.LOCAL_FILE, + related_id="test_relation_id", + filename="test-file2", + extension=".txt", + mime_type="text/plain", + size=500, + ) + segment = variable_factory.build_segment([file1, file2]) + assert isinstance(segment, ArrayFileSegment) + assert len(segment.value) == 2 + assert segment.value[0] == file1 + assert segment.value[1] == file2 + assert segment.value_type == SegmentType.ARRAY_FILE + + +def test_build_segment_array_file_empty_list(): + """Test building ArrayFileSegment from empty list should create ArrayAnySegment.""" + segment = variable_factory.build_segment([]) + assert isinstance(segment, ArrayAnySegment) + assert segment.value == [] + assert segment.value_type == SegmentType.ARRAY_ANY + + +def test_build_segment_array_any_mixed_types(): + """Test building ArrayAnySegment from list with mixed types.""" + mixed_values = ["string", 42, 3.14, {"key": "value"}, None] + segment = variable_factory.build_segment(mixed_values) + assert isinstance(segment, ArrayAnySegment) + assert segment.value == mixed_values + assert segment.value_type == SegmentType.ARRAY_ANY + + +def test_build_segment_array_any_with_nested_arrays(): + """Test building ArrayAnySegment from list containing arrays.""" + nested_values = [["nested", "array"], [1, 2, 3], "string"] + segment = variable_factory.build_segment(nested_values) + assert isinstance(segment, ArrayAnySegment) + assert segment.value == nested_values + assert segment.value_type == SegmentType.ARRAY_ANY + + +def test_build_segment_array_any_mixed_with_files(): + """Test building ArrayAnySegment from list with files and other types.""" + file = File( + id="test_file_id", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://test.example.com/test-file.png", + filename="test-file", + extension=".png", + mime_type="image/png", + size=1000, + ) + mixed_values = [file, "string", 42] + segment = variable_factory.build_segment(mixed_values) + assert isinstance(segment, ArrayAnySegment) + assert segment.value == mixed_values + assert segment.value_type == SegmentType.ARRAY_ANY + + +def test_build_segment_array_any_all_none_values(): + """Test building ArrayAnySegment from list with all None values.""" + none_values = [None, None, None] + segment = variable_factory.build_segment(none_values) + assert isinstance(segment, ArrayAnySegment) + assert segment.value == none_values + assert segment.value_type == SegmentType.ARRAY_ANY + + +def test_build_segment_array_file_properties(): + """Test ArrayFileSegment properties and methods.""" + file1 = File( + id="test_file_id_1", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://test.example.com/test-file1.png", + filename="test-file1", + extension=".png", + mime_type="image/png", + size=1000, + ) + file2 = File( + id="test_file_id_2", + tenant_id="test_tenant_id", + type=FileType.DOCUMENT, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://test.example.com/test-file2.txt", + filename="test-file2", + extension=".txt", + mime_type="text/plain", + size=500, + ) + segment = variable_factory.build_segment([file1, file2]) + + # Test properties + assert segment.text == "" # ArrayFileSegment text property returns empty string + assert segment.log == "" # ArrayFileSegment log property returns empty string + assert segment.markdown == f"{file1.markdown}\n{file2.markdown}" + assert segment.to_object() == [file1, file2] + + +def test_build_segment_array_any_properties(): + """Test ArrayAnySegment properties and methods.""" + mixed_values = ["string", 42, None] + segment = variable_factory.build_segment(mixed_values) + + # Test properties + assert segment.text == str(mixed_values) + assert segment.log == str(mixed_values) + assert segment.markdown == "string\n42\nNone" + assert segment.to_object() == mixed_values + + +def test_build_segment_edge_cases(): + """Test edge cases for build_segment function.""" + # Test with complex nested structures + complex_structure = [{"nested": {"deep": [1, 2, 3]}}, [{"inner": "value"}], "mixed"] + segment = variable_factory.build_segment(complex_structure) + assert isinstance(segment, ArrayAnySegment) + assert segment.value == complex_structure + + # Test with single None in list + single_none = [None] + segment = variable_factory.build_segment(single_none) + assert isinstance(segment, ArrayAnySegment) + assert segment.value == single_none + + +def test_build_segment_file_array_with_different_file_types(): + """Test ArrayFileSegment with different file types.""" + image_file = File( + id="image_id", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://test.example.com/image.png", + filename="image", + extension=".png", + mime_type="image/png", + size=1000, + ) + + video_file = File( + id="video_id", + tenant_id="test_tenant_id", + type=FileType.VIDEO, + transfer_method=FileTransferMethod.LOCAL_FILE, + related_id="video_relation_id", + filename="video", + extension=".mp4", + mime_type="video/mp4", + size=5000, + ) + + audio_file = File( + id="audio_id", + tenant_id="test_tenant_id", + type=FileType.AUDIO, + transfer_method=FileTransferMethod.LOCAL_FILE, + related_id="audio_relation_id", + filename="audio", + extension=".mp3", + mime_type="audio/mpeg", + size=3000, + ) + + segment = variable_factory.build_segment([image_file, video_file, audio_file]) + assert isinstance(segment, ArrayFileSegment) + assert len(segment.value) == 3 + assert segment.value[0].type == FileType.IMAGE + assert segment.value[1].type == FileType.VIDEO + assert segment.value[2].type == FileType.AUDIO + + +@st.composite +def _generate_file(draw) -> File: + file_id = draw(st.text(min_size=1, max_size=10)) + tenant_id = draw(st.text(min_size=1, max_size=10)) + file_type, mime_type, extension = draw( + st.sampled_from( + [ + (FileType.IMAGE, "image/png", ".png"), + (FileType.VIDEO, "video/mp4", ".mp4"), + (FileType.DOCUMENT, "text/plain", ".txt"), + (FileType.AUDIO, "audio/mpeg", ".mp3"), + ] + ) + ) + filename = "test-file" + size = draw(st.integers(min_value=0, max_value=1024 * 1024)) + + transfer_method = draw(st.sampled_from(list(FileTransferMethod))) + if transfer_method == FileTransferMethod.REMOTE_URL: + url = "https://test.example.com/test-file" + file = File( + id="test_file_id", + tenant_id="test_tenant_id", + type=file_type, + transfer_method=transfer_method, + remote_url=url, + related_id=None, + filename=filename, + extension=extension, + mime_type=mime_type, + size=size, + ) + else: + relation_id = draw(st.uuids(version=4)) + + file = File( + id="test_file_id", + tenant_id="test_tenant_id", + type=file_type, + transfer_method=transfer_method, + related_id=str(relation_id), + filename=filename, + extension=extension, + mime_type=mime_type, + size=size, + ) + return file + + +def _scalar_value() -> st.SearchStrategy[int | float | str | File | None]: + return st.one_of( + st.none(), + st.integers(), + st.floats(), + st.text(), + _generate_file(), + ) + + +@given(_scalar_value()) +def test_build_segment_and_extract_values_for_scalar_types(value): + seg = variable_factory.build_segment(value) + # nan == nan yields false, so we need to use `math.isnan` to check `seg.value` here. + if isinstance(value, float) and math.isnan(value): + assert math.isnan(seg.value) + else: + assert seg.value == value + + +@given(st.lists(_scalar_value())) +def test_build_segment_and_extract_values_for_array_types(values): + seg = variable_factory.build_segment(values) + assert seg.value == values + + +def test_build_segment_type_for_scalar(): + @dataclass(frozen=True) + class TestCase: + value: int | float | str | File + expected_type: SegmentType + + file = File( + id="test_file_id", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://test.example.com/test-file.png", + filename="test-file", + extension=".png", + mime_type="image/png", + size=1000, + ) + cases = [ + TestCase(0, SegmentType.NUMBER), + TestCase(0.0, SegmentType.NUMBER), + TestCase("", SegmentType.STRING), + TestCase(file, SegmentType.FILE), + ] + + for idx, c in enumerate(cases, 1): + segment = variable_factory.build_segment(c.value) + assert segment.value_type == c.expected_type, f"test case {idx} failed." + + +class TestBuildSegmentWithType: + """Test cases for build_segment_with_type function.""" + + def test_string_type(self): + """Test building a string segment with correct type.""" + result = build_segment_with_type(SegmentType.STRING, "hello") + assert isinstance(result, StringSegment) + assert result.value == "hello" + assert result.value_type == SegmentType.STRING + + def test_number_type_integer(self): + """Test building a number segment with integer value.""" + result = build_segment_with_type(SegmentType.NUMBER, 42) + assert isinstance(result, IntegerSegment) + assert result.value == 42 + assert result.value_type == SegmentType.NUMBER + + def test_number_type_float(self): + """Test building a number segment with float value.""" + result = build_segment_with_type(SegmentType.NUMBER, 3.14) + assert isinstance(result, FloatSegment) + assert result.value == 3.14 + assert result.value_type == SegmentType.NUMBER + + def test_object_type(self): + """Test building an object segment with correct type.""" + test_obj = {"key": "value", "nested": {"inner": 123}} + result = build_segment_with_type(SegmentType.OBJECT, test_obj) + assert isinstance(result, ObjectSegment) + assert result.value == test_obj + assert result.value_type == SegmentType.OBJECT + + def test_file_type(self): + """Test building a file segment with correct type.""" + test_file = File( + id="test_file_id", + tenant_id="test_tenant_id", + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://test.example.com/test-file.png", + filename="test-file", + extension=".png", + mime_type="image/png", + size=1000, + storage_key="test_storage_key", + ) + result = build_segment_with_type(SegmentType.FILE, test_file) + assert isinstance(result, FileSegment) + assert result.value == test_file + assert result.value_type == SegmentType.FILE + + def test_none_type(self): + """Test building a none segment with None value.""" + result = build_segment_with_type(SegmentType.NONE, None) + assert isinstance(result, NoneSegment) + assert result.value is None + assert result.value_type == SegmentType.NONE + + def test_empty_array_string(self): + """Test building an empty array[string] segment.""" + result = build_segment_with_type(SegmentType.ARRAY_STRING, []) + assert isinstance(result, ArrayStringSegment) + assert result.value == [] + assert result.value_type == SegmentType.ARRAY_STRING + + def test_empty_array_number(self): + """Test building an empty array[number] segment.""" + result = build_segment_with_type(SegmentType.ARRAY_NUMBER, []) + assert isinstance(result, ArrayNumberSegment) + assert result.value == [] + assert result.value_type == SegmentType.ARRAY_NUMBER + + def test_empty_array_object(self): + """Test building an empty array[object] segment.""" + result = build_segment_with_type(SegmentType.ARRAY_OBJECT, []) + assert isinstance(result, ArrayObjectSegment) + assert result.value == [] + assert result.value_type == SegmentType.ARRAY_OBJECT + + def test_empty_array_file(self): + """Test building an empty array[file] segment.""" + result = build_segment_with_type(SegmentType.ARRAY_FILE, []) + assert isinstance(result, ArrayFileSegment) + assert result.value == [] + assert result.value_type == SegmentType.ARRAY_FILE + + def test_empty_array_any(self): + """Test building an empty array[any] segment.""" + result = build_segment_with_type(SegmentType.ARRAY_ANY, []) + assert isinstance(result, ArrayAnySegment) + assert result.value == [] + assert result.value_type == SegmentType.ARRAY_ANY + + def test_array_with_values(self): + """Test building array segments with actual values.""" + # Array of strings + result = build_segment_with_type(SegmentType.ARRAY_STRING, ["hello", "world"]) + assert isinstance(result, ArrayStringSegment) + assert result.value == ["hello", "world"] + assert result.value_type == SegmentType.ARRAY_STRING + + # Array of numbers + result = build_segment_with_type(SegmentType.ARRAY_NUMBER, [1, 2, 3.14]) + assert isinstance(result, ArrayNumberSegment) + assert result.value == [1, 2, 3.14] + assert result.value_type == SegmentType.ARRAY_NUMBER + + # Array of objects + result = build_segment_with_type(SegmentType.ARRAY_OBJECT, [{"a": 1}, {"b": 2}]) + assert isinstance(result, ArrayObjectSegment) + assert result.value == [{"a": 1}, {"b": 2}] + assert result.value_type == SegmentType.ARRAY_OBJECT + + def test_type_mismatch_string_to_number(self): + """Test type mismatch when expecting number but getting string.""" + with pytest.raises(TypeMismatchError) as exc_info: + build_segment_with_type(SegmentType.NUMBER, "not_a_number") + + assert "Type mismatch" in str(exc_info.value) + assert "expected number" in str(exc_info.value) + assert "str" in str(exc_info.value) + + def test_type_mismatch_number_to_string(self): + """Test type mismatch when expecting string but getting number.""" + with pytest.raises(TypeMismatchError) as exc_info: + build_segment_with_type(SegmentType.STRING, 123) + + assert "Type mismatch" in str(exc_info.value) + assert "expected string" in str(exc_info.value) + assert "int" in str(exc_info.value) + + def test_type_mismatch_none_to_string(self): + """Test type mismatch when expecting string but getting None.""" + with pytest.raises(TypeMismatchError) as exc_info: + build_segment_with_type(SegmentType.STRING, None) + + assert "Expected string, but got None" in str(exc_info.value) + + def test_type_mismatch_empty_list_to_non_array(self): + """Test type mismatch when expecting non-array type but getting empty list.""" + with pytest.raises(TypeMismatchError) as exc_info: + build_segment_with_type(SegmentType.STRING, []) + + assert "Expected string, but got empty list" in str(exc_info.value) + + def test_type_mismatch_object_to_array(self): + """Test type mismatch when expecting array but getting object.""" + with pytest.raises(TypeMismatchError) as exc_info: + build_segment_with_type(SegmentType.ARRAY_STRING, {"key": "value"}) + + assert "Type mismatch" in str(exc_info.value) + assert "expected array[string]" in str(exc_info.value) + + def test_compatible_number_types(self): + """Test that int and float are both compatible with NUMBER type.""" + # Integer should work + result_int = build_segment_with_type(SegmentType.NUMBER, 42) + assert isinstance(result_int, IntegerSegment) + assert result_int.value_type == SegmentType.NUMBER + + # Float should work + result_float = build_segment_with_type(SegmentType.NUMBER, 3.14) + assert isinstance(result_float, FloatSegment) + assert result_float.value_type == SegmentType.NUMBER + + @pytest.mark.parametrize( + ("segment_type", "value", "expected_class"), + [ + (SegmentType.STRING, "test", StringSegment), + (SegmentType.NUMBER, 42, IntegerSegment), + (SegmentType.NUMBER, 3.14, FloatSegment), + (SegmentType.OBJECT, {}, ObjectSegment), + (SegmentType.NONE, None, NoneSegment), + (SegmentType.ARRAY_STRING, [], ArrayStringSegment), + (SegmentType.ARRAY_NUMBER, [], ArrayNumberSegment), + (SegmentType.ARRAY_OBJECT, [], ArrayObjectSegment), + (SegmentType.ARRAY_ANY, [], ArrayAnySegment), + ], + ) + def test_parametrized_valid_types(self, segment_type, value, expected_class): + """Parametrized test for valid type combinations.""" + result = build_segment_with_type(segment_type, value) + assert isinstance(result, expected_class) + assert result.value == value + assert result.value_type == segment_type + + @pytest.mark.parametrize( + ("segment_type", "value"), + [ + (SegmentType.STRING, 123), + (SegmentType.NUMBER, "not_a_number"), + (SegmentType.OBJECT, "not_an_object"), + (SegmentType.ARRAY_STRING, "not_an_array"), + (SegmentType.STRING, None), + (SegmentType.NUMBER, None), + ], + ) + def test_parametrized_type_mismatches(self, segment_type, value): + """Parametrized test for type mismatches that should raise TypeMismatchError.""" + with pytest.raises(TypeMismatchError): + build_segment_with_type(segment_type, value) + + +# Test cases for ValueError scenarios in build_segment function +class TestBuildSegmentValueErrors: + """Test cases for ValueError scenarios in the build_segment function.""" + + @dataclass(frozen=True) + class ValueErrorTestCase: + """Test case data for ValueError scenarios.""" + + name: str + description: str + test_value: Any + + def _get_test_cases(self): + """Get all test cases for ValueError scenarios.""" + + # Define inline classes for complex test cases + class CustomType: + pass + + def unsupported_function(): + return "test" + + def gen(): + yield 1 + yield 2 + + return [ + self.ValueErrorTestCase( + name="unsupported_custom_type", + description="custom class that doesn't match any supported type", + test_value=CustomType(), + ), + self.ValueErrorTestCase( + name="unsupported_set_type", + description="set (unsupported collection type)", + test_value={1, 2, 3}, + ), + self.ValueErrorTestCase( + name="unsupported_tuple_type", description="tuple (unsupported type)", test_value=(1, 2, 3) + ), + self.ValueErrorTestCase( + name="unsupported_bytes_type", + description="bytes (unsupported type)", + test_value=b"hello world", + ), + self.ValueErrorTestCase( + name="unsupported_function_type", + description="function (unsupported type)", + test_value=unsupported_function, + ), + self.ValueErrorTestCase( + name="unsupported_module_type", description="module (unsupported type)", test_value=math + ), + self.ValueErrorTestCase( + name="array_with_unsupported_element_types", + description="array with unsupported element types", + test_value=[CustomType()], + ), + self.ValueErrorTestCase( + name="mixed_array_with_unsupported_types", + description="array with mix of supported and unsupported types", + test_value=["valid_string", 42, CustomType()], + ), + self.ValueErrorTestCase( + name="nested_unsupported_types", + description="nested structures containing unsupported types", + test_value=[{"valid": "data"}, CustomType()], + ), + self.ValueErrorTestCase( + name="complex_number_type", + description="complex number (unsupported type)", + test_value=3 + 4j, + ), + self.ValueErrorTestCase( + name="range_type", description="range object (unsupported type)", test_value=range(10) + ), + self.ValueErrorTestCase( + name="generator_type", + description="generator (unsupported type)", + test_value=gen(), + ), + self.ValueErrorTestCase( + name="exception_message_contains_value", + description="set to verify error message contains the actual unsupported value", + test_value={1, 2, 3}, + ), + self.ValueErrorTestCase( + name="array_with_mixed_unsupported_segment_types", + description="array processing with unsupported segment types in match", + test_value=[CustomType()], + ), + self.ValueErrorTestCase( + name="frozenset_type", + description="frozenset (unsupported type)", + test_value=frozenset([1, 2, 3]), + ), + self.ValueErrorTestCase( + name="memoryview_type", + description="memoryview (unsupported type)", + test_value=memoryview(b"hello"), + ), + self.ValueErrorTestCase( + name="slice_type", description="slice object (unsupported type)", test_value=slice(1, 10, 2) + ), + self.ValueErrorTestCase(name="type_object", description="type object (unsupported type)", test_value=type), + self.ValueErrorTestCase( + name="generic_object", description="generic object (unsupported type)", test_value=object() + ), + ] + + def test_build_segment_unsupported_types(self): + """Table-driven test for all ValueError scenarios in build_segment function.""" + test_cases = self._get_test_cases() + + for index, test_case in enumerate(test_cases, 1): + # Use test value directly + test_value = test_case.test_value + + with pytest.raises(ValueError) as exc_info: # noqa: PT012 + segment = variable_factory.build_segment(test_value) + pytest.fail(f"Test case {index} ({test_case.name}) should raise ValueError but not, result={segment}") + + error_message = str(exc_info.value) + assert "not supported value" in error_message, ( + f"Test case {index} ({test_case.name}): Expected 'not supported value' in error message, " + f"but got: {error_message}" + ) + + def test_build_segment_boolean_type_note(self): + """Note: Boolean values are actually handled as integers in Python, so they don't raise ValueError.""" + # Boolean values in Python are subclasses of int, so they get processed as integers + # True becomes IntegerSegment(value=1) and False becomes IntegerSegment(value=0) + true_segment = variable_factory.build_segment(True) + false_segment = variable_factory.build_segment(False) + + # Verify they are processed as integers, not as errors + assert true_segment.value == 1, "Test case 1 (boolean_true): Expected True to be processed as integer 1" + assert false_segment.value == 0, "Test case 2 (boolean_false): Expected False to be processed as integer 0" + assert true_segment.value_type == SegmentType.NUMBER + assert false_segment.value_type == SegmentType.NUMBER diff --git a/api/tests/unit_tests/libs/test_datetime_utils.py b/api/tests/unit_tests/libs/test_datetime_utils.py new file mode 100644 index 0000000000..e7781a5821 --- /dev/null +++ b/api/tests/unit_tests/libs/test_datetime_utils.py @@ -0,0 +1,20 @@ +import datetime + +from libs.datetime_utils import naive_utc_now + + +def test_naive_utc_now(monkeypatch): + tz_aware_utc_now = datetime.datetime.now(tz=datetime.UTC) + + def _now_func(tz: datetime.timezone | None) -> datetime.datetime: + return tz_aware_utc_now.astimezone(tz) + + monkeypatch.setattr("libs.datetime_utils._now_func", _now_func) + + naive_datetime = naive_utc_now() + + assert naive_datetime.tzinfo is None + assert naive_datetime.date() == tz_aware_utc_now.date() + naive_time = naive_datetime.time() + utc_time = tz_aware_utc_now.time() + assert naive_time == utc_time diff --git a/api/tests/unit_tests/libs/test_password.py b/api/tests/unit_tests/libs/test_password.py new file mode 100644 index 0000000000..79fc792cc5 --- /dev/null +++ b/api/tests/unit_tests/libs/test_password.py @@ -0,0 +1,74 @@ +import base64 +import binascii +import os + +import pytest + +from libs.password import compare_password, hash_password, valid_password + + +class TestValidPassword: + """Test password format validation""" + + def test_should_accept_valid_passwords(self): + """Test accepting valid password formats""" + assert valid_password("password123") == "password123" + assert valid_password("test1234") == "test1234" + assert valid_password("Test123456") == "Test123456" + + def test_should_reject_invalid_passwords(self): + """Test rejecting invalid password formats""" + # Too short + with pytest.raises(ValueError) as exc_info: + valid_password("abc123") + assert "Password must contain letters and numbers" in str(exc_info.value) + + # No numbers + with pytest.raises(ValueError): + valid_password("abcdefgh") + + # No letters + with pytest.raises(ValueError): + valid_password("12345678") + + # Empty + with pytest.raises(ValueError): + valid_password("") + + +class TestPasswordHashing: + """Test password hashing and comparison""" + + def setup_method(self): + """Setup test data""" + self.password = "test123password" + self.salt = os.urandom(16) + self.salt_base64 = base64.b64encode(self.salt).decode() + + password_hash = hash_password(self.password, self.salt) + self.password_hash_base64 = base64.b64encode(password_hash).decode() + + def test_should_verify_correct_password(self): + """Test correct password verification""" + result = compare_password(self.password, self.password_hash_base64, self.salt_base64) + assert result is True + + def test_should_reject_wrong_password(self): + """Test rejection of incorrect passwords""" + result = compare_password("wrongpassword", self.password_hash_base64, self.salt_base64) + assert result is False + + def test_should_handle_invalid_base64(self): + """Test handling of invalid base64 data""" + # Invalid base64 hash + with pytest.raises(binascii.Error): + compare_password(self.password, "invalid_base64!", self.salt_base64) + + # Invalid base64 salt + with pytest.raises(binascii.Error): + compare_password(self.password, self.password_hash_base64, "invalid_base64!") + + def test_should_be_case_sensitive(self): + """Test password case sensitivity""" + result = compare_password(self.password.upper(), self.password_hash_base64, self.salt_base64) + assert result is False diff --git a/api/tests/unit_tests/models/__init__.py b/api/tests/unit_tests/models/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/tests/unit_tests/models/test_workflow.py b/api/tests/unit_tests/models/test_workflow.py index b79e95c7ed..69163d48bd 100644 --- a/api/tests/unit_tests/models/test_workflow.py +++ b/api/tests/unit_tests/models/test_workflow.py @@ -1,10 +1,15 @@ +import dataclasses import json from unittest import mock from uuid import uuid4 from constants import HIDDEN_VALUE +from core.file.enums import FileTransferMethod, FileType +from core.file.models import File from core.variables import FloatVariable, IntegerVariable, SecretVariable, StringVariable -from models.workflow import Workflow, WorkflowNodeExecutionModel +from core.variables.segments import IntegerSegment, Segment +from factories.variable_factory import build_segment +from models.workflow import Workflow, WorkflowDraftVariable, WorkflowNodeExecutionModel, is_system_variable_editable def test_environment_variables(): @@ -163,3 +168,147 @@ class TestWorkflowNodeExecution: original = {"a": 1, "b": ["2"]} node_exec.execution_metadata = json.dumps(original) assert node_exec.execution_metadata_dict == original + + +class TestIsSystemVariableEditable: + def test_is_system_variable(self): + cases = [ + ("query", True), + ("files", True), + ("dialogue_count", False), + ("conversation_id", False), + ("user_id", False), + ("app_id", False), + ("workflow_id", False), + ("workflow_run_id", False), + ] + for name, editable in cases: + assert editable == is_system_variable_editable(name) + + assert is_system_variable_editable("invalid_or_new_system_variable") == False + + +class TestWorkflowDraftVariableGetValue: + def test_get_value_by_case(self): + @dataclasses.dataclass + class TestCase: + name: str + value: Segment + + tenant_id = "test_tenant_id" + + test_file = File( + tenant_id=tenant_id, + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://example.com/example.jpg", + filename="example.jpg", + extension=".jpg", + mime_type="image/jpeg", + size=100, + ) + cases: list[TestCase] = [ + TestCase( + name="number/int", + value=build_segment(1), + ), + TestCase( + name="number/float", + value=build_segment(1.0), + ), + TestCase( + name="string", + value=build_segment("a"), + ), + TestCase( + name="object", + value=build_segment({}), + ), + TestCase( + name="file", + value=build_segment(test_file), + ), + TestCase( + name="array[any]", + value=build_segment([1, "a"]), + ), + TestCase( + name="array[string]", + value=build_segment(["a", "b"]), + ), + TestCase( + name="array[number]/int", + value=build_segment([1, 2]), + ), + TestCase( + name="array[number]/float", + value=build_segment([1.0, 2.0]), + ), + TestCase( + name="array[number]/mixed", + value=build_segment([1, 2.0]), + ), + TestCase( + name="array[object]", + value=build_segment([{}, {"a": 1}]), + ), + TestCase( + name="none", + value=build_segment(None), + ), + ] + + for idx, c in enumerate(cases, 1): + fail_msg = f"test case {c.name} failed, index={idx}" + draft_var = WorkflowDraftVariable() + draft_var.set_value(c.value) + assert c.value == draft_var.get_value(), fail_msg + + def test_file_variable_preserves_all_fields(self): + """Test that File type variables preserve all fields during encoding/decoding.""" + tenant_id = "test_tenant_id" + + # Create a File with specific field values + test_file = File( + id="test_file_id", + tenant_id=tenant_id, + type=FileType.IMAGE, + transfer_method=FileTransferMethod.REMOTE_URL, + remote_url="https://example.com/test.jpg", + filename="test.jpg", + extension=".jpg", + mime_type="image/jpeg", + size=12345, # Specific size to test preservation + storage_key="test_storage_key", + ) + + # Create a FileSegment and WorkflowDraftVariable + file_segment = build_segment(test_file) + draft_var = WorkflowDraftVariable() + draft_var.set_value(file_segment) + + # Retrieve the value and verify all fields are preserved + retrieved_segment = draft_var.get_value() + retrieved_file = retrieved_segment.value + + # Verify all important fields are preserved + assert retrieved_file.id == test_file.id + assert retrieved_file.tenant_id == test_file.tenant_id + assert retrieved_file.type == test_file.type + assert retrieved_file.transfer_method == test_file.transfer_method + assert retrieved_file.remote_url == test_file.remote_url + assert retrieved_file.filename == test_file.filename + assert retrieved_file.extension == test_file.extension + assert retrieved_file.mime_type == test_file.mime_type + assert retrieved_file.size == test_file.size # This was the main issue being fixed + # Note: storage_key is not serialized in model_dump() so it won't be preserved + + # Verify the segments have the same type and the important fields match + assert file_segment.value_type == retrieved_segment.value_type + + def test_get_and_set_value(self): + draft_var = WorkflowDraftVariable() + int_var = IntegerSegment(value=1) + draft_var.set_value(int_var) + value = draft_var.get_value() + assert value == int_var diff --git a/api/tests/unit_tests/services/test_dataset_permission.py b/api/tests/unit_tests/services/test_dataset_permission.py index 066f541c1b..a67252e856 100644 --- a/api/tests/unit_tests/services/test_dataset_permission.py +++ b/api/tests/unit_tests/services/test_dataset_permission.py @@ -8,151 +8,298 @@ from services.dataset_service import DatasetService from services.errors.account import NoPermissionError +class DatasetPermissionTestDataFactory: + """Factory class for creating test data and mock objects for dataset permission tests.""" + + @staticmethod + def create_dataset_mock( + dataset_id: str = "dataset-123", + tenant_id: str = "test-tenant-123", + created_by: str = "creator-456", + permission: DatasetPermissionEnum = DatasetPermissionEnum.ONLY_ME, + **kwargs, + ) -> Mock: + """Create a mock dataset with specified attributes.""" + dataset = Mock(spec=Dataset) + dataset.id = dataset_id + dataset.tenant_id = tenant_id + dataset.created_by = created_by + dataset.permission = permission + for key, value in kwargs.items(): + setattr(dataset, key, value) + return dataset + + @staticmethod + def create_user_mock( + user_id: str = "user-789", + tenant_id: str = "test-tenant-123", + role: TenantAccountRole = TenantAccountRole.NORMAL, + **kwargs, + ) -> Mock: + """Create a mock user with specified attributes.""" + user = Mock(spec=Account) + user.id = user_id + user.current_tenant_id = tenant_id + user.current_role = role + for key, value in kwargs.items(): + setattr(user, key, value) + return user + + @staticmethod + def create_dataset_permission_mock( + dataset_id: str = "dataset-123", + account_id: str = "user-789", + **kwargs, + ) -> Mock: + """Create a mock dataset permission record.""" + permission = Mock(spec=DatasetPermission) + permission.dataset_id = dataset_id + permission.account_id = account_id + for key, value in kwargs.items(): + setattr(permission, key, value) + return permission + + class TestDatasetPermissionService: - """Test cases for dataset permission checking functionality""" - - def setup_method(self): - """Set up test fixtures""" - # Mock tenant and user - self.tenant_id = "test-tenant-123" - self.creator_id = "creator-456" - self.normal_user_id = "normal-789" - self.owner_user_id = "owner-999" - - # Mock dataset - self.dataset = Mock(spec=Dataset) - self.dataset.id = "dataset-123" - self.dataset.tenant_id = self.tenant_id - self.dataset.created_by = self.creator_id - - # Mock users - self.creator_user = Mock(spec=Account) - self.creator_user.id = self.creator_id - self.creator_user.current_tenant_id = self.tenant_id - self.creator_user.current_role = TenantAccountRole.EDITOR - - self.normal_user = Mock(spec=Account) - self.normal_user.id = self.normal_user_id - self.normal_user.current_tenant_id = self.tenant_id - self.normal_user.current_role = TenantAccountRole.NORMAL - - self.owner_user = Mock(spec=Account) - self.owner_user.id = self.owner_user_id - self.owner_user.current_tenant_id = self.tenant_id - self.owner_user.current_role = TenantAccountRole.OWNER + """ + Comprehensive unit tests for DatasetService.check_dataset_permission method. + + This test suite covers all permission scenarios including: + - Cross-tenant access restrictions + - Owner privilege checks + - Different permission levels (ONLY_ME, ALL_TEAM, PARTIAL_TEAM) + - Explicit permission checks for PARTIAL_TEAM + - Error conditions and logging + """ + + @pytest.fixture + def mock_dataset_service_dependencies(self): + """Common mock setup for dataset service dependencies.""" + with patch("services.dataset_service.db.session") as mock_session: + yield { + "db_session": mock_session, + } + + @pytest.fixture + def mock_logging_dependencies(self): + """Mock setup for logging tests.""" + with patch("services.dataset_service.logging") as mock_logging: + yield { + "logging": mock_logging, + } + + def _assert_permission_check_passes(self, dataset: Mock, user: Mock): + """Helper method to verify that permission check passes without raising exceptions.""" + # Should not raise any exception + DatasetService.check_dataset_permission(dataset, user) + + def _assert_permission_check_fails( + self, dataset: Mock, user: Mock, expected_message: str = "You do not have permission to access this dataset." + ): + """Helper method to verify that permission check fails with expected error.""" + with pytest.raises(NoPermissionError, match=expected_message): + DatasetService.check_dataset_permission(dataset, user) + + def _assert_database_query_called(self, mock_session: Mock, dataset_id: str, account_id: str): + """Helper method to verify database query calls for permission checks.""" + mock_session.query().filter_by.assert_called_with(dataset_id=dataset_id, account_id=account_id) + + def _assert_database_query_not_called(self, mock_session: Mock): + """Helper method to verify that database query was not called.""" + mock_session.query.assert_not_called() + + # ==================== Cross-Tenant Access Tests ==================== def test_permission_check_different_tenant_should_fail(self): - """Test that users from different tenants cannot access dataset""" - self.normal_user.current_tenant_id = "different-tenant" + """Test that users from different tenants cannot access dataset regardless of other permissions.""" + # Create dataset and user from different tenants + dataset = DatasetPermissionTestDataFactory.create_dataset_mock( + tenant_id="tenant-123", permission=DatasetPermissionEnum.ALL_TEAM + ) + user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="user-789", tenant_id="different-tenant-456", role=TenantAccountRole.EDITOR + ) + + # Should fail due to different tenant + self._assert_permission_check_fails(dataset, user) - with pytest.raises(NoPermissionError, match="You do not have permission to access this dataset."): - DatasetService.check_dataset_permission(self.dataset, self.normal_user) + # ==================== Owner Privilege Tests ==================== def test_owner_can_access_any_dataset(self): - """Test that tenant owners can access any dataset regardless of permission""" - self.dataset.permission = DatasetPermissionEnum.ONLY_ME + """Test that tenant owners can access any dataset regardless of permission level.""" + # Create dataset with restrictive permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.ONLY_ME) - # Should not raise any exception - DatasetService.check_dataset_permission(self.dataset, self.owner_user) + # Create owner user + owner_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="owner-999", role=TenantAccountRole.OWNER + ) + + # Owner should have access regardless of dataset permission + self._assert_permission_check_passes(dataset, owner_user) + + # ==================== ONLY_ME Permission Tests ==================== def test_only_me_permission_creator_can_access(self): - """Test ONLY_ME permission allows only creator to access""" - self.dataset.permission = DatasetPermissionEnum.ONLY_ME + """Test ONLY_ME permission allows only the dataset creator to access.""" + # Create dataset with ONLY_ME permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock( + created_by="creator-456", permission=DatasetPermissionEnum.ONLY_ME + ) + + # Create creator user + creator_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="creator-456", role=TenantAccountRole.EDITOR + ) # Creator should be able to access - DatasetService.check_dataset_permission(self.dataset, self.creator_user) + self._assert_permission_check_passes(dataset, creator_user) def test_only_me_permission_others_cannot_access(self): - """Test ONLY_ME permission denies access to non-creators""" - self.dataset.permission = DatasetPermissionEnum.ONLY_ME + """Test ONLY_ME permission denies access to non-creators.""" + # Create dataset with ONLY_ME permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock( + created_by="creator-456", permission=DatasetPermissionEnum.ONLY_ME + ) + + # Create normal user (not the creator) + normal_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="normal-789", role=TenantAccountRole.NORMAL + ) - with pytest.raises(NoPermissionError, match="You do not have permission to access this dataset."): - DatasetService.check_dataset_permission(self.dataset, self.normal_user) + # Non-creator should be denied access + self._assert_permission_check_fails(dataset, normal_user) + + # ==================== ALL_TEAM Permission Tests ==================== def test_all_team_permission_allows_access(self): - """Test ALL_TEAM permission allows any team member to access""" - self.dataset.permission = DatasetPermissionEnum.ALL_TEAM + """Test ALL_TEAM permission allows any team member to access the dataset.""" + # Create dataset with ALL_TEAM permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.ALL_TEAM) + + # Create different types of team members + normal_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="normal-789", role=TenantAccountRole.NORMAL + ) + editor_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="editor-456", role=TenantAccountRole.EDITOR + ) + + # All team members should have access + self._assert_permission_check_passes(dataset, normal_user) + self._assert_permission_check_passes(dataset, editor_user) - # Should not raise any exception for team members - DatasetService.check_dataset_permission(self.dataset, self.normal_user) - DatasetService.check_dataset_permission(self.dataset, self.creator_user) + # ==================== PARTIAL_TEAM Permission Tests ==================== - @patch("services.dataset_service.db.session") - def test_partial_team_permission_creator_can_access(self, mock_session): - """Test PARTIAL_TEAM permission allows creator to access""" - self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM + def test_partial_team_permission_creator_can_access(self, mock_dataset_service_dependencies): + """Test PARTIAL_TEAM permission allows creator to access without database query.""" + # Create dataset with PARTIAL_TEAM permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock( + created_by="creator-456", permission=DatasetPermissionEnum.PARTIAL_TEAM + ) - # Should not raise any exception for creator - DatasetService.check_dataset_permission(self.dataset, self.creator_user) + # Create creator user + creator_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="creator-456", role=TenantAccountRole.EDITOR + ) - # Should not query database for creator - mock_session.query.assert_not_called() + # Creator should have access without database query + self._assert_permission_check_passes(dataset, creator_user) + self._assert_database_query_not_called(mock_dataset_service_dependencies["db_session"]) - @patch("services.dataset_service.db.session") - def test_partial_team_permission_with_explicit_permission(self, mock_session): - """Test PARTIAL_TEAM permission allows users with explicit permission""" - self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM + def test_partial_team_permission_with_explicit_permission(self, mock_dataset_service_dependencies): + """Test PARTIAL_TEAM permission allows users with explicit permission records.""" + # Create dataset with PARTIAL_TEAM permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.PARTIAL_TEAM) + + # Create normal user (not the creator) + normal_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="normal-789", role=TenantAccountRole.NORMAL + ) # Mock database query to return a permission record - mock_permission = Mock(spec=DatasetPermission) - mock_session.query().filter_by().first.return_value = mock_permission + mock_permission = DatasetPermissionTestDataFactory.create_dataset_permission_mock( + dataset_id=dataset.id, account_id=normal_user.id + ) + mock_dataset_service_dependencies["db_session"].query().filter_by().first.return_value = mock_permission - # Should not raise any exception - DatasetService.check_dataset_permission(self.dataset, self.normal_user) + # User with explicit permission should have access + self._assert_permission_check_passes(dataset, normal_user) + self._assert_database_query_called(mock_dataset_service_dependencies["db_session"], dataset.id, normal_user.id) - # Verify database was queried correctly - mock_session.query().filter_by.assert_called_with(dataset_id=self.dataset.id, account_id=self.normal_user.id) + def test_partial_team_permission_without_explicit_permission(self, mock_dataset_service_dependencies): + """Test PARTIAL_TEAM permission denies users without explicit permission records.""" + # Create dataset with PARTIAL_TEAM permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.PARTIAL_TEAM) - @patch("services.dataset_service.db.session") - def test_partial_team_permission_without_explicit_permission(self, mock_session): - """Test PARTIAL_TEAM permission denies users without explicit permission""" - self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM + # Create normal user (not the creator) + normal_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="normal-789", role=TenantAccountRole.NORMAL + ) # Mock database query to return None (no permission record) - mock_session.query().filter_by().first.return_value = None - - with pytest.raises(NoPermissionError, match="You do not have permission to access this dataset."): - DatasetService.check_dataset_permission(self.dataset, self.normal_user) + mock_dataset_service_dependencies["db_session"].query().filter_by().first.return_value = None - # Verify database was queried correctly - mock_session.query().filter_by.assert_called_with(dataset_id=self.dataset.id, account_id=self.normal_user.id) + # User without explicit permission should be denied access + self._assert_permission_check_fails(dataset, normal_user) + self._assert_database_query_called(mock_dataset_service_dependencies["db_session"], dataset.id, normal_user.id) - @patch("services.dataset_service.db.session") - def test_partial_team_permission_non_creator_without_permission_fails(self, mock_session): - """Test that non-creators without explicit permission are denied access""" - self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM + def test_partial_team_permission_non_creator_without_permission_fails(self, mock_dataset_service_dependencies): + """Test that non-creators without explicit permission are denied access to PARTIAL_TEAM datasets.""" + # Create dataset with PARTIAL_TEAM permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock( + created_by="creator-456", permission=DatasetPermissionEnum.PARTIAL_TEAM + ) # Create a different user (not the creator) - other_user = Mock(spec=Account) - other_user.id = "other-user-123" - other_user.current_tenant_id = self.tenant_id - other_user.current_role = TenantAccountRole.NORMAL + other_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="other-user-123", role=TenantAccountRole.NORMAL + ) # Mock database query to return None (no permission record) - mock_session.query().filter_by().first.return_value = None + mock_dataset_service_dependencies["db_session"].query().filter_by().first.return_value = None + + # Non-creator without explicit permission should be denied access + self._assert_permission_check_fails(dataset, other_user) + self._assert_database_query_called(mock_dataset_service_dependencies["db_session"], dataset.id, other_user.id) - with pytest.raises(NoPermissionError, match="You do not have permission to access this dataset."): - DatasetService.check_dataset_permission(self.dataset, other_user) + # ==================== Enum Usage Tests ==================== def test_partial_team_permission_uses_correct_enum(self): - """Test that the method correctly uses DatasetPermissionEnum.PARTIAL_TEAM""" - # This test ensures we're using the enum instead of string literals - self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM + """Test that the method correctly uses DatasetPermissionEnum.PARTIAL_TEAM instead of string literals.""" + # Create dataset with PARTIAL_TEAM permission using enum + dataset = DatasetPermissionTestDataFactory.create_dataset_mock( + created_by="creator-456", permission=DatasetPermissionEnum.PARTIAL_TEAM + ) + + # Create creator user + creator_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="creator-456", role=TenantAccountRole.EDITOR + ) - # Creator should always have access - DatasetService.check_dataset_permission(self.dataset, self.creator_user) + # Creator should always have access regardless of permission level + self._assert_permission_check_passes(dataset, creator_user) - @patch("services.dataset_service.logging") - @patch("services.dataset_service.db.session") - def test_permission_denied_logs_debug_message(self, mock_session, mock_logging): - """Test that permission denied events are logged""" - self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM - mock_session.query().filter_by().first.return_value = None + # ==================== Logging Tests ==================== + + def test_permission_denied_logs_debug_message(self, mock_dataset_service_dependencies, mock_logging_dependencies): + """Test that permission denied events are properly logged for debugging purposes.""" + # Create dataset with PARTIAL_TEAM permission + dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.PARTIAL_TEAM) + + # Create normal user (not the creator) + normal_user = DatasetPermissionTestDataFactory.create_user_mock( + user_id="normal-789", role=TenantAccountRole.NORMAL + ) + + # Mock database query to return None (no permission record) + mock_dataset_service_dependencies["db_session"].query().filter_by().first.return_value = None + # Attempt permission check (should fail) with pytest.raises(NoPermissionError): - DatasetService.check_dataset_permission(self.dataset, self.normal_user) + DatasetService.check_dataset_permission(dataset, normal_user) - # Verify debug message was logged - mock_logging.debug.assert_called_with( - f"User {self.normal_user.id} does not have permission to access dataset {self.dataset.id}" + # Verify debug message was logged with correct user and dataset information + mock_logging_dependencies["logging"].debug.assert_called_with( + f"User {normal_user.id} does not have permission to access dataset {dataset.id}" ) diff --git a/api/tests/unit_tests/services/test_dataset_service_batch_update_document_status.py b/api/tests/unit_tests/services/test_dataset_service_batch_update_document_status.py new file mode 100644 index 0000000000..dc09aca5b2 --- /dev/null +++ b/api/tests/unit_tests/services/test_dataset_service_batch_update_document_status.py @@ -0,0 +1,804 @@ +import datetime +from typing import Optional + +# Mock redis_client before importing dataset_service +from unittest.mock import Mock, call, patch + +import pytest + +from models.dataset import Dataset, Document +from services.dataset_service import DocumentService +from services.errors.document import DocumentIndexingError +from tests.unit_tests.conftest import redis_mock + + +class DocumentBatchUpdateTestDataFactory: + """Factory class for creating test data and mock objects for document batch update tests.""" + + @staticmethod + def create_dataset_mock(dataset_id: str = "dataset-123", tenant_id: str = "tenant-456") -> Mock: + """Create a mock dataset with specified attributes.""" + dataset = Mock(spec=Dataset) + dataset.id = dataset_id + dataset.tenant_id = tenant_id + return dataset + + @staticmethod + def create_user_mock(user_id: str = "user-789") -> Mock: + """Create a mock user.""" + user = Mock() + user.id = user_id + return user + + @staticmethod + def create_document_mock( + document_id: str = "doc-1", + name: str = "test_document.pdf", + enabled: bool = True, + archived: bool = False, + indexing_status: str = "completed", + completed_at: Optional[datetime.datetime] = None, + **kwargs, + ) -> Mock: + """Create a mock document with specified attributes.""" + document = Mock(spec=Document) + document.id = document_id + document.name = name + document.enabled = enabled + document.archived = archived + document.indexing_status = indexing_status + document.completed_at = completed_at or datetime.datetime.now() + + # Set default values for optional fields + document.disabled_at = None + document.disabled_by = None + document.archived_at = None + document.archived_by = None + document.updated_at = None + + for key, value in kwargs.items(): + setattr(document, key, value) + return document + + @staticmethod + def create_multiple_documents( + document_ids: list[str], enabled: bool = True, archived: bool = False, indexing_status: str = "completed" + ) -> list[Mock]: + """Create multiple mock documents with specified attributes.""" + documents = [] + for doc_id in document_ids: + doc = DocumentBatchUpdateTestDataFactory.create_document_mock( + document_id=doc_id, + name=f"document_{doc_id}.pdf", + enabled=enabled, + archived=archived, + indexing_status=indexing_status, + ) + documents.append(doc) + return documents + + +class TestDatasetServiceBatchUpdateDocumentStatus: + """ + Comprehensive unit tests for DocumentService.batch_update_document_status method. + + This test suite covers all supported actions (enable, disable, archive, un_archive), + error conditions, edge cases, and validates proper interaction with Redis cache, + database operations, and async task triggers. + """ + + @pytest.fixture + def mock_document_service_dependencies(self): + """Common mock setup for document service dependencies.""" + with ( + patch("services.dataset_service.DocumentService.get_document") as mock_get_doc, + patch("extensions.ext_database.db.session") as mock_db, + patch("services.dataset_service.datetime") as mock_datetime, + ): + current_time = datetime.datetime(2023, 1, 1, 12, 0, 0) + mock_datetime.datetime.now.return_value = current_time + mock_datetime.UTC = datetime.UTC + + yield { + "get_document": mock_get_doc, + "db_session": mock_db, + "datetime": mock_datetime, + "current_time": current_time, + } + + @pytest.fixture + def mock_async_task_dependencies(self): + """Mock setup for async task dependencies.""" + with ( + patch("services.dataset_service.add_document_to_index_task") as mock_add_task, + patch("services.dataset_service.remove_document_from_index_task") as mock_remove_task, + ): + yield {"add_task": mock_add_task, "remove_task": mock_remove_task} + + def _assert_document_enabled(self, document: Mock, user_id: str, current_time: datetime.datetime): + """Helper method to verify document was enabled correctly.""" + assert document.enabled == True + assert document.disabled_at is None + assert document.disabled_by is None + assert document.updated_at == current_time.replace(tzinfo=None) + + def _assert_document_disabled(self, document: Mock, user_id: str, current_time: datetime.datetime): + """Helper method to verify document was disabled correctly.""" + assert document.enabled == False + assert document.disabled_at == current_time.replace(tzinfo=None) + assert document.disabled_by == user_id + assert document.updated_at == current_time.replace(tzinfo=None) + + def _assert_document_archived(self, document: Mock, user_id: str, current_time: datetime.datetime): + """Helper method to verify document was archived correctly.""" + assert document.archived == True + assert document.archived_at == current_time.replace(tzinfo=None) + assert document.archived_by == user_id + assert document.updated_at == current_time.replace(tzinfo=None) + + def _assert_document_unarchived(self, document: Mock): + """Helper method to verify document was unarchived correctly.""" + assert document.archived == False + assert document.archived_at is None + assert document.archived_by is None + + def _assert_redis_cache_operations(self, document_ids: list[str], action: str = "setex"): + """Helper method to verify Redis cache operations.""" + if action == "setex": + expected_calls = [call(f"document_{doc_id}_indexing", 600, 1) for doc_id in document_ids] + redis_mock.setex.assert_has_calls(expected_calls) + elif action == "get": + expected_calls = [call(f"document_{doc_id}_indexing") for doc_id in document_ids] + redis_mock.get.assert_has_calls(expected_calls) + + def _assert_async_task_calls(self, mock_task, document_ids: list[str], task_type: str): + """Helper method to verify async task calls.""" + expected_calls = [call(doc_id) for doc_id in document_ids] + if task_type in {"add", "remove"}: + mock_task.delay.assert_has_calls(expected_calls) + + # ==================== Enable Document Tests ==================== + + def test_batch_update_enable_documents_success( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test successful enabling of disabled documents.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create disabled documents + disabled_docs = DocumentBatchUpdateTestDataFactory.create_multiple_documents(["doc-1", "doc-2"], enabled=False) + mock_document_service_dependencies["get_document"].side_effect = disabled_docs + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Call the method to enable documents + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1", "doc-2"], action="enable", user=user + ) + + # Verify document attributes were updated correctly + for doc in disabled_docs: + self._assert_document_enabled(doc, user.id, mock_document_service_dependencies["current_time"]) + + # Verify Redis cache operations + self._assert_redis_cache_operations(["doc-1", "doc-2"], "get") + self._assert_redis_cache_operations(["doc-1", "doc-2"], "setex") + + # Verify async tasks were triggered for indexing + self._assert_async_task_calls(mock_async_task_dependencies["add_task"], ["doc-1", "doc-2"], "add") + + # Verify database operations + mock_db = mock_document_service_dependencies["db_session"] + assert mock_db.add.call_count == 2 + assert mock_db.commit.call_count == 1 + + def test_batch_update_enable_already_enabled_document_skipped(self, mock_document_service_dependencies): + """Test enabling documents that are already enabled.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create already enabled document + enabled_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=True) + mock_document_service_dependencies["get_document"].return_value = enabled_doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Attempt to enable already enabled document + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="enable", user=user + ) + + # Verify no database operations occurred (document was skipped) + mock_db = mock_document_service_dependencies["db_session"] + mock_db.commit.assert_not_called() + + # Verify no Redis setex operations occurred (document was skipped) + redis_mock.setex.assert_not_called() + + # ==================== Disable Document Tests ==================== + + def test_batch_update_disable_documents_success( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test successful disabling of enabled and completed documents.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create enabled documents + enabled_docs = DocumentBatchUpdateTestDataFactory.create_multiple_documents(["doc-1", "doc-2"], enabled=True) + mock_document_service_dependencies["get_document"].side_effect = enabled_docs + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Call the method to disable documents + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1", "doc-2"], action="disable", user=user + ) + + # Verify document attributes were updated correctly + for doc in enabled_docs: + self._assert_document_disabled(doc, user.id, mock_document_service_dependencies["current_time"]) + + # Verify Redis cache operations for indexing prevention + self._assert_redis_cache_operations(["doc-1", "doc-2"], "setex") + + # Verify async tasks were triggered to remove from index + self._assert_async_task_calls(mock_async_task_dependencies["remove_task"], ["doc-1", "doc-2"], "remove") + + # Verify database operations + mock_db = mock_document_service_dependencies["db_session"] + assert mock_db.add.call_count == 2 + assert mock_db.commit.call_count == 1 + + def test_batch_update_disable_already_disabled_document_skipped( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test disabling documents that are already disabled.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create already disabled document + disabled_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=False) + mock_document_service_dependencies["get_document"].return_value = disabled_doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Attempt to disable already disabled document + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="disable", user=user + ) + + # Verify no database operations occurred (document was skipped) + mock_db = mock_document_service_dependencies["db_session"] + mock_db.commit.assert_not_called() + + # Verify no Redis setex operations occurred (document was skipped) + redis_mock.setex.assert_not_called() + + # Verify no async tasks were triggered (document was skipped) + mock_async_task_dependencies["add_task"].delay.assert_not_called() + + def test_batch_update_disable_non_completed_document_error(self, mock_document_service_dependencies): + """Test that DocumentIndexingError is raised when trying to disable non-completed documents.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create a document that's not completed + non_completed_doc = DocumentBatchUpdateTestDataFactory.create_document_mock( + enabled=True, + indexing_status="indexing", # Not completed + completed_at=None, # Not completed + ) + mock_document_service_dependencies["get_document"].return_value = non_completed_doc + + # Verify that DocumentIndexingError is raised + with pytest.raises(DocumentIndexingError) as exc_info: + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="disable", user=user + ) + + # Verify error message indicates document is not completed + assert "is not completed" in str(exc_info.value) + + # ==================== Archive Document Tests ==================== + + def test_batch_update_archive_documents_success( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test successful archiving of unarchived documents.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create unarchived enabled document + unarchived_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=True, archived=False) + mock_document_service_dependencies["get_document"].return_value = unarchived_doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Call the method to archive documents + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="archive", user=user + ) + + # Verify document attributes were updated correctly + self._assert_document_archived(unarchived_doc, user.id, mock_document_service_dependencies["current_time"]) + + # Verify Redis cache was set (because document was enabled) + redis_mock.setex.assert_called_once_with("document_doc-1_indexing", 600, 1) + + # Verify async task was triggered to remove from index (because enabled) + mock_async_task_dependencies["remove_task"].delay.assert_called_once_with("doc-1") + + # Verify database operations + mock_db = mock_document_service_dependencies["db_session"] + mock_db.add.assert_called_once() + mock_db.commit.assert_called_once() + + def test_batch_update_archive_already_archived_document_skipped(self, mock_document_service_dependencies): + """Test archiving documents that are already archived.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create already archived document + archived_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=True, archived=True) + mock_document_service_dependencies["get_document"].return_value = archived_doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Attempt to archive already archived document + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-3"], action="archive", user=user + ) + + # Verify no database operations occurred (document was skipped) + mock_db = mock_document_service_dependencies["db_session"] + mock_db.commit.assert_not_called() + + # Verify no Redis setex operations occurred (document was skipped) + redis_mock.setex.assert_not_called() + + def test_batch_update_archive_disabled_document_no_index_removal( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test archiving disabled documents (should not trigger index removal).""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Set up disabled, unarchived document + disabled_unarchived_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=False, archived=False) + mock_document_service_dependencies["get_document"].return_value = disabled_unarchived_doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Archive the disabled document + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="archive", user=user + ) + + # Verify document was archived + self._assert_document_archived( + disabled_unarchived_doc, user.id, mock_document_service_dependencies["current_time"] + ) + + # Verify no Redis cache was set (document is disabled) + redis_mock.setex.assert_not_called() + + # Verify no index removal task was triggered (document is disabled) + mock_async_task_dependencies["remove_task"].delay.assert_not_called() + + # Verify database operations still occurred + mock_db = mock_document_service_dependencies["db_session"] + mock_db.add.assert_called_once() + mock_db.commit.assert_called_once() + + # ==================== Unarchive Document Tests ==================== + + def test_batch_update_unarchive_documents_success( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test successful unarchiving of archived documents.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create mock archived document + archived_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=True, archived=True) + mock_document_service_dependencies["get_document"].return_value = archived_doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Call the method to unarchive documents + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="un_archive", user=user + ) + + # Verify document attributes were updated correctly + self._assert_document_unarchived(archived_doc) + assert archived_doc.updated_at == mock_document_service_dependencies["current_time"].replace(tzinfo=None) + + # Verify Redis cache was set (because document is enabled) + redis_mock.setex.assert_called_once_with("document_doc-1_indexing", 600, 1) + + # Verify async task was triggered to add back to index (because enabled) + mock_async_task_dependencies["add_task"].delay.assert_called_once_with("doc-1") + + # Verify database operations + mock_db = mock_document_service_dependencies["db_session"] + mock_db.add.assert_called_once() + mock_db.commit.assert_called_once() + + def test_batch_update_unarchive_already_unarchived_document_skipped( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test unarchiving documents that are already unarchived.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create already unarchived document + unarchived_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=True, archived=False) + mock_document_service_dependencies["get_document"].return_value = unarchived_doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Attempt to unarchive already unarchived document + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="un_archive", user=user + ) + + # Verify no database operations occurred (document was skipped) + mock_db = mock_document_service_dependencies["db_session"] + mock_db.commit.assert_not_called() + + # Verify no Redis setex operations occurred (document was skipped) + redis_mock.setex.assert_not_called() + + # Verify no async tasks were triggered (document was skipped) + mock_async_task_dependencies["add_task"].delay.assert_not_called() + + def test_batch_update_unarchive_disabled_document_no_index_addition( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test unarchiving disabled documents (should not trigger index addition).""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create mock archived but disabled document + archived_disabled_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=False, archived=True) + mock_document_service_dependencies["get_document"].return_value = archived_disabled_doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Unarchive the disabled document + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="un_archive", user=user + ) + + # Verify document was unarchived + self._assert_document_unarchived(archived_disabled_doc) + assert archived_disabled_doc.updated_at == mock_document_service_dependencies["current_time"].replace( + tzinfo=None + ) + + # Verify no Redis cache was set (document is disabled) + redis_mock.setex.assert_not_called() + + # Verify no index addition task was triggered (document is disabled) + mock_async_task_dependencies["add_task"].delay.assert_not_called() + + # Verify database operations still occurred + mock_db = mock_document_service_dependencies["db_session"] + mock_db.add.assert_called_once() + mock_db.commit.assert_called_once() + + # ==================== Error Handling Tests ==================== + + def test_batch_update_document_indexing_error_redis_cache_hit(self, mock_document_service_dependencies): + """Test that DocumentIndexingError is raised when documents are currently being indexed.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create mock enabled document + enabled_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=True) + mock_document_service_dependencies["get_document"].return_value = enabled_doc + + # Set up mock to indicate document is being indexed + redis_mock.reset_mock() + redis_mock.get.return_value = "indexing" + + # Verify that DocumentIndexingError is raised + with pytest.raises(DocumentIndexingError) as exc_info: + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="enable", user=user + ) + + # Verify error message contains document name + assert "test_document.pdf" in str(exc_info.value) + assert "is being indexed" in str(exc_info.value) + + # Verify Redis cache was checked + redis_mock.get.assert_called_once_with("document_doc-1_indexing") + + def test_batch_update_invalid_action_error(self, mock_document_service_dependencies): + """Test that ValueError is raised when an invalid action is provided.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create mock document + doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=True) + mock_document_service_dependencies["get_document"].return_value = doc + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Test with invalid action + invalid_action = "invalid_action" + with pytest.raises(ValueError) as exc_info: + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action=invalid_action, user=user + ) + + # Verify error message contains the invalid action + assert invalid_action in str(exc_info.value) + assert "Invalid action" in str(exc_info.value) + + # Verify no Redis operations occurred + redis_mock.setex.assert_not_called() + + def test_batch_update_async_task_error_handling( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test handling of async task errors during batch operations.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create mock disabled document + disabled_doc = DocumentBatchUpdateTestDataFactory.create_document_mock(enabled=False) + mock_document_service_dependencies["get_document"].return_value = disabled_doc + + # Mock async task to raise an exception + mock_async_task_dependencies["add_task"].delay.side_effect = Exception("Celery task error") + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Verify that async task error is propagated + with pytest.raises(Exception) as exc_info: + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1"], action="enable", user=user + ) + + # Verify error message + assert "Celery task error" in str(exc_info.value) + + # Verify database operations completed successfully + mock_db = mock_document_service_dependencies["db_session"] + mock_db.add.assert_called_once() + mock_db.commit.assert_called_once() + + # Verify Redis cache was set successfully + redis_mock.setex.assert_called_once_with("document_doc-1_indexing", 600, 1) + + # Verify document was updated + self._assert_document_enabled(disabled_doc, user.id, mock_document_service_dependencies["current_time"]) + + # ==================== Edge Case Tests ==================== + + def test_batch_update_empty_document_list(self, mock_document_service_dependencies): + """Test batch operations with an empty document ID list.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Call method with empty document list + result = DocumentService.batch_update_document_status( + dataset=dataset, document_ids=[], action="enable", user=user + ) + + # Verify no document lookups were performed + mock_document_service_dependencies["get_document"].assert_not_called() + + # Verify method returns None (early return) + assert result is None + + def test_batch_update_document_not_found_skipped(self, mock_document_service_dependencies): + """Test behavior when some documents don't exist in the database.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Mock document service to return None (document not found) + mock_document_service_dependencies["get_document"].return_value = None + + # Call method with non-existent document ID + # This should not raise an error, just skip the missing document + try: + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["non-existent-doc"], action="enable", user=user + ) + except Exception as e: + pytest.fail(f"Method should not raise exception for missing documents: {e}") + + # Verify document lookup was attempted + mock_document_service_dependencies["get_document"].assert_called_once_with(dataset.id, "non-existent-doc") + + def test_batch_update_mixed_document_states_and_actions( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test batch operations on documents with mixed states and various scenarios.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create documents in various states + disabled_doc = DocumentBatchUpdateTestDataFactory.create_document_mock("doc-1", enabled=False) + enabled_doc = DocumentBatchUpdateTestDataFactory.create_document_mock("doc-2", enabled=True) + archived_doc = DocumentBatchUpdateTestDataFactory.create_document_mock("doc-3", enabled=True, archived=True) + + # Mix of different document states + documents = [disabled_doc, enabled_doc, archived_doc] + mock_document_service_dependencies["get_document"].side_effect = documents + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Perform enable operation on mixed state documents + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=["doc-1", "doc-2", "doc-3"], action="enable", user=user + ) + + # Verify only the disabled document was processed + # (enabled and archived documents should be skipped for enable action) + + # Only one add should occur (for the disabled document that was enabled) + mock_db = mock_document_service_dependencies["db_session"] + mock_db.add.assert_called_once() + # Only one commit should occur + mock_db.commit.assert_called_once() + + # Only one Redis setex should occur (for the document that was enabled) + redis_mock.setex.assert_called_once_with("document_doc-1_indexing", 600, 1) + + # Only one async task should be triggered (for the document that was enabled) + mock_async_task_dependencies["add_task"].delay.assert_called_once_with("doc-1") + + # ==================== Performance Tests ==================== + + def test_batch_update_large_document_list_performance( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test batch operations with a large number of documents.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create large list of document IDs + document_ids = [f"doc-{i}" for i in range(1, 101)] # 100 documents + + # Create mock documents + mock_documents = DocumentBatchUpdateTestDataFactory.create_multiple_documents( + document_ids, + enabled=False, # All disabled, will be enabled + ) + mock_document_service_dependencies["get_document"].side_effect = mock_documents + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Perform batch enable operation + DocumentService.batch_update_document_status( + dataset=dataset, document_ids=document_ids, action="enable", user=user + ) + + # Verify all documents were processed + assert mock_document_service_dependencies["get_document"].call_count == 100 + + # Verify all documents were updated + for mock_doc in mock_documents: + self._assert_document_enabled(mock_doc, user.id, mock_document_service_dependencies["current_time"]) + + # Verify database operations + mock_db = mock_document_service_dependencies["db_session"] + assert mock_db.add.call_count == 100 + assert mock_db.commit.call_count == 1 + + # Verify Redis cache operations occurred for each document + assert redis_mock.setex.call_count == 100 + + # Verify async tasks were triggered for each document + assert mock_async_task_dependencies["add_task"].delay.call_count == 100 + + # Verify correct Redis cache keys were set + expected_redis_calls = [call(f"document_doc-{i}_indexing", 600, 1) for i in range(1, 101)] + redis_mock.setex.assert_has_calls(expected_redis_calls) + + # Verify correct async task calls + expected_task_calls = [call(f"doc-{i}") for i in range(1, 101)] + mock_async_task_dependencies["add_task"].delay.assert_has_calls(expected_task_calls) + + def test_batch_update_mixed_document_states_complex_scenario( + self, mock_document_service_dependencies, mock_async_task_dependencies + ): + """Test complex batch operations with documents in various states.""" + dataset = DocumentBatchUpdateTestDataFactory.create_dataset_mock() + user = DocumentBatchUpdateTestDataFactory.create_user_mock() + + # Create documents in various states + doc1 = DocumentBatchUpdateTestDataFactory.create_document_mock("doc-1", enabled=False) # Will be enabled + doc2 = DocumentBatchUpdateTestDataFactory.create_document_mock( + "doc-2", enabled=True + ) # Already enabled, will be skipped + doc3 = DocumentBatchUpdateTestDataFactory.create_document_mock( + "doc-3", enabled=True + ) # Already enabled, will be skipped + doc4 = DocumentBatchUpdateTestDataFactory.create_document_mock( + "doc-4", enabled=True + ) # Not affected by enable action + doc5 = DocumentBatchUpdateTestDataFactory.create_document_mock( + "doc-5", enabled=True, archived=True + ) # Not affected by enable action + doc6 = None # Non-existent, will be skipped + + mock_document_service_dependencies["get_document"].side_effect = [doc1, doc2, doc3, doc4, doc5, doc6] + + # Reset module-level Redis mock + redis_mock.reset_mock() + redis_mock.get.return_value = None + + # Perform mixed batch operations + DocumentService.batch_update_document_status( + dataset=dataset, + document_ids=["doc-1", "doc-2", "doc-3", "doc-4", "doc-5", "doc-6"], + action="enable", # This will only affect doc1 + user=user, + ) + + # Verify document 1 was enabled + self._assert_document_enabled(doc1, user.id, mock_document_service_dependencies["current_time"]) + + # Verify other documents were skipped appropriately + assert doc2.enabled == True # No change + assert doc3.enabled == True # No change + assert doc4.enabled == True # No change + assert doc5.enabled == True # No change + + # Verify database commits occurred for processed documents + # Only doc1 should be added (others were skipped, doc6 doesn't exist) + mock_db = mock_document_service_dependencies["db_session"] + assert mock_db.add.call_count == 1 + assert mock_db.commit.call_count == 1 + + # Verify Redis cache operations occurred for processed documents + # Only doc1 should have Redis operations + assert redis_mock.setex.call_count == 1 + + # Verify async tasks were triggered for processed documents + # Only doc1 should trigger tasks + assert mock_async_task_dependencies["add_task"].delay.call_count == 1 + + # Verify correct Redis cache keys were set + expected_redis_calls = [call("document_doc-1_indexing", 600, 1)] + redis_mock.setex.assert_has_calls(expected_redis_calls) + + # Verify correct async task calls + expected_task_calls = [call("doc-1")] + mock_async_task_dependencies["add_task"].delay.assert_has_calls(expected_task_calls) diff --git a/api/tests/unit_tests/services/test_dataset_service_update_dataset.py b/api/tests/unit_tests/services/test_dataset_service_update_dataset.py new file mode 100644 index 0000000000..cdbb439c85 --- /dev/null +++ b/api/tests/unit_tests/services/test_dataset_service_update_dataset.py @@ -0,0 +1,633 @@ +import datetime +from typing import Any, Optional + +# Mock redis_client before importing dataset_service +from unittest.mock import Mock, patch + +import pytest + +from core.model_runtime.entities.model_entities import ModelType +from models.dataset import Dataset, ExternalKnowledgeBindings +from services.dataset_service import DatasetService +from services.errors.account import NoPermissionError +from tests.unit_tests.conftest import redis_mock + + +class DatasetUpdateTestDataFactory: + """Factory class for creating test data and mock objects for dataset update tests.""" + + @staticmethod + def create_dataset_mock( + dataset_id: str = "dataset-123", + provider: str = "vendor", + name: str = "old_name", + description: str = "old_description", + indexing_technique: str = "high_quality", + retrieval_model: str = "old_model", + embedding_model_provider: Optional[str] = None, + embedding_model: Optional[str] = None, + collection_binding_id: Optional[str] = None, + **kwargs, + ) -> Mock: + """Create a mock dataset with specified attributes.""" + dataset = Mock(spec=Dataset) + dataset.id = dataset_id + dataset.provider = provider + dataset.name = name + dataset.description = description + dataset.indexing_technique = indexing_technique + dataset.retrieval_model = retrieval_model + dataset.embedding_model_provider = embedding_model_provider + dataset.embedding_model = embedding_model + dataset.collection_binding_id = collection_binding_id + for key, value in kwargs.items(): + setattr(dataset, key, value) + return dataset + + @staticmethod + def create_user_mock(user_id: str = "user-789") -> Mock: + """Create a mock user.""" + user = Mock() + user.id = user_id + return user + + @staticmethod + def create_external_binding_mock( + external_knowledge_id: str = "old_knowledge_id", external_knowledge_api_id: str = "old_api_id" + ) -> Mock: + """Create a mock external knowledge binding.""" + binding = Mock(spec=ExternalKnowledgeBindings) + binding.external_knowledge_id = external_knowledge_id + binding.external_knowledge_api_id = external_knowledge_api_id + return binding + + @staticmethod + def create_embedding_model_mock(model: str = "text-embedding-ada-002", provider: str = "openai") -> Mock: + """Create a mock embedding model.""" + embedding_model = Mock() + embedding_model.model = model + embedding_model.provider = provider + return embedding_model + + @staticmethod + def create_collection_binding_mock(binding_id: str = "binding-456") -> Mock: + """Create a mock collection binding.""" + binding = Mock() + binding.id = binding_id + return binding + + @staticmethod + def create_current_user_mock(tenant_id: str = "tenant-123") -> Mock: + """Create a mock current user.""" + current_user = Mock() + current_user.current_tenant_id = tenant_id + return current_user + + +class TestDatasetServiceUpdateDataset: + """ + Comprehensive unit tests for DatasetService.update_dataset method. + + This test suite covers all supported scenarios including: + - External dataset updates + - Internal dataset updates with different indexing techniques + - Embedding model updates + - Permission checks + - Error conditions and edge cases + """ + + @pytest.fixture + def mock_dataset_service_dependencies(self): + """Common mock setup for dataset service dependencies.""" + with ( + patch("services.dataset_service.DatasetService.get_dataset") as mock_get_dataset, + patch("services.dataset_service.DatasetService.check_dataset_permission") as mock_check_perm, + patch("extensions.ext_database.db.session") as mock_db, + patch("services.dataset_service.datetime") as mock_datetime, + ): + current_time = datetime.datetime(2023, 1, 1, 12, 0, 0) + mock_datetime.datetime.now.return_value = current_time + mock_datetime.UTC = datetime.UTC + + yield { + "get_dataset": mock_get_dataset, + "check_permission": mock_check_perm, + "db_session": mock_db, + "datetime": mock_datetime, + "current_time": current_time, + } + + @pytest.fixture + def mock_external_provider_dependencies(self): + """Mock setup for external provider tests.""" + with patch("services.dataset_service.Session") as mock_session: + from extensions.ext_database import db + + with patch.object(db.__class__, "engine", new_callable=Mock): + session_mock = Mock() + mock_session.return_value.__enter__.return_value = session_mock + yield session_mock + + @pytest.fixture + def mock_internal_provider_dependencies(self): + """Mock setup for internal provider tests.""" + with ( + patch("services.dataset_service.ModelManager") as mock_model_manager, + patch( + "services.dataset_service.DatasetCollectionBindingService.get_dataset_collection_binding" + ) as mock_get_binding, + patch("services.dataset_service.deal_dataset_vector_index_task") as mock_task, + patch("services.dataset_service.current_user") as mock_current_user, + ): + mock_current_user.current_tenant_id = "tenant-123" + yield { + "model_manager": mock_model_manager, + "get_binding": mock_get_binding, + "task": mock_task, + "current_user": mock_current_user, + } + + def _assert_database_update_called(self, mock_db, dataset_id: str, expected_updates: dict[str, Any]): + """Helper method to verify database update calls.""" + mock_db.query.return_value.filter_by.return_value.update.assert_called_once_with(expected_updates) + mock_db.commit.assert_called_once() + + def _assert_external_dataset_update(self, mock_dataset, mock_binding, update_data: dict[str, Any]): + """Helper method to verify external dataset updates.""" + assert mock_dataset.name == update_data.get("name", mock_dataset.name) + assert mock_dataset.description == update_data.get("description", mock_dataset.description) + assert mock_dataset.retrieval_model == update_data.get("external_retrieval_model", mock_dataset.retrieval_model) + + if "external_knowledge_id" in update_data: + assert mock_binding.external_knowledge_id == update_data["external_knowledge_id"] + if "external_knowledge_api_id" in update_data: + assert mock_binding.external_knowledge_api_id == update_data["external_knowledge_api_id"] + + # ==================== External Dataset Tests ==================== + + def test_update_external_dataset_success( + self, mock_dataset_service_dependencies, mock_external_provider_dependencies + ): + """Test successful update of external dataset.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock( + provider="external", name="old_name", description="old_description", retrieval_model="old_model" + ) + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + binding = DatasetUpdateTestDataFactory.create_external_binding_mock() + + # Mock external knowledge binding query + mock_external_provider_dependencies.query.return_value.filter_by.return_value.first.return_value = binding + + update_data = { + "name": "new_name", + "description": "new_description", + "external_retrieval_model": "new_model", + "permission": "only_me", + "external_knowledge_id": "new_knowledge_id", + "external_knowledge_api_id": "new_api_id", + } + + result = DatasetService.update_dataset("dataset-123", update_data, user) + + # Verify permission check was called + mock_dataset_service_dependencies["check_permission"].assert_called_once_with(dataset, user) + + # Verify dataset and binding updates + self._assert_external_dataset_update(dataset, binding, update_data) + + # Verify database operations + mock_db = mock_dataset_service_dependencies["db_session"] + mock_db.add.assert_any_call(dataset) + mock_db.add.assert_any_call(binding) + mock_db.commit.assert_called_once() + + # Verify return value + assert result == dataset + + def test_update_external_dataset_missing_knowledge_id_error(self, mock_dataset_service_dependencies): + """Test error when external knowledge id is missing.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock(provider="external") + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + update_data = {"name": "new_name", "external_knowledge_api_id": "api_id"} + + with pytest.raises(ValueError) as context: + DatasetService.update_dataset("dataset-123", update_data, user) + + assert "External knowledge id is required" in str(context.value) + + def test_update_external_dataset_missing_api_id_error(self, mock_dataset_service_dependencies): + """Test error when external knowledge api id is missing.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock(provider="external") + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + update_data = {"name": "new_name", "external_knowledge_id": "knowledge_id"} + + with pytest.raises(ValueError) as context: + DatasetService.update_dataset("dataset-123", update_data, user) + + assert "External knowledge api id is required" in str(context.value) + + def test_update_external_dataset_binding_not_found_error( + self, mock_dataset_service_dependencies, mock_external_provider_dependencies + ): + """Test error when external knowledge binding is not found.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock(provider="external") + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + # Mock external knowledge binding query returning None + mock_external_provider_dependencies.query.return_value.filter_by.return_value.first.return_value = None + + update_data = { + "name": "new_name", + "external_knowledge_id": "knowledge_id", + "external_knowledge_api_id": "api_id", + } + + with pytest.raises(ValueError) as context: + DatasetService.update_dataset("dataset-123", update_data, user) + + assert "External knowledge binding not found" in str(context.value) + + # ==================== Internal Dataset Basic Tests ==================== + + def test_update_internal_dataset_basic_success(self, mock_dataset_service_dependencies): + """Test successful update of internal dataset with basic fields.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock( + provider="vendor", + indexing_technique="high_quality", + embedding_model_provider="openai", + embedding_model="text-embedding-ada-002", + collection_binding_id="binding-123", + ) + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + update_data = { + "name": "new_name", + "description": "new_description", + "indexing_technique": "high_quality", + "retrieval_model": "new_model", + "embedding_model_provider": "openai", + "embedding_model": "text-embedding-ada-002", + } + + result = DatasetService.update_dataset("dataset-123", update_data, user) + + # Verify permission check was called + mock_dataset_service_dependencies["check_permission"].assert_called_once_with(dataset, user) + + # Verify database update was called with correct filtered data + expected_filtered_data = { + "name": "new_name", + "description": "new_description", + "indexing_technique": "high_quality", + "retrieval_model": "new_model", + "embedding_model_provider": "openai", + "embedding_model": "text-embedding-ada-002", + "updated_by": user.id, + "updated_at": mock_dataset_service_dependencies["current_time"].replace(tzinfo=None), + } + + self._assert_database_update_called( + mock_dataset_service_dependencies["db_session"], "dataset-123", expected_filtered_data + ) + + # Verify return value + assert result == dataset + + def test_update_internal_dataset_filter_none_values(self, mock_dataset_service_dependencies): + """Test that None values are filtered out except for description field.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock(provider="vendor", indexing_technique="high_quality") + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + update_data = { + "name": "new_name", + "description": None, # Should be included + "indexing_technique": "high_quality", + "retrieval_model": "new_model", + "embedding_model_provider": None, # Should be filtered out + "embedding_model": None, # Should be filtered out + } + + result = DatasetService.update_dataset("dataset-123", update_data, user) + + # Verify database update was called with filtered data + expected_filtered_data = { + "name": "new_name", + "description": None, # Description should be included even if None + "indexing_technique": "high_quality", + "retrieval_model": "new_model", + "updated_by": user.id, + "updated_at": mock_dataset_service_dependencies["current_time"].replace(tzinfo=None), + } + + actual_call_args = mock_dataset_service_dependencies[ + "db_session" + ].query.return_value.filter_by.return_value.update.call_args[0][0] + # Remove timestamp for comparison as it's dynamic + del actual_call_args["updated_at"] + del expected_filtered_data["updated_at"] + + assert actual_call_args == expected_filtered_data + + # Verify return value + assert result == dataset + + # ==================== Indexing Technique Switch Tests ==================== + + def test_update_internal_dataset_indexing_technique_to_economy( + self, mock_dataset_service_dependencies, mock_internal_provider_dependencies + ): + """Test updating internal dataset indexing technique to economy.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock(provider="vendor", indexing_technique="high_quality") + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + update_data = {"indexing_technique": "economy", "retrieval_model": "new_model"} + + result = DatasetService.update_dataset("dataset-123", update_data, user) + + # Verify database update was called with embedding model fields cleared + expected_filtered_data = { + "indexing_technique": "economy", + "embedding_model": None, + "embedding_model_provider": None, + "collection_binding_id": None, + "retrieval_model": "new_model", + "updated_by": user.id, + "updated_at": mock_dataset_service_dependencies["current_time"].replace(tzinfo=None), + } + + self._assert_database_update_called( + mock_dataset_service_dependencies["db_session"], "dataset-123", expected_filtered_data + ) + + # Verify return value + assert result == dataset + + def test_update_internal_dataset_indexing_technique_to_high_quality( + self, mock_dataset_service_dependencies, mock_internal_provider_dependencies + ): + """Test updating internal dataset indexing technique to high_quality.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock(provider="vendor", indexing_technique="economy") + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + # Mock embedding model + embedding_model = DatasetUpdateTestDataFactory.create_embedding_model_mock() + mock_internal_provider_dependencies[ + "model_manager" + ].return_value.get_model_instance.return_value = embedding_model + + # Mock collection binding + binding = DatasetUpdateTestDataFactory.create_collection_binding_mock() + mock_internal_provider_dependencies["get_binding"].return_value = binding + + update_data = { + "indexing_technique": "high_quality", + "embedding_model_provider": "openai", + "embedding_model": "text-embedding-ada-002", + "retrieval_model": "new_model", + } + + result = DatasetService.update_dataset("dataset-123", update_data, user) + + # Verify embedding model was validated + mock_internal_provider_dependencies["model_manager"].return_value.get_model_instance.assert_called_once_with( + tenant_id=mock_internal_provider_dependencies["current_user"].current_tenant_id, + provider="openai", + model_type=ModelType.TEXT_EMBEDDING, + model="text-embedding-ada-002", + ) + + # Verify collection binding was retrieved + mock_internal_provider_dependencies["get_binding"].assert_called_once_with("openai", "text-embedding-ada-002") + + # Verify database update was called with correct data + expected_filtered_data = { + "indexing_technique": "high_quality", + "embedding_model": "text-embedding-ada-002", + "embedding_model_provider": "openai", + "collection_binding_id": "binding-456", + "retrieval_model": "new_model", + "updated_by": user.id, + "updated_at": mock_dataset_service_dependencies["current_time"].replace(tzinfo=None), + } + + self._assert_database_update_called( + mock_dataset_service_dependencies["db_session"], "dataset-123", expected_filtered_data + ) + + # Verify vector index task was triggered + mock_internal_provider_dependencies["task"].delay.assert_called_once_with("dataset-123", "add") + + # Verify return value + assert result == dataset + + # ==================== Embedding Model Update Tests ==================== + + def test_update_internal_dataset_keep_existing_embedding_model(self, mock_dataset_service_dependencies): + """Test updating internal dataset without changing embedding model.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock( + provider="vendor", + indexing_technique="high_quality", + embedding_model_provider="openai", + embedding_model="text-embedding-ada-002", + collection_binding_id="binding-123", + ) + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + update_data = {"name": "new_name", "indexing_technique": "high_quality", "retrieval_model": "new_model"} + + result = DatasetService.update_dataset("dataset-123", update_data, user) + + # Verify database update was called with existing embedding model preserved + expected_filtered_data = { + "name": "new_name", + "indexing_technique": "high_quality", + "embedding_model_provider": "openai", + "embedding_model": "text-embedding-ada-002", + "collection_binding_id": "binding-123", + "retrieval_model": "new_model", + "updated_by": user.id, + "updated_at": mock_dataset_service_dependencies["current_time"].replace(tzinfo=None), + } + + self._assert_database_update_called( + mock_dataset_service_dependencies["db_session"], "dataset-123", expected_filtered_data + ) + + # Verify return value + assert result == dataset + + def test_update_internal_dataset_embedding_model_update( + self, mock_dataset_service_dependencies, mock_internal_provider_dependencies + ): + """Test updating internal dataset with new embedding model.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock( + provider="vendor", + indexing_technique="high_quality", + embedding_model_provider="openai", + embedding_model="text-embedding-ada-002", + ) + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + # Mock embedding model + embedding_model = DatasetUpdateTestDataFactory.create_embedding_model_mock("text-embedding-3-small") + mock_internal_provider_dependencies[ + "model_manager" + ].return_value.get_model_instance.return_value = embedding_model + + # Mock collection binding + binding = DatasetUpdateTestDataFactory.create_collection_binding_mock("binding-789") + mock_internal_provider_dependencies["get_binding"].return_value = binding + + update_data = { + "indexing_technique": "high_quality", + "embedding_model_provider": "openai", + "embedding_model": "text-embedding-3-small", + "retrieval_model": "new_model", + } + + result = DatasetService.update_dataset("dataset-123", update_data, user) + + # Verify embedding model was validated + mock_internal_provider_dependencies["model_manager"].return_value.get_model_instance.assert_called_once_with( + tenant_id=mock_internal_provider_dependencies["current_user"].current_tenant_id, + provider="openai", + model_type=ModelType.TEXT_EMBEDDING, + model="text-embedding-3-small", + ) + + # Verify collection binding was retrieved + mock_internal_provider_dependencies["get_binding"].assert_called_once_with("openai", "text-embedding-3-small") + + # Verify database update was called with correct data + expected_filtered_data = { + "indexing_technique": "high_quality", + "embedding_model": "text-embedding-3-small", + "embedding_model_provider": "openai", + "collection_binding_id": "binding-789", + "retrieval_model": "new_model", + "updated_by": user.id, + "updated_at": mock_dataset_service_dependencies["current_time"].replace(tzinfo=None), + } + + self._assert_database_update_called( + mock_dataset_service_dependencies["db_session"], "dataset-123", expected_filtered_data + ) + + # Verify vector index task was triggered + mock_internal_provider_dependencies["task"].delay.assert_called_once_with("dataset-123", "update") + + # Verify return value + assert result == dataset + + def test_update_internal_dataset_no_indexing_technique_change(self, mock_dataset_service_dependencies): + """Test updating internal dataset without changing indexing technique.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock( + provider="vendor", + indexing_technique="high_quality", + embedding_model_provider="openai", + embedding_model="text-embedding-ada-002", + collection_binding_id="binding-123", + ) + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + update_data = { + "name": "new_name", + "indexing_technique": "high_quality", # Same as current + "retrieval_model": "new_model", + } + + result = DatasetService.update_dataset("dataset-123", update_data, user) + + # Verify database update was called with correct data + expected_filtered_data = { + "name": "new_name", + "indexing_technique": "high_quality", + "embedding_model_provider": "openai", + "embedding_model": "text-embedding-ada-002", + "collection_binding_id": "binding-123", + "retrieval_model": "new_model", + "updated_by": user.id, + "updated_at": mock_dataset_service_dependencies["current_time"].replace(tzinfo=None), + } + + self._assert_database_update_called( + mock_dataset_service_dependencies["db_session"], "dataset-123", expected_filtered_data + ) + + # Verify return value + assert result == dataset + + # ==================== Error Handling Tests ==================== + + def test_update_dataset_not_found_error(self, mock_dataset_service_dependencies): + """Test error when dataset is not found.""" + mock_dataset_service_dependencies["get_dataset"].return_value = None + + user = DatasetUpdateTestDataFactory.create_user_mock() + update_data = {"name": "new_name"} + + with pytest.raises(ValueError) as context: + DatasetService.update_dataset("dataset-123", update_data, user) + + assert "Dataset not found" in str(context.value) + + def test_update_dataset_permission_error(self, mock_dataset_service_dependencies): + """Test error when user doesn't have permission.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock() + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + mock_dataset_service_dependencies["check_permission"].side_effect = NoPermissionError("No permission") + + update_data = {"name": "new_name"} + + with pytest.raises(NoPermissionError): + DatasetService.update_dataset("dataset-123", update_data, user) + + def test_update_internal_dataset_embedding_model_error( + self, mock_dataset_service_dependencies, mock_internal_provider_dependencies + ): + """Test error when embedding model is not available.""" + dataset = DatasetUpdateTestDataFactory.create_dataset_mock(provider="vendor", indexing_technique="economy") + mock_dataset_service_dependencies["get_dataset"].return_value = dataset + + user = DatasetUpdateTestDataFactory.create_user_mock() + + # Mock model manager to raise error + mock_internal_provider_dependencies["model_manager"].return_value.get_model_instance.side_effect = Exception( + "No Embedding Model available" + ) + + update_data = { + "indexing_technique": "high_quality", + "embedding_model_provider": "invalid_provider", + "embedding_model": "invalid_model", + "retrieval_model": "new_model", + } + + with pytest.raises(Exception) as context: + DatasetService.update_dataset("dataset-123", update_data, user) + + assert "No Embedding Model available".lower() in str(context.value).lower() diff --git a/api/tests/unit_tests/services/workflow/test_workflow_draft_variable_service.py b/api/tests/unit_tests/services/workflow/test_workflow_draft_variable_service.py new file mode 100644 index 0000000000..c5c9cf1050 --- /dev/null +++ b/api/tests/unit_tests/services/workflow/test_workflow_draft_variable_service.py @@ -0,0 +1,373 @@ +import dataclasses +import secrets +from unittest import mock +from unittest.mock import Mock, patch + +import pytest +from sqlalchemy.orm import Session + +from core.variables import StringSegment +from core.workflow.constants import SYSTEM_VARIABLE_NODE_ID +from core.workflow.nodes import NodeType +from models.enums import DraftVariableType +from models.workflow import Workflow, WorkflowDraftVariable, WorkflowNodeExecutionModel, is_system_variable_editable +from services.workflow_draft_variable_service import ( + DraftVariableSaver, + VariableResetError, + WorkflowDraftVariableService, +) + + +class TestDraftVariableSaver: + def _get_test_app_id(self): + suffix = secrets.token_hex(6) + return f"test_app_id_{suffix}" + + def test__should_variable_be_visible(self): + mock_session = mock.MagicMock(spec=Session) + test_app_id = self._get_test_app_id() + saver = DraftVariableSaver( + session=mock_session, + app_id=test_app_id, + node_id="test_node_id", + node_type=NodeType.START, + node_execution_id="test_execution_id", + ) + assert saver._should_variable_be_visible("123_456", NodeType.IF_ELSE, "output") == False + assert saver._should_variable_be_visible("123", NodeType.START, "output") == True + + def test__normalize_variable_for_start_node(self): + @dataclasses.dataclass(frozen=True) + class TestCase: + name: str + input_node_id: str + input_name: str + expected_node_id: str + expected_name: str + + _NODE_ID = "1747228642872" + cases = [ + TestCase( + name="name with `sys.` prefix should return the system node_id", + input_node_id=_NODE_ID, + input_name="sys.workflow_id", + expected_node_id=SYSTEM_VARIABLE_NODE_ID, + expected_name="workflow_id", + ), + TestCase( + name="name without `sys.` prefix should return the original input node_id", + input_node_id=_NODE_ID, + input_name="start_input", + expected_node_id=_NODE_ID, + expected_name="start_input", + ), + TestCase( + name="dummy_variable should return the original input node_id", + input_node_id=_NODE_ID, + input_name="__dummy__", + expected_node_id=_NODE_ID, + expected_name="__dummy__", + ), + ] + + mock_session = mock.MagicMock(spec=Session) + test_app_id = self._get_test_app_id() + saver = DraftVariableSaver( + session=mock_session, + app_id=test_app_id, + node_id=_NODE_ID, + node_type=NodeType.START, + node_execution_id="test_execution_id", + ) + for idx, c in enumerate(cases, 1): + fail_msg = f"Test case {c.name} failed, index={idx}" + node_id, name = saver._normalize_variable_for_start_node(c.input_name) + assert node_id == c.expected_node_id, fail_msg + assert name == c.expected_name, fail_msg + + +class TestWorkflowDraftVariableService: + def _get_test_app_id(self): + suffix = secrets.token_hex(6) + return f"test_app_id_{suffix}" + + def _create_test_workflow(self, app_id: str) -> Workflow: + """Create a real Workflow instance for testing""" + return Workflow.new( + tenant_id="test_tenant_id", + app_id=app_id, + type="workflow", + version="draft", + graph='{"nodes": [], "edges": []}', + features="{}", + created_by="test_user_id", + environment_variables=[], + conversation_variables=[], + ) + + def test_reset_conversation_variable(self): + """Test resetting a conversation variable""" + mock_session = Mock(spec=Session) + service = WorkflowDraftVariableService(mock_session) + + test_app_id = self._get_test_app_id() + workflow = self._create_test_workflow(test_app_id) + + # Create real conversation variable + test_value = StringSegment(value="test_value") + variable = WorkflowDraftVariable.new_conversation_variable( + app_id=test_app_id, name="test_var", value=test_value, description="Test conversation variable" + ) + + # Mock the _reset_conv_var method + expected_result = WorkflowDraftVariable.new_conversation_variable( + app_id=test_app_id, + name="test_var", + value=StringSegment(value="reset_value"), + ) + with patch.object(service, "_reset_conv_var", return_value=expected_result) as mock_reset_conv: + result = service.reset_variable(workflow, variable) + + mock_reset_conv.assert_called_once_with(workflow, variable) + assert result == expected_result + + def test_reset_node_variable_with_no_execution_id(self): + """Test resetting a node variable with no execution ID - should delete variable""" + mock_session = Mock(spec=Session) + service = WorkflowDraftVariableService(mock_session) + + test_app_id = self._get_test_app_id() + workflow = self._create_test_workflow(test_app_id) + + # Create real node variable with no execution ID + test_value = StringSegment(value="test_value") + variable = WorkflowDraftVariable.new_node_variable( + app_id=test_app_id, + node_id="test_node_id", + name="test_var", + value=test_value, + node_execution_id="exec-id", # Set initially + ) + # Manually set to None to simulate the test condition + variable.node_execution_id = None + + result = service._reset_node_var_or_sys_var(workflow, variable) + + # Should delete the variable and return None + mock_session.delete.assert_called_once_with(instance=variable) + mock_session.flush.assert_called_once() + assert result is None + + def test_reset_node_variable_with_missing_execution_record(self): + """Test resetting a node variable when execution record doesn't exist""" + mock_session = Mock(spec=Session) + service = WorkflowDraftVariableService(mock_session) + + test_app_id = self._get_test_app_id() + workflow = self._create_test_workflow(test_app_id) + + # Create real node variable with execution ID + test_value = StringSegment(value="test_value") + variable = WorkflowDraftVariable.new_node_variable( + app_id=test_app_id, node_id="test_node_id", name="test_var", value=test_value, node_execution_id="exec-id" + ) + + # Mock session.scalars to return None (no execution record found) + mock_scalars = Mock() + mock_scalars.first.return_value = None + mock_session.scalars.return_value = mock_scalars + + result = service._reset_node_var_or_sys_var(workflow, variable) + + # Should delete the variable and return None + mock_session.delete.assert_called_once_with(instance=variable) + mock_session.flush.assert_called_once() + assert result is None + + def test_reset_node_variable_with_valid_execution_record(self): + """Test resetting a node variable with valid execution record - should restore from execution""" + mock_session = Mock(spec=Session) + service = WorkflowDraftVariableService(mock_session) + + test_app_id = self._get_test_app_id() + workflow = self._create_test_workflow(test_app_id) + + # Create real node variable with execution ID + test_value = StringSegment(value="original_value") + variable = WorkflowDraftVariable.new_node_variable( + app_id=test_app_id, node_id="test_node_id", name="test_var", value=test_value, node_execution_id="exec-id" + ) + + # Create mock execution record + mock_execution = Mock(spec=WorkflowNodeExecutionModel) + mock_execution.process_data_dict = {"test_var": "process_value"} + mock_execution.outputs_dict = {"test_var": "output_value"} + + # Mock session.scalars to return the execution record + mock_scalars = Mock() + mock_scalars.first.return_value = mock_execution + mock_session.scalars.return_value = mock_scalars + + # Mock workflow methods + mock_node_config = {"type": "test_node"} + with ( + patch.object(workflow, "get_node_config_by_id", return_value=mock_node_config), + patch.object(workflow, "get_node_type_from_node_config", return_value=NodeType.LLM), + ): + result = service._reset_node_var_or_sys_var(workflow, variable) + + # Verify last_edited_at was reset + assert variable.last_edited_at is None + # Verify session.flush was called + mock_session.flush.assert_called() + + # Should return the updated variable + assert result == variable + + def test_reset_non_editable_system_variable_raises_error(self): + """Test that resetting a non-editable system variable raises an error""" + mock_session = Mock(spec=Session) + service = WorkflowDraftVariableService(mock_session) + + test_app_id = self._get_test_app_id() + workflow = self._create_test_workflow(test_app_id) + + # Create a non-editable system variable (workflow_id is not editable) + test_value = StringSegment(value="test_workflow_id") + variable = WorkflowDraftVariable.new_sys_variable( + app_id=test_app_id, + name="workflow_id", # This is not in _EDITABLE_SYSTEM_VARIABLE + value=test_value, + node_execution_id="exec-id", + editable=False, # Non-editable system variable + ) + + # Mock the service to properly check system variable editability + with patch.object(service, "reset_variable") as mock_reset: + + def side_effect(wf, var): + if var.get_variable_type() == DraftVariableType.SYS and not is_system_variable_editable(var.name): + raise VariableResetError(f"cannot reset system variable, variable_id={var.id}") + return var + + mock_reset.side_effect = side_effect + + with pytest.raises(VariableResetError) as exc_info: + service.reset_variable(workflow, variable) + assert "cannot reset system variable" in str(exc_info.value) + assert f"variable_id={variable.id}" in str(exc_info.value) + + def test_reset_editable_system_variable_succeeds(self): + """Test that resetting an editable system variable succeeds""" + mock_session = Mock(spec=Session) + service = WorkflowDraftVariableService(mock_session) + + test_app_id = self._get_test_app_id() + workflow = self._create_test_workflow(test_app_id) + + # Create an editable system variable (files is editable) + test_value = StringSegment(value="[]") + variable = WorkflowDraftVariable.new_sys_variable( + app_id=test_app_id, + name="files", # This is in _EDITABLE_SYSTEM_VARIABLE + value=test_value, + node_execution_id="exec-id", + editable=True, # Editable system variable + ) + + # Create mock execution record + mock_execution = Mock(spec=WorkflowNodeExecutionModel) + mock_execution.outputs_dict = {"sys.files": "[]"} + + # Mock session.scalars to return the execution record + mock_scalars = Mock() + mock_scalars.first.return_value = mock_execution + mock_session.scalars.return_value = mock_scalars + + result = service._reset_node_var_or_sys_var(workflow, variable) + + # Should succeed and return the variable + assert result == variable + assert variable.last_edited_at is None + mock_session.flush.assert_called() + + def test_reset_query_system_variable_succeeds(self): + """Test that resetting query system variable (another editable one) succeeds""" + mock_session = Mock(spec=Session) + service = WorkflowDraftVariableService(mock_session) + + test_app_id = self._get_test_app_id() + workflow = self._create_test_workflow(test_app_id) + + # Create an editable system variable (query is editable) + test_value = StringSegment(value="original query") + variable = WorkflowDraftVariable.new_sys_variable( + app_id=test_app_id, + name="query", # This is in _EDITABLE_SYSTEM_VARIABLE + value=test_value, + node_execution_id="exec-id", + editable=True, # Editable system variable + ) + + # Create mock execution record + mock_execution = Mock(spec=WorkflowNodeExecutionModel) + mock_execution.outputs_dict = {"sys.query": "reset query"} + + # Mock session.scalars to return the execution record + mock_scalars = Mock() + mock_scalars.first.return_value = mock_execution + mock_session.scalars.return_value = mock_scalars + + result = service._reset_node_var_or_sys_var(workflow, variable) + + # Should succeed and return the variable + assert result == variable + assert variable.last_edited_at is None + mock_session.flush.assert_called() + + def test_system_variable_editability_check(self): + """Test the system variable editability function directly""" + # Test editable system variables + assert is_system_variable_editable("files") == True + assert is_system_variable_editable("query") == True + + # Test non-editable system variables + assert is_system_variable_editable("workflow_id") == False + assert is_system_variable_editable("conversation_id") == False + assert is_system_variable_editable("user_id") == False + + def test_workflow_draft_variable_factory_methods(self): + """Test that factory methods create proper instances""" + test_app_id = self._get_test_app_id() + test_value = StringSegment(value="test_value") + + # Test conversation variable factory + conv_var = WorkflowDraftVariable.new_conversation_variable( + app_id=test_app_id, name="conv_var", value=test_value, description="Test conversation variable" + ) + assert conv_var.get_variable_type() == DraftVariableType.CONVERSATION + assert conv_var.editable == True + assert conv_var.node_execution_id is None + + # Test system variable factory + sys_var = WorkflowDraftVariable.new_sys_variable( + app_id=test_app_id, name="workflow_id", value=test_value, node_execution_id="exec-id", editable=False + ) + assert sys_var.get_variable_type() == DraftVariableType.SYS + assert sys_var.editable == False + assert sys_var.node_execution_id == "exec-id" + + # Test node variable factory + node_var = WorkflowDraftVariable.new_node_variable( + app_id=test_app_id, + node_id="node-id", + name="node_var", + value=test_value, + node_execution_id="exec-id", + visible=True, + editable=True, + ) + assert node_var.get_variable_type() == DraftVariableType.NODE + assert node_var.visible == True + assert node_var.editable == True + assert node_var.node_execution_id == "exec-id" diff --git a/api/tests/unit_tests/utils/http_parser/test_oauth_convert_request_to_raw_data.py b/api/tests/unit_tests/utils/http_parser/test_oauth_convert_request_to_raw_data.py index f788a9756b..293ac253f5 100644 --- a/api/tests/unit_tests/utils/http_parser/test_oauth_convert_request_to_raw_data.py +++ b/api/tests/unit_tests/utils/http_parser/test_oauth_convert_request_to_raw_data.py @@ -1,3 +1,5 @@ +import json + from werkzeug import Request from werkzeug.datastructures import Headers from werkzeug.test import EnvironBuilder @@ -15,6 +17,59 @@ def test_oauth_convert_request_to_raw_data(): request = Request(builder.get_environ()) raw_request_bytes = oauth_handler._convert_request_to_raw_data(request) - assert b"GET /test HTTP/1.1" in raw_request_bytes + assert b"GET /test? HTTP/1.1" in raw_request_bytes + assert b"Content-Type: application/json" in raw_request_bytes + assert b"\r\n\r\n" in raw_request_bytes + + +def test_oauth_convert_request_to_raw_data_with_query_params(): + oauth_handler = OAuthHandler() + builder = EnvironBuilder( + method="GET", + path="/test", + query_string="code=abc123&state=xyz789", + headers=Headers({"Content-Type": "application/json"}), + ) + request = Request(builder.get_environ()) + raw_request_bytes = oauth_handler._convert_request_to_raw_data(request) + + assert b"GET /test?code=abc123&state=xyz789 HTTP/1.1" in raw_request_bytes + assert b"Content-Type: application/json" in raw_request_bytes + assert b"\r\n\r\n" in raw_request_bytes + + +def test_oauth_convert_request_to_raw_data_with_post_body(): + oauth_handler = OAuthHandler() + builder = EnvironBuilder( + method="POST", + path="/test", + data="param1=value1¶m2=value2", + headers=Headers({"Content-Type": "application/x-www-form-urlencoded"}), + ) + request = Request(builder.get_environ()) + raw_request_bytes = oauth_handler._convert_request_to_raw_data(request) + + assert b"POST /test? HTTP/1.1" in raw_request_bytes + assert b"Content-Type: application/x-www-form-urlencoded" in raw_request_bytes + assert b"\r\n\r\n" in raw_request_bytes + assert b"param1=value1¶m2=value2" in raw_request_bytes + + +def test_oauth_convert_request_to_raw_data_with_json_body(): + oauth_handler = OAuthHandler() + json_data = {"code": "abc123", "state": "xyz789", "grant_type": "authorization_code"} + builder = EnvironBuilder( + method="POST", + path="/test", + data=json.dumps(json_data), + headers=Headers({"Content-Type": "application/json"}), + ) + request = Request(builder.get_environ()) + raw_request_bytes = oauth_handler._convert_request_to_raw_data(request) + + assert b"POST /test? HTTP/1.1" in raw_request_bytes assert b"Content-Type: application/json" in raw_request_bytes assert b"\r\n\r\n" in raw_request_bytes + assert b'"code": "abc123"' in raw_request_bytes + assert b'"state": "xyz789"' in raw_request_bytes + assert b'"grant_type": "authorization_code"' in raw_request_bytes diff --git a/api/tests/unit_tests/utils/structured_output_parser/__init__.py b/api/tests/unit_tests/utils/structured_output_parser/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/tests/unit_tests/utils/structured_output_parser/test_structured_output_parser.py b/api/tests/unit_tests/utils/structured_output_parser/test_structured_output_parser.py new file mode 100644 index 0000000000..728c58fc5b --- /dev/null +++ b/api/tests/unit_tests/utils/structured_output_parser/test_structured_output_parser.py @@ -0,0 +1,465 @@ +from decimal import Decimal +from unittest.mock import MagicMock, patch + +import pytest + +from core.llm_generator.output_parser.errors import OutputParserError +from core.llm_generator.output_parser.structured_output import invoke_llm_with_structured_output +from core.model_runtime.entities.llm_entities import ( + LLMResult, + LLMResultChunk, + LLMResultChunkDelta, + LLMResultChunkWithStructuredOutput, + LLMResultWithStructuredOutput, + LLMUsage, +) +from core.model_runtime.entities.message_entities import ( + AssistantPromptMessage, + SystemPromptMessage, + TextPromptMessageContent, + UserPromptMessage, +) +from core.model_runtime.entities.model_entities import AIModelEntity, ModelType + + +def create_mock_usage(prompt_tokens: int = 10, completion_tokens: int = 5) -> LLMUsage: + """Create a mock LLMUsage with all required fields""" + return LLMUsage( + prompt_tokens=prompt_tokens, + prompt_unit_price=Decimal("0.001"), + prompt_price_unit=Decimal("1"), + prompt_price=Decimal(str(prompt_tokens)) * Decimal("0.001"), + completion_tokens=completion_tokens, + completion_unit_price=Decimal("0.002"), + completion_price_unit=Decimal("1"), + completion_price=Decimal(str(completion_tokens)) * Decimal("0.002"), + total_tokens=prompt_tokens + completion_tokens, + total_price=Decimal(str(prompt_tokens)) * Decimal("0.001") + Decimal(str(completion_tokens)) * Decimal("0.002"), + currency="USD", + latency=1.5, + ) + + +def get_model_entity(provider: str, model_name: str, support_structure_output: bool = False) -> AIModelEntity: + """Create a mock AIModelEntity for testing""" + model_schema = MagicMock() + model_schema.model = model_name + model_schema.provider = provider + model_schema.model_type = ModelType.LLM + model_schema.model_provider = provider + model_schema.model_name = model_name + model_schema.support_structure_output = support_structure_output + model_schema.parameter_rules = [] + + return model_schema + + +def get_model_instance() -> MagicMock: + """Create a mock ModelInstance for testing""" + mock_instance = MagicMock() + mock_instance.provider = "openai" + mock_instance.credentials = {} + return mock_instance + + +def test_structured_output_parser(): + """Test cases for invoke_llm_with_structured_output function""" + + testcases = [ + # Test case 1: Model with native structured output support, non-streaming + { + "name": "native_structured_output_non_streaming", + "provider": "openai", + "model_name": "gpt-4o", + "support_structure_output": True, + "stream": False, + "json_schema": {"type": "object", "properties": {"name": {"type": "string"}}}, + "expected_llm_response": LLMResult( + model="gpt-4o", + message=AssistantPromptMessage(content='{"name": "test"}'), + usage=create_mock_usage(prompt_tokens=10, completion_tokens=5), + ), + "expected_result_type": LLMResultWithStructuredOutput, + "should_raise": False, + }, + # Test case 2: Model with native structured output support, streaming + { + "name": "native_structured_output_streaming", + "provider": "openai", + "model_name": "gpt-4o", + "support_structure_output": True, + "stream": True, + "json_schema": {"type": "object", "properties": {"name": {"type": "string"}}}, + "expected_llm_response": [ + LLMResultChunk( + model="gpt-4o", + prompt_messages=[UserPromptMessage(content="test")], + system_fingerprint="test", + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage(content='{"name":'), + usage=create_mock_usage(prompt_tokens=10, completion_tokens=2), + ), + ), + LLMResultChunk( + model="gpt-4o", + prompt_messages=[UserPromptMessage(content="test")], + system_fingerprint="test", + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage(content=' "test"}'), + usage=create_mock_usage(prompt_tokens=10, completion_tokens=3), + ), + ), + ], + "expected_result_type": "generator", + "should_raise": False, + }, + # Test case 3: Model without native structured output support, non-streaming + { + "name": "prompt_based_structured_output_non_streaming", + "provider": "anthropic", + "model_name": "claude-3-sonnet", + "support_structure_output": False, + "stream": False, + "json_schema": {"type": "object", "properties": {"answer": {"type": "string"}}}, + "expected_llm_response": LLMResult( + model="claude-3-sonnet", + message=AssistantPromptMessage(content='{"answer": "test response"}'), + usage=create_mock_usage(prompt_tokens=15, completion_tokens=8), + ), + "expected_result_type": LLMResultWithStructuredOutput, + "should_raise": False, + }, + # Test case 4: Model without native structured output support, streaming + { + "name": "prompt_based_structured_output_streaming", + "provider": "anthropic", + "model_name": "claude-3-sonnet", + "support_structure_output": False, + "stream": True, + "json_schema": {"type": "object", "properties": {"answer": {"type": "string"}}}, + "expected_llm_response": [ + LLMResultChunk( + model="claude-3-sonnet", + prompt_messages=[UserPromptMessage(content="test")], + system_fingerprint="test", + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage(content='{"answer": "test'), + usage=create_mock_usage(prompt_tokens=15, completion_tokens=3), + ), + ), + LLMResultChunk( + model="claude-3-sonnet", + prompt_messages=[UserPromptMessage(content="test")], + system_fingerprint="test", + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage(content=' response"}'), + usage=create_mock_usage(prompt_tokens=15, completion_tokens=5), + ), + ), + ], + "expected_result_type": "generator", + "should_raise": False, + }, + # Test case 5: Streaming with list content + { + "name": "streaming_with_list_content", + "provider": "openai", + "model_name": "gpt-4o", + "support_structure_output": True, + "stream": True, + "json_schema": {"type": "object", "properties": {"data": {"type": "string"}}}, + "expected_llm_response": [ + LLMResultChunk( + model="gpt-4o", + prompt_messages=[UserPromptMessage(content="test")], + system_fingerprint="test", + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage( + content=[ + TextPromptMessageContent(data='{"data":'), + ] + ), + usage=create_mock_usage(prompt_tokens=10, completion_tokens=2), + ), + ), + LLMResultChunk( + model="gpt-4o", + prompt_messages=[UserPromptMessage(content="test")], + system_fingerprint="test", + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage( + content=[ + TextPromptMessageContent(data=' "value"}'), + ] + ), + usage=create_mock_usage(prompt_tokens=10, completion_tokens=3), + ), + ), + ], + "expected_result_type": "generator", + "should_raise": False, + }, + # Test case 6: Error case - non-string LLM response content (non-streaming) + { + "name": "error_non_string_content_non_streaming", + "provider": "openai", + "model_name": "gpt-4o", + "support_structure_output": True, + "stream": False, + "json_schema": {"type": "object", "properties": {"name": {"type": "string"}}}, + "expected_llm_response": LLMResult( + model="gpt-4o", + message=AssistantPromptMessage(content=None), # Non-string content + usage=create_mock_usage(prompt_tokens=10, completion_tokens=5), + ), + "expected_result_type": None, + "should_raise": True, + "expected_error": OutputParserError, + }, + # Test case 7: JSON repair scenario + { + "name": "json_repair_scenario", + "provider": "openai", + "model_name": "gpt-4o", + "support_structure_output": True, + "stream": False, + "json_schema": {"type": "object", "properties": {"name": {"type": "string"}}}, + "expected_llm_response": LLMResult( + model="gpt-4o", + message=AssistantPromptMessage(content='{"name": "test"'), # Invalid JSON - missing closing brace + usage=create_mock_usage(prompt_tokens=10, completion_tokens=5), + ), + "expected_result_type": LLMResultWithStructuredOutput, + "should_raise": False, + }, + # Test case 8: Model with parameter rules for response format + { + "name": "model_with_parameter_rules", + "provider": "openai", + "model_name": "gpt-4o", + "support_structure_output": True, + "stream": False, + "json_schema": {"type": "object", "properties": {"result": {"type": "string"}}}, + "parameter_rules": [ + MagicMock(name="response_format", options=["json_schema"], required=False), + ], + "expected_llm_response": LLMResult( + model="gpt-4o", + message=AssistantPromptMessage(content='{"result": "success"}'), + usage=create_mock_usage(prompt_tokens=10, completion_tokens=5), + ), + "expected_result_type": LLMResultWithStructuredOutput, + "should_raise": False, + }, + # Test case 9: Model without native support but with JSON response format rules + { + "name": "non_native_with_json_rules", + "provider": "anthropic", + "model_name": "claude-3-sonnet", + "support_structure_output": False, + "stream": False, + "json_schema": {"type": "object", "properties": {"output": {"type": "string"}}}, + "parameter_rules": [ + MagicMock(name="response_format", options=["JSON"], required=False), + ], + "expected_llm_response": LLMResult( + model="claude-3-sonnet", + message=AssistantPromptMessage(content='{"output": "result"}'), + usage=create_mock_usage(prompt_tokens=15, completion_tokens=8), + ), + "expected_result_type": LLMResultWithStructuredOutput, + "should_raise": False, + }, + ] + + for case in testcases: + print(f"Running test case: {case['name']}") + + # Setup model entity + model_schema = get_model_entity(case["provider"], case["model_name"], case["support_structure_output"]) + + # Add parameter rules if specified + if "parameter_rules" in case: + model_schema.parameter_rules = case["parameter_rules"] + + # Setup model instance + model_instance = get_model_instance() + model_instance.invoke_llm.return_value = case["expected_llm_response"] + + # Setup prompt messages + prompt_messages = [ + SystemPromptMessage(content="You are a helpful assistant."), + UserPromptMessage(content="Generate a response according to the schema."), + ] + + if case["should_raise"]: + # Test error cases + with pytest.raises(case["expected_error"]): # noqa: PT012 + if case["stream"]: + result_generator = invoke_llm_with_structured_output( + provider=case["provider"], + model_schema=model_schema, + model_instance=model_instance, + prompt_messages=prompt_messages, + json_schema=case["json_schema"], + stream=case["stream"], + ) + # Consume the generator to trigger the error + list(result_generator) + else: + invoke_llm_with_structured_output( + provider=case["provider"], + model_schema=model_schema, + model_instance=model_instance, + prompt_messages=prompt_messages, + json_schema=case["json_schema"], + stream=case["stream"], + ) + else: + # Test successful cases + with patch("core.llm_generator.output_parser.structured_output.json_repair.loads") as mock_json_repair: + # Configure json_repair mock for cases that need it + if case["name"] == "json_repair_scenario": + mock_json_repair.return_value = {"name": "test"} + + result = invoke_llm_with_structured_output( + provider=case["provider"], + model_schema=model_schema, + model_instance=model_instance, + prompt_messages=prompt_messages, + json_schema=case["json_schema"], + stream=case["stream"], + model_parameters={"temperature": 0.7, "max_tokens": 100}, + user="test_user", + ) + + if case["expected_result_type"] == "generator": + # Test streaming results + assert hasattr(result, "__iter__") + chunks = list(result) + assert len(chunks) > 0 + + # Verify all chunks are LLMResultChunkWithStructuredOutput + for chunk in chunks[:-1]: # All except last + assert isinstance(chunk, LLMResultChunkWithStructuredOutput) + assert chunk.model == case["model_name"] + + # Last chunk should have structured output + last_chunk = chunks[-1] + assert isinstance(last_chunk, LLMResultChunkWithStructuredOutput) + assert last_chunk.structured_output is not None + assert isinstance(last_chunk.structured_output, dict) + else: + # Test non-streaming results + assert isinstance(result, case["expected_result_type"]) + assert result.model == case["model_name"] + assert result.structured_output is not None + assert isinstance(result.structured_output, dict) + + # Verify model_instance.invoke_llm was called with correct parameters + model_instance.invoke_llm.assert_called_once() + call_args = model_instance.invoke_llm.call_args + + assert call_args.kwargs["stream"] == case["stream"] + assert call_args.kwargs["user"] == "test_user" + assert "temperature" in call_args.kwargs["model_parameters"] + assert "max_tokens" in call_args.kwargs["model_parameters"] + + +def test_parse_structured_output_edge_cases(): + """Test edge cases for structured output parsing""" + + # Test case with list that contains dict (reasoning model scenario) + testcase_list_with_dict = { + "name": "list_with_dict_parsing", + "provider": "deepseek", + "model_name": "deepseek-r1", + "support_structure_output": False, + "stream": False, + "json_schema": {"type": "object", "properties": {"thought": {"type": "string"}}}, + "expected_llm_response": LLMResult( + model="deepseek-r1", + message=AssistantPromptMessage(content='[{"thought": "reasoning process"}, "other content"]'), + usage=create_mock_usage(prompt_tokens=10, completion_tokens=5), + ), + "expected_result_type": LLMResultWithStructuredOutput, + "should_raise": False, + } + + # Setup for list parsing test + model_schema = get_model_entity( + testcase_list_with_dict["provider"], + testcase_list_with_dict["model_name"], + testcase_list_with_dict["support_structure_output"], + ) + + model_instance = get_model_instance() + model_instance.invoke_llm.return_value = testcase_list_with_dict["expected_llm_response"] + + prompt_messages = [UserPromptMessage(content="Test reasoning")] + + with patch("core.llm_generator.output_parser.structured_output.json_repair.loads") as mock_json_repair: + # Mock json_repair to return a list with dict + mock_json_repair.return_value = [{"thought": "reasoning process"}, "other content"] + + result = invoke_llm_with_structured_output( + provider=testcase_list_with_dict["provider"], + model_schema=model_schema, + model_instance=model_instance, + prompt_messages=prompt_messages, + json_schema=testcase_list_with_dict["json_schema"], + stream=testcase_list_with_dict["stream"], + ) + + assert isinstance(result, LLMResultWithStructuredOutput) + assert result.structured_output == {"thought": "reasoning process"} + + +def test_model_specific_schema_preparation(): + """Test schema preparation for different model types""" + + # Test Gemini model + gemini_case = { + "provider": "google", + "model_name": "gemini-pro", + "support_structure_output": True, + "stream": False, + "json_schema": {"type": "object", "properties": {"result": {"type": "boolean"}}, "additionalProperties": False}, + } + + model_schema = get_model_entity( + gemini_case["provider"], gemini_case["model_name"], gemini_case["support_structure_output"] + ) + + model_instance = get_model_instance() + model_instance.invoke_llm.return_value = LLMResult( + model="gemini-pro", + message=AssistantPromptMessage(content='{"result": "true"}'), + usage=create_mock_usage(prompt_tokens=10, completion_tokens=5), + ) + + prompt_messages = [UserPromptMessage(content="Test")] + + result = invoke_llm_with_structured_output( + provider=gemini_case["provider"], + model_schema=model_schema, + model_instance=model_instance, + prompt_messages=prompt_messages, + json_schema=gemini_case["json_schema"], + stream=gemini_case["stream"], + ) + + assert isinstance(result, LLMResultWithStructuredOutput) + + # Verify model_instance.invoke_llm was called and check the schema preparation + model_instance.invoke_llm.assert_called_once() + call_args = model_instance.invoke_llm.call_args + + # For Gemini, the schema should not have additionalProperties and boolean should be converted to string + assert "json_schema" in call_args.kwargs["model_parameters"] diff --git a/api/uv.lock b/api/uv.lock index c900191ceb..d379f28e52 100644 --- a/api/uv.lock +++ b/api/uv.lock @@ 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a/docker/.env.example b/docker/.env.example index 020deb6881..a403f25cb2 100644 --- a/docker/.env.example +++ b/docker/.env.example @@ -285,6 +285,7 @@ BROKER_USE_SSL=false # If you are using Redis Sentinel for high availability, configure the following settings. CELERY_USE_SENTINEL=false CELERY_SENTINEL_MASTER_NAME= +CELERY_SENTINEL_PASSWORD= CELERY_SENTINEL_SOCKET_TIMEOUT=0.1 # ------------------------------ @@ -399,7 +400,7 @@ SUPABASE_URL=your-server-url # ------------------------------ # The type of vector store to use. -# Supported values are `weaviate`, `qdrant`, `milvus`, `myscale`, `relyt`, `pgvector`, `pgvecto-rs`, `chroma`, `opensearch`, `oracle`, `tencent`, `elasticsearch`, `elasticsearch-ja`, `analyticdb`, `couchbase`, `vikingdb`, `oceanbase`, `opengauss`, `tablestore`,`vastbase`,`tidb`,`tidb_on_qdrant`,`baidu`,`lindorm`,`huawei_cloud`,`upstash`. +# Supported values are `weaviate`, `qdrant`, `milvus`, `myscale`, `relyt`, `pgvector`, `pgvecto-rs`, `chroma`, `opensearch`, `oracle`, `tencent`, `elasticsearch`, `elasticsearch-ja`, `analyticdb`, `couchbase`, `vikingdb`, `oceanbase`, `opengauss`, `tablestore`,`vastbase`,`tidb`,`tidb_on_qdrant`,`baidu`,`lindorm`,`huawei_cloud`,`upstash`, `matrixone`. VECTOR_STORE=weaviate # The Weaviate endpoint URL. Only available when VECTOR_STORE is `weaviate`. @@ -490,6 +491,13 @@ TIDB_VECTOR_USER= TIDB_VECTOR_PASSWORD= TIDB_VECTOR_DATABASE=dify +# Matrixone vector configurations. +MATRIXONE_HOST=matrixone +MATRIXONE_PORT=6001 +MATRIXONE_USER=dump +MATRIXONE_PASSWORD=111 +MATRIXONE_DATABASE=dify + # Tidb on qdrant configuration, only available when VECTOR_STORE is `tidb_on_qdrant` TIDB_ON_QDRANT_URL=http://127.0.0.1 TIDB_ON_QDRANT_API_KEY=dify @@ -719,10 +727,11 @@ NOTION_INTERNAL_SECRET= # Mail related configuration # ------------------------------ -# Mail type, support: resend, smtp +# Mail type, support: resend, smtp, sendgrid MAIL_TYPE=resend # Default send from email address, if not specified +# If using SendGrid, use the 'from' field for authentication if necessary. MAIL_DEFAULT_SEND_FROM= # API-Key for the Resend email provider, used when MAIL_TYPE is `resend`. @@ -738,6 +747,9 @@ SMTP_PASSWORD= SMTP_USE_TLS=true SMTP_OPPORTUNISTIC_TLS=false +# Sendgid configuration +SENDGRID_API_KEY= + # ------------------------------ # Others Configuration # ------------------------------ @@ -787,6 +799,9 @@ HTTP_REQUEST_NODE_MAX_BINARY_SIZE=10485760 HTTP_REQUEST_NODE_MAX_TEXT_SIZE=1048576 HTTP_REQUEST_NODE_SSL_VERIFY=True +# Respect X-* headers to redirect clients +RESPECT_XFORWARD_HEADERS_ENABLED=false + # SSRF Proxy server HTTP URL SSRF_PROXY_HTTP_URL=http://ssrf_proxy:3128 # SSRF Proxy server HTTPS URL @@ -811,6 +826,9 @@ MAX_ITERATIONS_NUM=99 # The timeout for the text generation in millisecond TEXT_GENERATION_TIMEOUT_MS=60000 +# Allow rendering unsafe URLs which have "data:" scheme. +ALLOW_UNSAFE_DATA_SCHEME=false + # ------------------------------ # Environment Variables for db Service # ------------------------------ @@ -943,7 +961,7 @@ NGINX_SSL_PROTOCOLS=TLSv1.1 TLSv1.2 TLSv1.3 # Nginx performance tuning NGINX_WORKER_PROCESSES=auto -NGINX_CLIENT_MAX_BODY_SIZE=15M +NGINX_CLIENT_MAX_BODY_SIZE=100M NGINX_KEEPALIVE_TIMEOUT=65 # Proxy settings diff --git a/docker/docker-compose-template.yaml b/docker/docker-compose-template.yaml index 9534d8ef7c..fd7c78c7e7 100644 --- a/docker/docker-compose-template.yaml +++ b/docker/docker-compose-template.yaml @@ -2,7 +2,7 @@ x-shared-env: &shared-api-worker-env services: # API service api: - image: langgenius/dify-api:1.4.3 + image: langgenius/dify-api:1.5.1 restart: always environment: # Use the shared environment variables. @@ -31,7 +31,7 @@ services: # worker service # The Celery worker for processing the queue. worker: - image: langgenius/dify-api:1.4.3 + image: langgenius/dify-api:1.5.1 restart: always environment: # Use the shared environment variables. @@ -57,7 +57,7 @@ services: # Frontend web application. web: - image: langgenius/dify-web:1.4.3 + image: langgenius/dify-web:1.5.1 restart: always environment: CONSOLE_API_URL: ${CONSOLE_API_URL:-} @@ -67,6 +67,7 @@ services: TEXT_GENERATION_TIMEOUT_MS: ${TEXT_GENERATION_TIMEOUT_MS:-60000} CSP_WHITELIST: ${CSP_WHITELIST:-} ALLOW_EMBED: ${ALLOW_EMBED:-false} + ALLOW_UNSAFE_DATA_SCHEME: ${ALLOW_UNSAFE_DATA_SCHEME:-false} MARKETPLACE_API_URL: ${MARKETPLACE_API_URL:-https://marketplace.dify.ai} MARKETPLACE_URL: ${MARKETPLACE_URL:-https://marketplace.dify.ai} TOP_K_MAX_VALUE: ${TOP_K_MAX_VALUE:-} @@ -142,7 +143,7 @@ services: # plugin daemon plugin_daemon: - image: langgenius/dify-plugin-daemon:0.1.2-local + image: langgenius/dify-plugin-daemon:0.1.3-local restart: always environment: # Use the shared environment variables. @@ -168,7 +169,7 @@ services: PLUGIN_MEDIA_CACHE_PATH: ${PLUGIN_MEDIA_CACHE_PATH:-assets} PLUGIN_STORAGE_OSS_BUCKET: ${PLUGIN_STORAGE_OSS_BUCKET:-} S3_USE_AWS_MANAGED_IAM: ${PLUGIN_S3_USE_AWS_MANAGED_IAM:-false} - S3_USE_AWS: ${PLUGIN_S3_USE_AWS:-} + S3_USE_AWS: ${PLUGIN_S3_USE_AWS:-false} S3_ENDPOINT: ${PLUGIN_S3_ENDPOINT:-} S3_USE_PATH_STYLE: ${PLUGIN_S3_USE_PATH_STYLE:-false} AWS_ACCESS_KEY: ${PLUGIN_AWS_ACCESS_KEY:-} @@ -265,7 +266,7 @@ services: NGINX_SSL_CERT_KEY_FILENAME: ${NGINX_SSL_CERT_KEY_FILENAME:-dify.key} NGINX_SSL_PROTOCOLS: ${NGINX_SSL_PROTOCOLS:-TLSv1.1 TLSv1.2 TLSv1.3} NGINX_WORKER_PROCESSES: ${NGINX_WORKER_PROCESSES:-auto} - NGINX_CLIENT_MAX_BODY_SIZE: ${NGINX_CLIENT_MAX_BODY_SIZE:-15M} + NGINX_CLIENT_MAX_BODY_SIZE: ${NGINX_CLIENT_MAX_BODY_SIZE:-100M} NGINX_KEEPALIVE_TIMEOUT: ${NGINX_KEEPALIVE_TIMEOUT:-65} NGINX_PROXY_READ_TIMEOUT: ${NGINX_PROXY_READ_TIMEOUT:-3600s} NGINX_PROXY_SEND_TIMEOUT: ${NGINX_PROXY_SEND_TIMEOUT:-3600s} @@ -617,6 +618,18 @@ services: ports: - ${MYSCALE_PORT:-8123}:${MYSCALE_PORT:-8123} + # Matrixone vector store. + matrixone: + hostname: matrixone + image: matrixorigin/matrixone:2.1.1 + profiles: + - matrixone + restart: always + volumes: + - ./volumes/matrixone/data:/mo-data + ports: + - ${MATRIXONE_PORT:-6001}:${MATRIXONE_PORT:-6001} + # https://www.elastic.co/guide/en/elasticsearch/reference/current/settings.html # https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#docker-prod-prerequisites elasticsearch: diff --git a/docker/docker-compose.middleware.yaml b/docker/docker-compose.middleware.yaml index 5308a1f978..0b1885755b 100644 --- a/docker/docker-compose.middleware.yaml +++ b/docker/docker-compose.middleware.yaml @@ -71,7 +71,7 @@ services: # plugin daemon plugin_daemon: - image: langgenius/dify-plugin-daemon:0.1.2-local + image: langgenius/dify-plugin-daemon:0.1.3-local restart: always env_file: - ./middleware.env diff --git a/docker/docker-compose.yaml b/docker/docker-compose.yaml index b0f274c298..0a95251ff0 100644 --- a/docker/docker-compose.yaml +++ b/docker/docker-compose.yaml @@ -79,6 +79,7 @@ x-shared-env: &shared-api-worker-env BROKER_USE_SSL: ${BROKER_USE_SSL:-false} CELERY_USE_SENTINEL: ${CELERY_USE_SENTINEL:-false} CELERY_SENTINEL_MASTER_NAME: ${CELERY_SENTINEL_MASTER_NAME:-} + CELERY_SENTINEL_PASSWORD: ${CELERY_SENTINEL_PASSWORD:-} CELERY_SENTINEL_SOCKET_TIMEOUT: ${CELERY_SENTINEL_SOCKET_TIMEOUT:-0.1} WEB_API_CORS_ALLOW_ORIGINS: ${WEB_API_CORS_ALLOW_ORIGINS:-*} CONSOLE_CORS_ALLOW_ORIGINS: ${CONSOLE_CORS_ALLOW_ORIGINS:-*} @@ -195,6 +196,11 @@ x-shared-env: &shared-api-worker-env TIDB_VECTOR_USER: ${TIDB_VECTOR_USER:-} TIDB_VECTOR_PASSWORD: ${TIDB_VECTOR_PASSWORD:-} TIDB_VECTOR_DATABASE: ${TIDB_VECTOR_DATABASE:-dify} + MATRIXONE_HOST: ${MATRIXONE_HOST:-matrixone} + MATRIXONE_PORT: ${MATRIXONE_PORT:-6001} + MATRIXONE_USER: ${MATRIXONE_USER:-dump} + MATRIXONE_PASSWORD: ${MATRIXONE_PASSWORD:-111} + MATRIXONE_DATABASE: ${MATRIXONE_DATABASE:-dify} TIDB_ON_QDRANT_URL: ${TIDB_ON_QDRANT_URL:-http://127.0.0.1} TIDB_ON_QDRANT_API_KEY: ${TIDB_ON_QDRANT_API_KEY:-dify} TIDB_ON_QDRANT_CLIENT_TIMEOUT: ${TIDB_ON_QDRANT_CLIENT_TIMEOUT:-20} @@ -322,6 +328,7 @@ x-shared-env: &shared-api-worker-env SMTP_PASSWORD: ${SMTP_PASSWORD:-} SMTP_USE_TLS: ${SMTP_USE_TLS:-true} SMTP_OPPORTUNISTIC_TLS: ${SMTP_OPPORTUNISTIC_TLS:-false} + SENDGRID_API_KEY: ${SENDGRID_API_KEY:-} INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH: ${INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH:-4000} INVITE_EXPIRY_HOURS: ${INVITE_EXPIRY_HOURS:-72} RESET_PASSWORD_TOKEN_EXPIRY_MINUTES: ${RESET_PASSWORD_TOKEN_EXPIRY_MINUTES:-5} @@ -349,6 +356,7 @@ x-shared-env: &shared-api-worker-env HTTP_REQUEST_NODE_MAX_BINARY_SIZE: ${HTTP_REQUEST_NODE_MAX_BINARY_SIZE:-10485760} HTTP_REQUEST_NODE_MAX_TEXT_SIZE: ${HTTP_REQUEST_NODE_MAX_TEXT_SIZE:-1048576} HTTP_REQUEST_NODE_SSL_VERIFY: ${HTTP_REQUEST_NODE_SSL_VERIFY:-True} + RESPECT_XFORWARD_HEADERS_ENABLED: ${RESPECT_XFORWARD_HEADERS_ENABLED:-false} SSRF_PROXY_HTTP_URL: ${SSRF_PROXY_HTTP_URL:-http://ssrf_proxy:3128} SSRF_PROXY_HTTPS_URL: ${SSRF_PROXY_HTTPS_URL:-http://ssrf_proxy:3128} LOOP_NODE_MAX_COUNT: ${LOOP_NODE_MAX_COUNT:-100} @@ -356,6 +364,7 @@ x-shared-env: &shared-api-worker-env MAX_PARALLEL_LIMIT: ${MAX_PARALLEL_LIMIT:-10} MAX_ITERATIONS_NUM: ${MAX_ITERATIONS_NUM:-99} TEXT_GENERATION_TIMEOUT_MS: ${TEXT_GENERATION_TIMEOUT_MS:-60000} + ALLOW_UNSAFE_DATA_SCHEME: ${ALLOW_UNSAFE_DATA_SCHEME:-false} POSTGRES_USER: ${POSTGRES_USER:-${DB_USERNAME}} POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-${DB_PASSWORD}} POSTGRES_DB: ${POSTGRES_DB:-${DB_DATABASE}} @@ -412,7 +421,7 @@ x-shared-env: &shared-api-worker-env NGINX_SSL_CERT_KEY_FILENAME: ${NGINX_SSL_CERT_KEY_FILENAME:-dify.key} NGINX_SSL_PROTOCOLS: ${NGINX_SSL_PROTOCOLS:-TLSv1.1 TLSv1.2 TLSv1.3} NGINX_WORKER_PROCESSES: ${NGINX_WORKER_PROCESSES:-auto} - NGINX_CLIENT_MAX_BODY_SIZE: ${NGINX_CLIENT_MAX_BODY_SIZE:-15M} + NGINX_CLIENT_MAX_BODY_SIZE: ${NGINX_CLIENT_MAX_BODY_SIZE:-100M} NGINX_KEEPALIVE_TIMEOUT: ${NGINX_KEEPALIVE_TIMEOUT:-65} NGINX_PROXY_READ_TIMEOUT: ${NGINX_PROXY_READ_TIMEOUT:-3600s} NGINX_PROXY_SEND_TIMEOUT: ${NGINX_PROXY_SEND_TIMEOUT:-3600s} @@ -509,7 +518,7 @@ x-shared-env: &shared-api-worker-env services: # API service api: - image: langgenius/dify-api:1.4.3 + image: langgenius/dify-api:1.5.1 restart: always environment: # Use the shared environment variables. @@ -538,7 +547,7 @@ services: # worker service # The Celery worker for processing the queue. worker: - image: langgenius/dify-api:1.4.3 + image: langgenius/dify-api:1.5.1 restart: always environment: # Use the shared environment variables. @@ -564,7 +573,7 @@ services: # Frontend web application. web: - image: langgenius/dify-web:1.4.3 + image: langgenius/dify-web:1.5.1 restart: always environment: CONSOLE_API_URL: ${CONSOLE_API_URL:-} @@ -574,6 +583,7 @@ services: TEXT_GENERATION_TIMEOUT_MS: ${TEXT_GENERATION_TIMEOUT_MS:-60000} CSP_WHITELIST: ${CSP_WHITELIST:-} ALLOW_EMBED: ${ALLOW_EMBED:-false} + ALLOW_UNSAFE_DATA_SCHEME: ${ALLOW_UNSAFE_DATA_SCHEME:-false} MARKETPLACE_API_URL: ${MARKETPLACE_API_URL:-https://marketplace.dify.ai} MARKETPLACE_URL: ${MARKETPLACE_URL:-https://marketplace.dify.ai} TOP_K_MAX_VALUE: ${TOP_K_MAX_VALUE:-} @@ -649,7 +659,7 @@ services: # plugin daemon plugin_daemon: - image: langgenius/dify-plugin-daemon:0.1.2-local + image: langgenius/dify-plugin-daemon:0.1.3-local restart: always environment: # Use the shared environment variables. @@ -675,7 +685,7 @@ services: PLUGIN_MEDIA_CACHE_PATH: ${PLUGIN_MEDIA_CACHE_PATH:-assets} PLUGIN_STORAGE_OSS_BUCKET: ${PLUGIN_STORAGE_OSS_BUCKET:-} S3_USE_AWS_MANAGED_IAM: ${PLUGIN_S3_USE_AWS_MANAGED_IAM:-false} - S3_USE_AWS: ${PLUGIN_S3_USE_AWS:-} + S3_USE_AWS: ${PLUGIN_S3_USE_AWS:-false} S3_ENDPOINT: ${PLUGIN_S3_ENDPOINT:-} S3_USE_PATH_STYLE: ${PLUGIN_S3_USE_PATH_STYLE:-false} AWS_ACCESS_KEY: ${PLUGIN_AWS_ACCESS_KEY:-} @@ -772,7 +782,7 @@ services: NGINX_SSL_CERT_KEY_FILENAME: ${NGINX_SSL_CERT_KEY_FILENAME:-dify.key} NGINX_SSL_PROTOCOLS: ${NGINX_SSL_PROTOCOLS:-TLSv1.1 TLSv1.2 TLSv1.3} NGINX_WORKER_PROCESSES: ${NGINX_WORKER_PROCESSES:-auto} - NGINX_CLIENT_MAX_BODY_SIZE: ${NGINX_CLIENT_MAX_BODY_SIZE:-15M} + NGINX_CLIENT_MAX_BODY_SIZE: ${NGINX_CLIENT_MAX_BODY_SIZE:-100M} NGINX_KEEPALIVE_TIMEOUT: ${NGINX_KEEPALIVE_TIMEOUT:-65} NGINX_PROXY_READ_TIMEOUT: ${NGINX_PROXY_READ_TIMEOUT:-3600s} NGINX_PROXY_SEND_TIMEOUT: ${NGINX_PROXY_SEND_TIMEOUT:-3600s} @@ -1124,6 +1134,18 @@ services: ports: - ${MYSCALE_PORT:-8123}:${MYSCALE_PORT:-8123} + # Matrixone vector store. + matrixone: + hostname: matrixone + image: matrixorigin/matrixone:2.1.1 + profiles: + - matrixone + restart: always + volumes: + - ./volumes/matrixone/data:/mo-data + ports: + - ${MATRIXONE_PORT:-6001}:${MATRIXONE_PORT:-6001} + # https://www.elastic.co/guide/en/elasticsearch/reference/current/settings.html # https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#docker-prod-prerequisites elasticsearch: diff --git a/images/GitHub_README_if.png b/images/GitHub_README_if.png index 2a4e67264e..10c9d87b08 100644 Binary files a/images/GitHub_README_if.png and b/images/GitHub_README_if.png differ diff --git a/tests/unit_tests/events/test_provider_update_deadlock_prevention.py b/tests/unit_tests/events/test_provider_update_deadlock_prevention.py new file mode 100644 index 0000000000..47c175acd7 --- /dev/null +++ b/tests/unit_tests/events/test_provider_update_deadlock_prevention.py @@ -0,0 +1,248 @@ +import threading +from unittest.mock import Mock, patch + +from core.app.entities.app_invoke_entities import ChatAppGenerateEntity +from core.entities.provider_entities import QuotaUnit +from events.event_handlers.update_provider_when_message_created import ( + handle, + get_update_stats, +) +from models.provider import ProviderType +from sqlalchemy.exc import OperationalError + + +class TestProviderUpdateDeadlockPrevention: + """Test suite for deadlock prevention in Provider updates.""" + + def setup_method(self): + """Setup test fixtures.""" + self.mock_message = Mock() + self.mock_message.answer_tokens = 100 + + self.mock_app_config = Mock() + self.mock_app_config.tenant_id = "test-tenant-123" + + self.mock_model_conf = Mock() + self.mock_model_conf.provider = "openai" + + self.mock_system_config = Mock() + self.mock_system_config.current_quota_type = QuotaUnit.TOKENS + + self.mock_provider_config = Mock() + self.mock_provider_config.using_provider_type = ProviderType.SYSTEM + self.mock_provider_config.system_configuration = self.mock_system_config + + self.mock_provider_bundle = Mock() + self.mock_provider_bundle.configuration = self.mock_provider_config + + self.mock_model_conf.provider_model_bundle = self.mock_provider_bundle + + self.mock_generate_entity = Mock(spec=ChatAppGenerateEntity) + self.mock_generate_entity.app_config = self.mock_app_config + self.mock_generate_entity.model_conf = self.mock_model_conf + + @patch("events.event_handlers.update_provider_when_message_created.db") + def test_consolidated_handler_basic_functionality(self, mock_db): + """Test that the consolidated handler performs both updates correctly.""" + # Setup mock query chain + mock_query = Mock() + mock_db.session.query.return_value = mock_query + mock_query.filter.return_value = mock_query + mock_query.order_by.return_value = mock_query + mock_query.update.return_value = 1 # 1 row affected + + # Call the handler + handle(self.mock_message, application_generate_entity=self.mock_generate_entity) + + # Verify db.session.query was called + assert mock_db.session.query.called + + # Verify commit was called + mock_db.session.commit.assert_called_once() + + # Verify no rollback was called + assert not mock_db.session.rollback.called + + @patch("events.event_handlers.update_provider_when_message_created.db") + def test_deadlock_retry_mechanism(self, mock_db): + """Test that deadlock errors trigger retry logic.""" + # Setup mock to raise deadlock error on first attempt, succeed on second + mock_query = Mock() + mock_db.session.query.return_value = mock_query + mock_query.filter.return_value = mock_query + mock_query.order_by.return_value = mock_query + mock_query.update.return_value = 1 + + # First call raises deadlock, second succeeds + mock_db.session.commit.side_effect = [ + OperationalError("deadlock detected", None, None), + None, # Success on retry + ] + + # Call the handler + handle(self.mock_message, application_generate_entity=self.mock_generate_entity) + + # Verify commit was called twice (original + retry) + assert mock_db.session.commit.call_count == 2 + + # Verify rollback was called once (after first failure) + mock_db.session.rollback.assert_called_once() + + @patch("events.event_handlers.update_provider_when_message_created.db") + @patch("events.event_handlers.update_provider_when_message_created.time.sleep") + def test_exponential_backoff_timing(self, mock_sleep, mock_db): + """Test that retry delays follow exponential backoff pattern.""" + # Setup mock to fail twice, succeed on third attempt + mock_query = Mock() + mock_db.session.query.return_value = mock_query + mock_query.filter.return_value = mock_query + mock_query.order_by.return_value = mock_query + mock_query.update.return_value = 1 + + mock_db.session.commit.side_effect = [ + OperationalError("deadlock detected", None, None), + OperationalError("deadlock detected", None, None), + None, # Success on third attempt + ] + + # Call the handler + handle(self.mock_message, application_generate_entity=self.mock_generate_entity) + + # Verify sleep was called twice with increasing delays + assert mock_sleep.call_count == 2 + + # First delay should be around 0.1s + jitter + first_delay = mock_sleep.call_args_list[0][0][0] + assert 0.1 <= first_delay <= 0.3 + + # Second delay should be around 0.2s + jitter + second_delay = mock_sleep.call_args_list[1][0][0] + assert 0.2 <= second_delay <= 0.4 + + def test_concurrent_handler_execution(self): + """Test that multiple handlers can run concurrently without deadlock.""" + results = [] + errors = [] + + def run_handler(): + try: + with patch( + "events.event_handlers.update_provider_when_message_created.db" + ) as mock_db: + mock_query = Mock() + mock_db.session.query.return_value = mock_query + mock_query.filter.return_value = mock_query + mock_query.order_by.return_value = mock_query + mock_query.update.return_value = 1 + + handle( + self.mock_message, + application_generate_entity=self.mock_generate_entity, + ) + results.append("success") + except Exception as e: + errors.append(str(e)) + + # Run multiple handlers concurrently + threads = [] + for _ in range(5): + thread = threading.Thread(target=run_handler) + threads.append(thread) + thread.start() + + # Wait for all threads to complete + for thread in threads: + thread.join(timeout=5) + + # Verify all handlers completed successfully + assert len(results) == 5 + assert len(errors) == 0 + + def test_performance_stats_tracking(self): + """Test that performance statistics are tracked correctly.""" + # Reset stats + stats = get_update_stats() + initial_total = stats["total_updates"] + + with patch( + "events.event_handlers.update_provider_when_message_created.db" + ) as mock_db: + mock_query = Mock() + mock_db.session.query.return_value = mock_query + mock_query.filter.return_value = mock_query + mock_query.order_by.return_value = mock_query + mock_query.update.return_value = 1 + + # Call handler + handle( + self.mock_message, application_generate_entity=self.mock_generate_entity + ) + + # Check that stats were updated + updated_stats = get_update_stats() + assert updated_stats["total_updates"] == initial_total + 1 + assert updated_stats["successful_updates"] >= initial_total + 1 + + def test_non_chat_entity_ignored(self): + """Test that non-chat entities are ignored by the handler.""" + # Create a non-chat entity + mock_non_chat_entity = Mock() + mock_non_chat_entity.__class__.__name__ = "NonChatEntity" + + with patch( + "events.event_handlers.update_provider_when_message_created.db" + ) as mock_db: + # Call handler with non-chat entity + handle(self.mock_message, application_generate_entity=mock_non_chat_entity) + + # Verify no database operations were performed + assert not mock_db.session.query.called + assert not mock_db.session.commit.called + + @patch("events.event_handlers.update_provider_when_message_created.db") + def test_quota_calculation_tokens(self, mock_db): + """Test quota calculation for token-based quotas.""" + # Setup token-based quota + self.mock_system_config.current_quota_type = QuotaUnit.TOKENS + self.mock_message.answer_tokens = 150 + + mock_query = Mock() + mock_db.session.query.return_value = mock_query + mock_query.filter.return_value = mock_query + mock_query.order_by.return_value = mock_query + mock_query.update.return_value = 1 + + # Call handler + handle(self.mock_message, application_generate_entity=self.mock_generate_entity) + + # Verify update was called with token count + update_calls = mock_query.update.call_args_list + + # Should have at least one call with quota_used update + quota_update_found = False + for call in update_calls: + values = call[0][0] # First argument to update() + if "quota_used" in values: + quota_update_found = True + break + + assert quota_update_found + + @patch("events.event_handlers.update_provider_when_message_created.db") + def test_quota_calculation_times(self, mock_db): + """Test quota calculation for times-based quotas.""" + # Setup times-based quota + self.mock_system_config.current_quota_type = QuotaUnit.TIMES + + mock_query = Mock() + mock_db.session.query.return_value = mock_query + mock_query.filter.return_value = mock_query + mock_query.order_by.return_value = mock_query + mock_query.update.return_value = 1 + + # Call handler + handle(self.mock_message, application_generate_entity=self.mock_generate_entity) + + # Verify update was called + assert mock_query.update.called + assert mock_db.session.commit.called diff --git a/web/.env.example b/web/.env.example index 78b4f33e8c..37bfc939eb 100644 --- a/web/.env.example +++ b/web/.env.example @@ -32,6 +32,9 @@ NEXT_PUBLIC_CSP_WHITELIST= # Default is not allow to embed into iframe to prevent Clickjacking: https://owasp.org/www-community/attacks/Clickjacking NEXT_PUBLIC_ALLOW_EMBED= +# Allow rendering unsafe URLs which have "data:" scheme. +NEXT_PUBLIC_ALLOW_UNSAFE_DATA_SCHEME=false + # Github Access Token, used for invoking Github API NEXT_PUBLIC_GITHUB_ACCESS_TOKEN= # The maximum number of top-k value for RAG. @@ -56,3 +59,5 @@ NEXT_PUBLIC_ENABLE_WEBSITE_JINAREADER=true NEXT_PUBLIC_ENABLE_WEBSITE_FIRECRAWL=true NEXT_PUBLIC_ENABLE_WEBSITE_WATERCRAWL=true +# The maximum number of tree node depth for workflow +NEXT_PUBLIC_MAX_TREE_DEPTH=50 diff --git a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config-popup.tsx b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config-popup.tsx index 0efc5082a4..2afe451fe1 100644 --- a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config-popup.tsx +++ b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config-popup.tsx @@ -5,7 +5,7 @@ import { useTranslation } from 'react-i18next' import { useBoolean } from 'ahooks' import TracingIcon from './tracing-icon' import ProviderPanel from './provider-panel' -import type { LangFuseConfig, LangSmithConfig, OpikConfig, WeaveConfig } from './type' +import type { AliyunConfig, ArizeConfig, LangFuseConfig, LangSmithConfig, OpikConfig, PhoenixConfig, WeaveConfig } from './type' import { TracingProvider } from './type' import ProviderConfigModal from './provider-config-modal' import Indicator from '@/app/components/header/indicator' @@ -23,11 +23,14 @@ export type PopupProps = { onStatusChange: (enabled: boolean) => void chosenProvider: TracingProvider | null onChooseProvider: (provider: TracingProvider) => void + arizeConfig: ArizeConfig | null + phoenixConfig: PhoenixConfig | null langSmithConfig: LangSmithConfig | null langFuseConfig: LangFuseConfig | null opikConfig: OpikConfig | null weaveConfig: WeaveConfig | null - onConfigUpdated: (provider: TracingProvider, payload: LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => void + aliyunConfig: AliyunConfig | null + onConfigUpdated: (provider: TracingProvider, payload: ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig | AliyunConfig) => void onConfigRemoved: (provider: TracingProvider) => void } @@ -38,10 +41,13 @@ const ConfigPopup: FC = ({ onStatusChange, chosenProvider, onChooseProvider, + arizeConfig, + phoenixConfig, langSmithConfig, langFuseConfig, opikConfig, weaveConfig, + aliyunConfig, onConfigUpdated, onConfigRemoved, }) => { @@ -65,7 +71,7 @@ const ConfigPopup: FC = ({ } }, [onChooseProvider]) - const handleConfigUpdated = useCallback((payload: LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => { + const handleConfigUpdated = useCallback((payload: ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig | AliyunConfig) => { onConfigUpdated(currentProvider!, payload) hideConfigModal() }, [currentProvider, hideConfigModal, onConfigUpdated]) @@ -75,8 +81,8 @@ const ConfigPopup: FC = ({ hideConfigModal() }, [currentProvider, hideConfigModal, onConfigRemoved]) - const providerAllConfigured = langSmithConfig && langFuseConfig && opikConfig && weaveConfig - const providerAllNotConfigured = !langSmithConfig && !langFuseConfig && !opikConfig && !weaveConfig + const providerAllConfigured = arizeConfig && phoenixConfig && langSmithConfig && langFuseConfig && opikConfig && weaveConfig && aliyunConfig + const providerAllNotConfigured = !arizeConfig && !phoenixConfig && !langSmithConfig && !langFuseConfig && !opikConfig && !weaveConfig && !aliyunConfig const switchContent = ( = ({ disabled={providerAllNotConfigured} /> ) + const arizePanel = ( + + ) + + const phoenixPanel = ( + + ) + const langSmithPanel = ( = ({ key="weave-provider-panel" /> ) + + const aliyunPanel = ( + + ) const configuredProviderPanel = () => { const configuredPanels: JSX.Element[] = [] @@ -152,12 +197,27 @@ const ConfigPopup: FC = ({ if (weaveConfig) configuredPanels.push(weavePanel) + if (arizeConfig) + configuredPanels.push(arizePanel) + + if (phoenixConfig) + configuredPanels.push(phoenixPanel) + + if (aliyunConfig) + configuredPanels.push(aliyunPanel) + return configuredPanels } const moreProviderPanel = () => { const notConfiguredPanels: JSX.Element[] = [] + if (!arizeConfig) + notConfiguredPanels.push(arizePanel) + + if (!phoenixConfig) + notConfiguredPanels.push(phoenixPanel) + if (!langFuseConfig) notConfiguredPanels.push(langfusePanel) @@ -170,16 +230,25 @@ const ConfigPopup: FC = ({ if (!weaveConfig) notConfiguredPanels.push(weavePanel) + if (!aliyunConfig) + notConfiguredPanels.push(aliyunPanel) + return notConfiguredPanels } const configuredProviderConfig = () => { + if (currentProvider === TracingProvider.arize) + return arizeConfig + if (currentProvider === TracingProvider.phoenix) + return phoenixConfig if (currentProvider === TracingProvider.langSmith) return langSmithConfig if (currentProvider === TracingProvider.langfuse) return langFuseConfig if (currentProvider === TracingProvider.opik) return opikConfig + if (currentProvider === TracingProvider.aliyun) + return aliyunConfig return weaveConfig } @@ -220,22 +289,25 @@ const ConfigPopup: FC = ({ ? ( <>
{t(`${I18N_PREFIX}.configProviderTitle.${providerAllConfigured ? 'configured' : 'notConfigured'}`)}
-
+
{langfusePanel} {langSmithPanel} {opikPanel} {weavePanel} + {arizePanel} + {phoenixPanel} + {aliyunPanel}
) : ( <>
{t(`${I18N_PREFIX}.configProviderTitle.configured`)}
-
+
{configuredProviderPanel()}
{t(`${I18N_PREFIX}.configProviderTitle.moreProvider`)}
-
+
{moreProviderPanel()}
diff --git a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config.ts b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config.ts index 5d3c4076bd..4c81b63ea2 100644 --- a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config.ts +++ b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config.ts @@ -1,8 +1,11 @@ import { TracingProvider } from './type' export const docURL = { + [TracingProvider.arize]: 'https://docs.arize.com/arize', + [TracingProvider.phoenix]: 'https://docs.arize.com/phoenix', [TracingProvider.langSmith]: 'https://docs.smith.langchain.com/', [TracingProvider.langfuse]: 'https://docs.langfuse.com', [TracingProvider.opik]: 'https://www.comet.com/docs/opik/tracing/integrations/dify#setup-instructions', [TracingProvider.weave]: 'https://weave-docs.wandb.ai/', + [TracingProvider.aliyun]: 'https://help.aliyun.com/zh/arms/tracing-analysis/untitled-document-1750672984680', } diff --git a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/panel.tsx b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/panel.tsx index 76e90ecf19..8bf18904be 100644 --- a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/panel.tsx +++ b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/panel.tsx @@ -7,12 +7,12 @@ import { import { useTranslation } from 'react-i18next' import { usePathname } from 'next/navigation' import { useBoolean } from 'ahooks' -import type { LangFuseConfig, LangSmithConfig, OpikConfig, WeaveConfig } from './type' +import type { AliyunConfig, ArizeConfig, LangFuseConfig, LangSmithConfig, OpikConfig, PhoenixConfig, WeaveConfig } from './type' import { TracingProvider } from './type' import TracingIcon from './tracing-icon' import ConfigButton from './config-button' import cn from '@/utils/classnames' -import { LangfuseIcon, LangsmithIcon, OpikIcon, WeaveIcon } from '@/app/components/base/icons/src/public/tracing' +import { AliyunIcon, ArizeIcon, LangfuseIcon, LangsmithIcon, OpikIcon, PhoenixIcon, WeaveIcon } from '@/app/components/base/icons/src/public/tracing' import Indicator from '@/app/components/header/indicator' import { fetchTracingConfig as doFetchTracingConfig, fetchTracingStatus, updateTracingStatus } from '@/service/apps' import type { TracingStatus } from '@/models/app' @@ -62,24 +62,33 @@ const Panel: FC = () => { } const inUseTracingProvider: TracingProvider | null = tracingStatus?.tracing_provider || null - const InUseProviderIcon - = inUseTracingProvider === TracingProvider.langSmith - ? LangsmithIcon - : inUseTracingProvider === TracingProvider.langfuse - ? LangfuseIcon - : inUseTracingProvider === TracingProvider.opik - ? OpikIcon - : inUseTracingProvider === TracingProvider.weave - ? WeaveIcon - : LangsmithIcon + const providerIconMap: Record> = { + [TracingProvider.arize]: ArizeIcon, + [TracingProvider.phoenix]: PhoenixIcon, + [TracingProvider.langSmith]: LangsmithIcon, + [TracingProvider.langfuse]: LangfuseIcon, + [TracingProvider.opik]: OpikIcon, + [TracingProvider.weave]: WeaveIcon, + [TracingProvider.aliyun]: AliyunIcon, + } + const InUseProviderIcon = inUseTracingProvider ? providerIconMap[inUseTracingProvider] : undefined + const [arizeConfig, setArizeConfig] = useState(null) + const [phoenixConfig, setPhoenixConfig] = useState(null) const [langSmithConfig, setLangSmithConfig] = useState(null) const [langFuseConfig, setLangFuseConfig] = useState(null) const [opikConfig, setOpikConfig] = useState(null) const [weaveConfig, setWeaveConfig] = useState(null) - const hasConfiguredTracing = !!(langSmithConfig || langFuseConfig || opikConfig || weaveConfig) + const [aliyunConfig, setAliyunConfig] = useState(null) + const hasConfiguredTracing = !!(langSmithConfig || langFuseConfig || opikConfig || weaveConfig || arizeConfig || phoenixConfig || aliyunConfig) const fetchTracingConfig = async () => { + const { tracing_config: arizeConfig, has_not_configured: arizeHasNotConfig } = await doFetchTracingConfig({ appId, provider: TracingProvider.arize }) + if (!arizeHasNotConfig) + setArizeConfig(arizeConfig as ArizeConfig) + const { tracing_config: phoenixConfig, has_not_configured: phoenixHasNotConfig } = await doFetchTracingConfig({ appId, provider: TracingProvider.phoenix }) + if (!phoenixHasNotConfig) + setPhoenixConfig(phoenixConfig as PhoenixConfig) const { tracing_config: langSmithConfig, has_not_configured: langSmithHasNotConfig } = await doFetchTracingConfig({ appId, provider: TracingProvider.langSmith }) if (!langSmithHasNotConfig) setLangSmithConfig(langSmithConfig as LangSmithConfig) @@ -92,12 +101,19 @@ const Panel: FC = () => { const { tracing_config: weaveConfig, has_not_configured: weaveHasNotConfig } = await doFetchTracingConfig({ appId, provider: TracingProvider.weave }) if (!weaveHasNotConfig) setWeaveConfig(weaveConfig as WeaveConfig) + const { tracing_config: aliyunConfig, has_not_configured: aliyunHasNotConfig } = await doFetchTracingConfig({ appId, provider: TracingProvider.aliyun }) + if (!aliyunHasNotConfig) + setAliyunConfig(aliyunConfig as AliyunConfig) } const handleTracingConfigUpdated = async (provider: TracingProvider) => { // call api to hide secret key value const { tracing_config } = await doFetchTracingConfig({ appId, provider }) - if (provider === TracingProvider.langSmith) + if (provider === TracingProvider.arize) + setArizeConfig(tracing_config as ArizeConfig) + else if (provider === TracingProvider.phoenix) + setPhoenixConfig(tracing_config as PhoenixConfig) + else if (provider === TracingProvider.langSmith) setLangSmithConfig(tracing_config as LangSmithConfig) else if (provider === TracingProvider.langfuse) setLangFuseConfig(tracing_config as LangFuseConfig) @@ -105,10 +121,16 @@ const Panel: FC = () => { setOpikConfig(tracing_config as OpikConfig) else if (provider === TracingProvider.weave) setWeaveConfig(tracing_config as WeaveConfig) + else if (provider === TracingProvider.aliyun) + setAliyunConfig(tracing_config as AliyunConfig) } const handleTracingConfigRemoved = (provider: TracingProvider) => { - if (provider === TracingProvider.langSmith) + if (provider === TracingProvider.arize) + setArizeConfig(null) + else if (provider === TracingProvider.phoenix) + setPhoenixConfig(null) + else if (provider === TracingProvider.langSmith) setLangSmithConfig(null) else if (provider === TracingProvider.langfuse) setLangFuseConfig(null) @@ -116,6 +138,8 @@ const Panel: FC = () => { setOpikConfig(null) else if (provider === TracingProvider.weave) setWeaveConfig(null) + else if (provider === TracingProvider.aliyun) + setAliyunConfig(null) if (provider === inUseTracingProvider) { handleTracingStatusChange({ enabled: false, @@ -170,10 +194,13 @@ const Panel: FC = () => { onStatusChange={handleTracingEnabledChange} chosenProvider={inUseTracingProvider} onChooseProvider={handleChooseProvider} + arizeConfig={arizeConfig} + phoenixConfig={phoenixConfig} langSmithConfig={langSmithConfig} langFuseConfig={langFuseConfig} opikConfig={opikConfig} weaveConfig={weaveConfig} + aliyunConfig={aliyunConfig} onConfigUpdated={handleTracingConfigUpdated} onConfigRemoved={handleTracingConfigRemoved} controlShowPopup={controlShowPopup} @@ -205,10 +232,13 @@ const Panel: FC = () => { onStatusChange={handleTracingEnabledChange} chosenProvider={inUseTracingProvider} onChooseProvider={handleChooseProvider} + arizeConfig={arizeConfig} + phoenixConfig={phoenixConfig} langSmithConfig={langSmithConfig} langFuseConfig={langFuseConfig} opikConfig={opikConfig} weaveConfig={weaveConfig} + aliyunConfig={aliyunConfig} onConfigUpdated={handleTracingConfigUpdated} onConfigRemoved={handleTracingConfigRemoved} controlShowPopup={controlShowPopup} diff --git a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/provider-config-modal.tsx b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/provider-config-modal.tsx index b6c97add48..318f1f61d6 100644 --- a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/provider-config-modal.tsx +++ b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/provider-config-modal.tsx @@ -4,7 +4,7 @@ import React, { useCallback, useState } from 'react' import { useTranslation } from 'react-i18next' import { useBoolean } from 'ahooks' import Field from './field' -import type { LangFuseConfig, LangSmithConfig, OpikConfig, WeaveConfig } from './type' +import type { AliyunConfig, ArizeConfig, LangFuseConfig, LangSmithConfig, OpikConfig, PhoenixConfig, WeaveConfig } from './type' import { TracingProvider } from './type' import { docURL } from './config' import { @@ -22,15 +22,28 @@ import Divider from '@/app/components/base/divider' type Props = { appId: string type: TracingProvider - payload?: LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig | null + payload?: ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig | AliyunConfig | null onRemoved: () => void onCancel: () => void - onSaved: (payload: LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => void + onSaved: (payload: ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig | AliyunConfig) => void onChosen: (provider: TracingProvider) => void } const I18N_PREFIX = 'app.tracing.configProvider' +const arizeConfigTemplate = { + api_key: '', + space_id: '', + project: '', + endpoint: '', +} + +const phoenixConfigTemplate = { + api_key: '', + project: '', + endpoint: '', +} + const langSmithConfigTemplate = { api_key: '', project: '', @@ -58,6 +71,12 @@ const weaveConfigTemplate = { host: '', } +const aliyunConfigTemplate = { + app_name: '', + license_key: '', + endpoint: '', +} + const ProviderConfigModal: FC = ({ appId, type, @@ -71,11 +90,17 @@ const ProviderConfigModal: FC = ({ const isEdit = !!payload const isAdd = !isEdit const [isSaving, setIsSaving] = useState(false) - const [config, setConfig] = useState((() => { + const [config, setConfig] = useState((() => { if (isEdit) return payload - if (type === TracingProvider.langSmith) + if (type === TracingProvider.arize) + return arizeConfigTemplate + + else if (type === TracingProvider.phoenix) + return phoenixConfigTemplate + + else if (type === TracingProvider.langSmith) return langSmithConfigTemplate else if (type === TracingProvider.langfuse) @@ -84,6 +109,9 @@ const ProviderConfigModal: FC = ({ else if (type === TracingProvider.opik) return opikConfigTemplate + else if (type === TracingProvider.aliyun) + return aliyunConfigTemplate + return weaveConfigTemplate })()) const [isShowRemoveConfirm, { @@ -115,6 +143,24 @@ const ProviderConfigModal: FC = ({ const checkValid = useCallback(() => { let errorMessage = '' + if (type === TracingProvider.arize) { + const postData = config as ArizeConfig + if (!postData.api_key) + errorMessage = t('common.errorMsg.fieldRequired', { field: 'API Key' }) + if (!postData.space_id) + errorMessage = t('common.errorMsg.fieldRequired', { field: 'Space ID' }) + if (!errorMessage && !postData.project) + errorMessage = t('common.errorMsg.fieldRequired', { field: t(`${I18N_PREFIX}.project`) }) + } + + if (type === TracingProvider.phoenix) { + const postData = config as PhoenixConfig + if (!postData.api_key) + errorMessage = t('common.errorMsg.fieldRequired', { field: 'API Key' }) + if (!errorMessage && !postData.project) + errorMessage = t('common.errorMsg.fieldRequired', { field: t(`${I18N_PREFIX}.project`) }) + } + if (type === TracingProvider.langSmith) { const postData = config as LangSmithConfig if (!postData.api_key) @@ -146,6 +192,16 @@ const ProviderConfigModal: FC = ({ errorMessage = t('common.errorMsg.fieldRequired', { field: t(`${I18N_PREFIX}.project`) }) } + if (type === TracingProvider.aliyun) { + const postData = config as AliyunConfig + if (!errorMessage && !postData.app_name) + errorMessage = t('common.errorMsg.fieldRequired', { field: 'App Name' }) + if (!errorMessage && !postData.license_key) + errorMessage = t('common.errorMsg.fieldRequired', { field: 'License Key' }) + if (!errorMessage && !postData.endpoint) + errorMessage = t('common.errorMsg.fieldRequired', { field: 'Endpoint' }) + } + return errorMessage }, [config, t, type]) const handleSave = useCallback(async () => { @@ -195,6 +251,93 @@ const ProviderConfigModal: FC = ({
+ {type === TracingProvider.arize && ( + <> + + + + + + )} + {type === TracingProvider.phoenix && ( + <> + + + + + )} + {type === TracingProvider.aliyun && ( + <> + + + + + )} {type === TracingProvider.weave && ( <> { return ({ + [TracingProvider.arize]: ArizeIconBig, + [TracingProvider.phoenix]: PhoenixIconBig, [TracingProvider.langSmith]: LangsmithIconBig, [TracingProvider.langfuse]: LangfuseIconBig, [TracingProvider.opik]: OpikIconBig, [TracingProvider.weave]: WeaveIconBig, + [TracingProvider.aliyun]: AliyunIconBig, })[type] } diff --git a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/type.ts b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/type.ts index ed468caf65..78bca41ad2 100644 --- a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/type.ts +++ b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/type.ts @@ -1,8 +1,24 @@ export enum TracingProvider { + arize = 'arize', + phoenix = 'phoenix', langSmith = 'langsmith', langfuse = 'langfuse', opik = 'opik', weave = 'weave', + aliyun = 'aliyun', +} + +export type ArizeConfig = { + api_key: string + space_id: string + project: string + endpoint: string +} + +export type PhoenixConfig = { + api_key: string + project: string + endpoint: string } export type LangSmithConfig = { @@ -31,3 +47,9 @@ export type WeaveConfig = { endpoint: string host: string } + +export type AliyunConfig = { + app_name: string + license_key: string + endpoint: string +} diff --git a/web/app/(commonLayout)/apps/AppCard.tsx b/web/app/(commonLayout)/apps/AppCard.tsx index 31b9ed87c2..f50cc10520 100644 --- a/web/app/(commonLayout)/apps/AppCard.tsx +++ b/web/app/(commonLayout)/apps/AppCard.tsx @@ -36,6 +36,7 @@ import AccessControl from '@/app/components/app/app-access-control' import { AccessMode } from '@/models/access-control' import { useGlobalPublicStore } from '@/context/global-public-context' import { formatTime } from '@/utils/time' +import { useGetUserCanAccessApp } from '@/service/access-control' export type AppCardProps = { app: App @@ -190,6 +191,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { }, [onRefresh, mutateApps, setShowAccessControl]) const Operations = (props: HtmlContentProps) => { + const { data: userCanAccessApp, isLoading: isGettingUserCanAccessApp } = useGetUserCanAccessApp({ appId: app?.id, enabled: (!!props?.open && systemFeatures.webapp_auth.enabled) }) const onMouseLeave = async () => { props.onClose?.() } @@ -267,10 +269,14 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { )} - - + { + (isGettingUserCanAccessApp || !userCanAccessApp?.result) ? null : <> + + + + } { systemFeatures.webapp_auth.enabled && isCurrentWorkspaceEditor && <> @@ -333,7 +339,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
{app.author_name}
·
-
{EditTimeText}
+
{EditTimeText}
diff --git a/web/app/(commonLayout)/datasets/(datasetDetailLayout)/[datasetId]/layout-main.tsx b/web/app/(commonLayout)/datasets/(datasetDetailLayout)/[datasetId]/layout-main.tsx index fb3a9087ca..acaae3f720 100644 --- a/web/app/(commonLayout)/datasets/(datasetDetailLayout)/[datasetId]/layout-main.tsx +++ b/web/app/(commonLayout)/datasets/(datasetDetailLayout)/[datasetId]/layout-main.tsx @@ -77,7 +77,7 @@ const ExtraInfo = ({ isMobile, relatedApps, expand }: IExtraInfoProps) => { )} - {isMobile &&
+ {isMobile &&
{relatedAppsTotal || '--'}
} diff --git a/web/app/(commonLayout)/datasets/Datasets.tsx b/web/app/(commonLayout)/datasets/Datasets.tsx index 28461e8617..2d4848e92e 100644 --- a/web/app/(commonLayout)/datasets/Datasets.tsx +++ b/web/app/(commonLayout)/datasets/Datasets.tsx @@ -81,7 +81,7 @@ const Datasets = ({ currentContainer?.removeEventListener('scroll', onScroll) onScroll.cancel() } - }, [onScroll]) + }, [containerRef, onScroll]) return (