Merge branch 'main' into feat/install-plugin-limit

.devcontainer/post_create_command.sh

@@ -1,12 +1,13 @@
 #!/bin/bash
 
-npm add -g pnpm@10.8.0
+npm add -g pnpm@10.11.1
 cd web && pnpm install
 pipx install uv
 
 echo 'alias start-api="cd /workspaces/dify/api && uv run python -m flask run --host 0.0.0.0 --port=5001 --debug"' >> ~/.bashrc
 echo 'alias start-worker="cd /workspaces/dify/api && uv run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion"' >> ~/.bashrc
 echo 'alias start-web="cd /workspaces/dify/web && pnpm dev"' >> ~/.bashrc
+echo 'alias start-web-prod="cd /workspaces/dify/web && pnpm build && pnpm start"' >> ~/.bashrc
 echo 'alias start-containers="cd /workspaces/dify/docker && docker-compose -f docker-compose.middleware.yaml -p dify --env-file middleware.env up -d"' >> ~/.bashrc
 echo 'alias stop-containers="cd /workspaces/dify/docker && docker-compose -f docker-compose.middleware.yaml -p dify --env-file middleware.env down"' >> ~/.bashrc
 

.github/pull_request_template.md

@@ -1,25 +1,23 @@
-# Summary
+> [!IMPORTANT]
+>
+> 1. Make sure you have read our [contribution guidelines](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)
+> 2. Ensure there is an associated issue and you have been assigned to it
+> 3. Use the correct syntax to link this PR: `Fixes #<issue number>`.
 
-Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
+## Summary
 
-> [!Tip]
-> Close issue syntax: `Fixes #<issue number>` or `Resolves #<issue number>`, see [documentation](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) for more details.
+<!-- Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change. -->
 
-
-# Screenshots
+## Screenshots
 
 | Before | After |
 |--------|-------|
 | ...    | ...   |
 
-# Checklist
-
-> [!IMPORTANT]  
-> Please review the checklist below before submitting your pull request.
+## Checklist
 
 - [ ] This change requires a documentation update, included: [Dify Document](https://github.com/langgenius/dify-docs)
 - [x] I understand that this PR may be closed in case there was no previous discussion or issues. (This doesn't apply to typos!)
 - [x] I've added a test for each change that was introduced, and I tried as much as possible to make a single atomic change.
 - [x] I've updated the documentation accordingly.
 - [x] I ran `dev/reformat`(backend) and `cd web && npx lint-staged`(frontend) to appease the lint gods
-

.github/workflows/translate-i18n-base-on-english.yml

@@ -31,11 +31,19 @@ jobs:
             echo "FILES_CHANGED=false" >> $GITHUB_ENV
           fi
 
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 10
+          run_install: false
+
       - name: Set up Node.js
         if: env.FILES_CHANGED == 'true'
         uses: actions/setup-node@v4
         with:
           node-version: 'lts/*'
+          cache: pnpm
+          cache-dependency-path: ./web/package.json
 
       - name: Install dependencies
         if: env.FILES_CHANGED == 'true'

.gitignore

@@ -192,12 +192,12 @@ sdks/python-client/dist
 sdks/python-client/dify_client.egg-info
 
 .vscode/*
-!.vscode/launch.json
+!.vscode/launch.json.template
+!.vscode/README.md
 pyrightconfig.json
 api/.vscode
 
 .idea/
-.vscode
 
 # pnpm
 /.pnpm-store
@@ -207,3 +207,6 @@ plugins.jsonl
 
 # mise
 mise.toml
+
+# Next.js build output
+.next/

.vscode/README.md

@@ -0,0 +1,14 @@
+# Debugging with VS Code
+
+This `launch.json.template` file provides various debug configurations for the Dify project within VS Code / Cursor. To use these configurations, you should copy the contents of this file into a new file named `launch.json` in the same `.vscode` directory.
+
+## How to Use
+
+1.  **Create `launch.json`**: If you don't have one, create a file named `launch.json` inside the `.vscode` directory.
+2.  **Copy Content**: Copy the entire content from `launch.json.template` into your newly created `launch.json` file.
+3.  **Select Debug Configuration**: Go to the Run and Debug view in VS Code / Cursor (Ctrl+Shift+D or Cmd+Shift+D).
+4.  **Start Debugging**: Select the desired configuration from the dropdown menu and click the green play button.
+
+## Tips
+
+- If you need to debug with Edge browser instead of Chrome, modify the `serverReadyAction` configuration in the "Next.js: debug full stack" section, change `"debugWithChrome"` to `"debugWithEdge"` to use Microsoft Edge for debugging.

.vscode/launch.json.template

@@ -0,0 +1,68 @@
+{
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python: Flask API",
+            "type": "debugpy",
+            "request": "launch",
+            "module": "flask",
+            "env": {
+                "FLASK_APP": "app.py",
+                "FLASK_ENV": "development",
+                "GEVENT_SUPPORT": "True"
+            },
+            "args": [
+                "run",
+                "--host=0.0.0.0",
+                "--port=5001",
+                "--no-debugger",
+                "--no-reload"
+            ],
+            "jinja": true,
+            "justMyCode": true,
+            "cwd": "${workspaceFolder}/api",
+            "python": "${workspaceFolder}/api/.venv/bin/python"
+        },
+        {
+            "name": "Python: Celery Worker (Solo)",
+            "type": "debugpy",
+            "request": "launch",
+            "module": "celery",
+            "env": {
+                "GEVENT_SUPPORT": "True"
+            },
+            "args": [
+                "-A",
+                "app.celery",
+                "worker",
+                "-P",
+                "solo",
+                "-c",
+                "1",
+                "-Q",
+                "dataset,generation,mail,ops_trace",
+                "--loglevel",
+                "INFO"
+            ],
+            "justMyCode": false,
+            "cwd": "${workspaceFolder}/api",
+            "python": "${workspaceFolder}/api/.venv/bin/python"
+        },
+        {
+            "name": "Next.js: debug full stack",
+            "type": "node",
+            "request": "launch",
+            "program": "${workspaceFolder}/web/node_modules/next/dist/bin/next",
+            "runtimeArgs": ["--inspect"],
+            "skipFiles": ["<node_internals>/**"],
+            "serverReadyAction": {
+              "action": "debugWithChrome",
+              "killOnServerStop": true,
+              "pattern": "- Local:.+(https?://.+)",
+              "uriFormat": "%s",
+              "webRoot": "${workspaceFolder}/web"
+            },
+            "cwd": "${workspaceFolder}/web"
+          }
+    ]
+}

README.md

@@ -235,7 +235,7 @@ At the same time, please consider supporting Dify by sharing it on social media
 
 ## Community & contact
 
-- [Github Discussion](https://github.com/langgenius/dify/discussions). Best for: sharing feedback and asking questions.
+- [GitHub Discussion](https://github.com/langgenius/dify/discussions). Best for: sharing feedback and asking questions.
 - [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
 - [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.
 - [X(Twitter)](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.

README_AR.md

@@ -223,7 +223,7 @@ docker compose up -d
 </a>
 
 ## المجتمع والاتصال
-- [مناقشة Github](https://github.com/langgenius/dify/discussions). الأفضل لـ: مشاركة التعليقات وطرح الأسئلة.
+- [مناقشة GitHub](https://github.com/langgenius/dify/discussions). الأفضل لـ: مشاركة التعليقات وطرح الأسئلة.
 - [المشكلات على GitHub](https://github.com/langgenius/dify/issues). الأفضل لـ: الأخطاء التي تواجهها في استخدام Dify.AI، واقتراحات الميزات. انظر [دليل المساهمة](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
 - [Discord](https://discord.gg/FngNHpbcY7). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.
 - [تويتر](https://twitter.com/dify_ai). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.

README_BN.md

@@ -234,7 +234,7 @@ GitHub-এ ডিফাইকে স্টার দিয়ে রাখুন
 
 ## কমিউনিটি এবং যোগাযোগ
 
-- [Github Discussion](https://github.com/langgenius/dify/discussions) ফিডব্যাক এবং প্রতিক্রিয়া জানানোর মাধ্যম।
+- [GitHub Discussion](https://github.com/langgenius/dify/discussions) ফিডব্যাক এবং প্রতিক্রিয়া জানানোর মাধ্যম।
 - [GitHub Issues](https://github.com/langgenius/dify/issues). Dify.AI ব্যবহার করে আপনি যেসব বাগের সম্মুখীন হন এবং ফিচার প্রস্তাবনা।  আমাদের [অবদান নির্দেশিকা](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) দেখুন।
 - [Discord](https://discord.gg/FngNHpbcY7) আপনার এপ্লিকেশন শেয়ার এবং কমিউনিটি আড্ডার মাধ্যম। 
 - [X(Twitter)](https://twitter.com/dify_ai) আপনার এপ্লিকেশন শেয়ার এবং কমিউনিটি আড্ডার মাধ্যম। 

README_CN.md

@@ -243,7 +243,7 @@ docker compose up -d
 
 我们欢迎您为 Dify 做出贡献，以帮助改善 Dify。包括：提交代码、问题、新想法，或分享您基于 Dify 创建的有趣且有用的 AI 应用程序。同时，我们也欢迎您在不同的活动、会议和社交媒体上分享 Dify。
 
-- [Github Discussion](https://github.com/langgenius/dify/discussions). 👉：分享您的应用程序并与社区交流。
+- [GitHub Discussion](https://github.com/langgenius/dify/discussions). 👉：分享您的应用程序并与社区交流。
 - [GitHub Issues](https://github.com/langgenius/dify/issues)。👉：使用 Dify.AI 时遇到的错误和问题，请参阅[贡献指南](CONTRIBUTING.md)。
 - [电子邮件支持](mailto:hello@dify.ai?subject=[GitHub]Questions%20About%20Dify)。👉：关于使用 Dify.AI 的问题。
 - [Discord](https://discord.gg/FngNHpbcY7)。👉：分享您的应用程序并与社区交流。

README_DE.md

@@ -230,7 +230,7 @@ Falls Sie Code beitragen möchten, lesen Sie bitte unseren [Contribution Guide](
 
 ## Gemeinschaft & Kontakt
 
-* [Github Discussion](https://github.com/langgenius/dify/discussions). Am besten geeignet für: den Austausch von Feedback und das Stellen von Fragen.
+* [GitHub Discussion](https://github.com/langgenius/dify/discussions). Am besten geeignet für: den Austausch von Feedback und das Stellen von Fragen.
 * [GitHub Issues](https://github.com/langgenius/dify/issues). Am besten für: Fehler, auf die Sie bei der Verwendung von Dify.AI stoßen, und Funktionsvorschläge. Siehe unseren [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
 * [Discord](https://discord.gg/FngNHpbcY7).  Am besten geeignet für: den Austausch von Bewerbungen und den Austausch mit der Community.
 * [X(Twitter)](https://twitter.com/dify_ai). Am besten geeignet für: den Austausch von Bewerbungen und den Austausch mit der Community.

README_JA.md

@@ -236,7 +236,7 @@ docker compose up -d
 
 ## コミュニティ & お問い合わせ
 
-* [Github Discussion](https://github.com/langgenius/dify/discussions). 主に: フィードバックの共有や質問。
+* [GitHub Discussion](https://github.com/langgenius/dify/discussions). 主に: フィードバックの共有や質問。
 * [GitHub Issues](https://github.com/langgenius/dify/issues). 主に: Dify.AIを使用する際に発生するエラーや問題については、[貢献ガイド](CONTRIBUTING_JA.md)を参照してください
 * [Discord](https://discord.gg/FngNHpbcY7). 主に: アプリケーションの共有やコミュニティとの交流。
 * [X(Twitter)](https://twitter.com/dify_ai). 主に: アプリケーションの共有やコミュニティとの交流。

README_KL.md

@@ -235,7 +235,7 @@ At the same time, please consider supporting Dify by sharing it on social media
 
 ## Community & Contact
 
-* [Github Discussion](https://github.com/langgenius/dify/discussions
+* [GitHub Discussion](https://github.com/langgenius/dify/discussions
 
 ). Best for: sharing feedback and asking questions.
 * [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).

README_KR.md

@@ -229,7 +229,7 @@ Dify를 Kubernetes에 배포하고 프리미엄 스케일링 설정을 구성했
 
 ## 커뮤니티 & 연락처
 
-* [Github 토론](https://github.com/langgenius/dify/discussions). 피드백 공유 및 질문하기에 적합합니다.
+* [GitHub 토론](https://github.com/langgenius/dify/discussions). 피드백 공유 및 질문하기에 적합합니다.
 * [GitHub 이슈](https://github.com/langgenius/dify/issues). Dify.AI 사용 중 발견한 버그와 기능 제안에 적합합니다. [기여 가이드](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)를 참조하세요. 
 * [디스코드](https://discord.gg/FngNHpbcY7). 애플리케이션 공유 및 커뮤니티와 소통하기에 적합합니다.
 * [트위터](https://twitter.com/dify_ai). 애플리케이션 공유 및 커뮤니티와 소통하기에 적합합니다.

README_SI.md

@@ -229,7 +229,7 @@ Za tiste, ki bi radi prispevali kodo, si oglejte naš vodnik za prispevke . Hkra
 
 ## Skupnost in stik
 
-* [Github Discussion](https://github.com/langgenius/dify/discussions). Najboljše za: izmenjavo povratnih informacij in postavljanje vprašanj.
+* [GitHub Discussion](https://github.com/langgenius/dify/discussions). Najboljše za: izmenjavo povratnih informacij in postavljanje vprašanj.
 * [GitHub Issues](https://github.com/langgenius/dify/issues). Najboljše za: hrošče, na katere naletite pri uporabi Dify.AI, in predloge funkcij. Oglejte si naš [vodnik za prispevke](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
 * [Discord](https://discord.gg/FngNHpbcY7). Najboljše za: deljenje vaših aplikacij in druženje s skupnostjo.
 * [X(Twitter)](https://twitter.com/dify_ai). Najboljše za: deljenje vaših aplikacij in druženje s skupnostjo.

README_TR.md

@@ -227,7 +227,7 @@ Aynı zamanda, lütfen Dify'ı sosyal medyada, etkinliklerde ve konferanslarda p
 
 ## Topluluk & iletişim
 
-* [Github Tartışmaları](https://github.com/langgenius/dify/discussions). En uygun: geri bildirim paylaşmak ve soru sormak için.
+* [GitHub Tartışmaları](https://github.com/langgenius/dify/discussions). En uygun: geri bildirim paylaşmak ve soru sormak için.
 * [GitHub Sorunları](https://github.com/langgenius/dify/issues). En uygun: Dify.AI kullanırken karşılaştığınız hatalar ve özellik önerileri için. [Katkı Kılavuzumuza](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) bakın.
 * [Discord](https://discord.gg/FngNHpbcY7). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.
 * [X(Twitter)](https://twitter.com/dify_ai). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.

README_TW.md

@@ -233,7 +233,7 @@ Dify 的所有功能都提供相應的 API，因此您可以輕鬆地將 Dify
 
 ## 社群與聯絡方式
 
-- [Github Discussion](https://github.com/langgenius/dify/discussions)：最適合分享反饋和提問。
+- [GitHub Discussion](https://github.com/langgenius/dify/discussions)：最適合分享反饋和提問。
 - [GitHub Issues](https://github.com/langgenius/dify/issues)：最適合報告使用 Dify.AI 時遇到的問題和提出功能建議。請參閱我們的[貢獻指南](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)。
 - [Discord](https://discord.gg/FngNHpbcY7)：最適合分享您的應用程式並與社群互動。
 - [X(Twitter)](https://twitter.com/dify_ai)：最適合分享您的應用程式並與社群互動。

api/.env.example

@@ -152,6 +152,7 @@ QDRANT_API_KEY=difyai123456
 QDRANT_CLIENT_TIMEOUT=20
 QDRANT_GRPC_ENABLED=false
 QDRANT_GRPC_PORT=6334
+QDRANT_REPLICATION_FACTOR=1
 
 #Couchbase configuration
 COUCHBASE_CONNECTION_STRING=127.0.0.1
@@ -269,6 +270,7 @@ OPENSEARCH_PORT=9200
 OPENSEARCH_USER=admin
 OPENSEARCH_PASSWORD=admin
 OPENSEARCH_SECURE=true
+OPENSEARCH_VERIFY_CERTS=true
 
 # Baidu configuration
 BAIDU_VECTOR_DB_ENDPOINT=http://127.0.0.1:5287
@@ -489,3 +491,10 @@ OTEL_METRIC_EXPORT_TIMEOUT=30000
 
 # Prevent Clickjacking
 ALLOW_EMBED=false
+
+# Dataset queue monitor configuration
+QUEUE_MONITOR_THRESHOLD=200
+# You can configure multiple ones, separated by commas. eg: test1@dify.ai,test2@dify.ai
+QUEUE_MONITOR_ALERT_EMAILS=
+# Monitor interval in minutes, default is 30 minutes
+QUEUE_MONITOR_INTERVAL=30

api/commands.py

@@ -846,6 +846,9 @@ def clear_orphaned_file_records(force: bool):
         {"type": "text", "table": "workflow_node_executions", "column": "outputs"},
         {"type": "text", "table": "conversations", "column": "introduction"},
         {"type": "text", "table": "conversations", "column": "system_instruction"},
+        {"type": "text", "table": "accounts", "column": "avatar"},
+        {"type": "text", "table": "apps", "column": "icon"},
+        {"type": "text", "table": "sites", "column": "icon"},
         {"type": "json", "table": "messages", "column": "inputs"},
         {"type": "json", "table": "messages", "column": "message"},
     ]

api/configs/middleware/__init__.py

@@ -2,7 +2,7 @@ import os
 from typing import Any, Literal, Optional
 from urllib.parse import parse_qsl, quote_plus
 
-from pydantic import Field, NonNegativeInt, PositiveFloat, PositiveInt, computed_field
+from pydantic import Field, NonNegativeFloat, NonNegativeInt, PositiveFloat, PositiveInt, computed_field
 from pydantic_settings import BaseSettings
 
 from .cache.redis_config import RedisConfig
@@ -256,6 +256,25 @@ class InternalTestConfig(BaseSettings):
     )
 
 
+class DatasetQueueMonitorConfig(BaseSettings):
+    """
+    Configuration settings for Dataset Queue Monitor
+    """
+
+    QUEUE_MONITOR_THRESHOLD: Optional[NonNegativeInt] = Field(
+        description="Threshold for dataset queue monitor",
+        default=200,
+    )
+    QUEUE_MONITOR_ALERT_EMAILS: Optional[str] = Field(
+        description="Emails for dataset queue monitor alert, separated by commas",
+        default=None,
+    )
+    QUEUE_MONITOR_INTERVAL: Optional[NonNegativeFloat] = Field(
+        description="Interval for dataset queue monitor in minutes",
+        default=30,
+    )
+
+
 class MiddlewareConfig(
     # place the configs in alphabet order
     CeleryConfig,
@@ -303,5 +322,6 @@ class MiddlewareConfig(
     BaiduVectorDBConfig,
     OpenGaussConfig,
     TableStoreConfig,
+    DatasetQueueMonitorConfig,
 ):
     pass

api/configs/middleware/storage/amazon_s3_storage_config.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Literal, Optional
 
 from pydantic import Field
 from pydantic_settings import BaseSettings
@@ -34,7 +34,7 @@ class S3StorageConfig(BaseSettings):
         default=None,
     )
 
-    S3_ADDRESS_STYLE: str = Field(
+    S3_ADDRESS_STYLE: Literal["auto", "virtual", "path"] = Field(
         description="S3 addressing style: 'auto', 'path', or 'virtual'",
         default="auto",
     )

api/configs/middleware/vdb/opensearch_config.py

@@ -33,6 +33,11 @@ class OpenSearchConfig(BaseSettings):
         default=False,
     )
 
+    OPENSEARCH_VERIFY_CERTS: bool = Field(
+        description="Whether to verify SSL certificates for HTTPS connections (recommended to set True in production)",
+        default=True,
+    )
+
     OPENSEARCH_AUTH_METHOD: AuthMethod = Field(
         description="Authentication method for OpenSearch connection (default is 'basic')",
         default=AuthMethod.BASIC,

api/configs/middleware/vdb/qdrant_config.py

@@ -33,3 +33,8 @@ class QdrantConfig(BaseSettings):
         description="Port number for gRPC connection to Qdrant server (default is 6334)",
         default=6334,
     )
+
+    QDRANT_REPLICATION_FACTOR: PositiveInt = Field(
+        description="Replication factor for Qdrant collections (default is 1)",
+        default=1,
+    )

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description="Dify version",
-        default="1.4.0",
+        default="1.4.1",
     )
 
     COMMIT_SHA: str = Field(

api/configs/remote_settings_sources/nacos/http_request.py

@@ -60,8 +60,7 @@ class NacosHttpClient:
             sign_str = tenant + "+"
         if group:
             sign_str = sign_str + group + "+"
-        if sign_str:
-            sign_str += ts
+        sign_str += ts  # Directly concatenate ts without conditional checks, because the nacos auth header forced it.
         return sign_str
 
     def get_access_token(self, force_refresh=False):

api/contexts/__init__.py

@@ -11,10 +11,6 @@ if TYPE_CHECKING:
     from core.workflow.entities.variable_pool import VariablePool
 
 
-tenant_id: ContextVar[str] = ContextVar("tenant_id")
-
-workflow_variable_pool: ContextVar["VariablePool"] = ContextVar("workflow_variable_pool")
-
 """
 To avoid race-conditions caused by gunicorn thread recycling, using RecyclableContextVar to replace with
 """

api/controllers/console/app/workflow_app_log.py

@@ -6,12 +6,12 @@ from sqlalchemy.orm import Session
 from controllers.console import api
 from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import account_initialization_required, setup_required
+from core.workflow.entities.workflow_execution import WorkflowExecutionStatus
 from extensions.ext_database import db
 from fields.workflow_app_log_fields import workflow_app_log_pagination_fields
 from libs.login import login_required
 from models import App
 from models.model import AppMode
-from models.workflow import WorkflowRunStatus
 from services.workflow_app_service import WorkflowAppService
 
 
@@ -38,7 +38,7 @@ class WorkflowAppLogApi(Resource):
         parser.add_argument("limit", type=int_range(1, 100), default=20, location="args")
         args = parser.parse_args()
 
-        args.status = WorkflowRunStatus(args.status) if args.status else None
+        args.status = WorkflowExecutionStatus(args.status) if args.status else None
         if args.created_at__before:
             args.created_at__before = isoparse(args.created_at__before)
 

api/controllers/console/auth/login.py

@@ -202,18 +202,18 @@ class EmailCodeLoginApi(Resource):
         except AccountRegisterError as are:
             raise AccountInFreezeError()
         if account:
-            tenant = TenantService.get_join_tenants(account)
-            if not tenant:
+            tenants = TenantService.get_join_tenants(account)
+            if not tenants:
                 workspaces = FeatureService.get_system_features().license.workspaces
                 if not workspaces.is_available():
                     raise WorkspacesLimitExceeded()
                 if not FeatureService.get_system_features().is_allow_create_workspace:
                     raise NotAllowedCreateWorkspace()
                 else:
-                    tenant = TenantService.create_tenant(f"{account.name}'s Workspace")
-                    TenantService.create_tenant_member(tenant, account, role="owner")
-                    account.current_tenant = tenant
-                    tenant_was_created.send(tenant)
+                    new_tenant = TenantService.create_tenant(f"{account.name}'s Workspace")
+                    TenantService.create_tenant_member(new_tenant, account, role="owner")
+                    account.current_tenant = new_tenant
+                    tenant_was_created.send(new_tenant)
 
         if account is None:
             try:

api/controllers/console/auth/oauth.py

@@ -148,15 +148,15 @@ def _generate_account(provider: str, user_info: OAuthUserInfo):
     account = _get_account_by_openid_or_email(provider, user_info)
 
     if account:
-        tenant = TenantService.get_join_tenants(account)
-        if not tenant:
+        tenants = TenantService.get_join_tenants(account)
+        if not tenants:
             if not FeatureService.get_system_features().is_allow_create_workspace:
                 raise WorkSpaceNotAllowedCreateError()
             else:
-                tenant = TenantService.create_tenant(f"{account.name}'s Workspace")
-                TenantService.create_tenant_member(tenant, account, role="owner")
-                account.current_tenant = tenant
-                tenant_was_created.send(tenant)
+                new_tenant = TenantService.create_tenant(f"{account.name}'s Workspace")
+                TenantService.create_tenant_member(new_tenant, account, role="owner")
+                account.current_tenant = new_tenant
+                tenant_was_created.send(new_tenant)
 
     if not account:
         if not FeatureService.get_system_features().is_allow_register:

api/controllers/console/datasets/datasets.py

@@ -540,9 +540,22 @@ class DatasetIndexingStatusApi(Resource):
                 .filter(DocumentSegment.document_id == str(document.id), DocumentSegment.status != "re_segment")
                 .count()
             )
-            document.completed_segments = completed_segments
-            document.total_segments = total_segments
-            documents_status.append(marshal(document, document_status_fields))
+            # Create a dictionary with document attributes and additional fields
+            document_dict = {
+                "id": document.id,
+                "indexing_status": document.indexing_status,
+                "processing_started_at": document.processing_started_at,
+                "parsing_completed_at": document.parsing_completed_at,
+                "cleaning_completed_at": document.cleaning_completed_at,
+                "splitting_completed_at": document.splitting_completed_at,
+                "completed_at": document.completed_at,
+                "paused_at": document.paused_at,
+                "error": document.error,
+                "stopped_at": document.stopped_at,
+                "completed_segments": completed_segments,
+                "total_segments": total_segments,
+            }
+            documents_status.append(marshal(document_dict, document_status_fields))
         data = {"data": documents_status}
         return data
 

api/controllers/console/datasets/datasets_document.py

@@ -583,11 +583,22 @@ class DocumentBatchIndexingStatusApi(DocumentResource):
                 .filter(DocumentSegment.document_id == str(document.id), DocumentSegment.status != "re_segment")
                 .count()
             )
-            document.completed_segments = completed_segments
-            document.total_segments = total_segments
-            if document.is_paused:
-                document.indexing_status = "paused"
-            documents_status.append(marshal(document, document_status_fields))
+            # Create a dictionary with document attributes and additional fields
+            document_dict = {
+                "id": document.id,
+                "indexing_status": "paused" if document.is_paused else document.indexing_status,
+                "processing_started_at": document.processing_started_at,
+                "parsing_completed_at": document.parsing_completed_at,
+                "cleaning_completed_at": document.cleaning_completed_at,
+                "splitting_completed_at": document.splitting_completed_at,
+                "completed_at": document.completed_at,
+                "paused_at": document.paused_at,
+                "error": document.error,
+                "stopped_at": document.stopped_at,
+                "completed_segments": completed_segments,
+                "total_segments": total_segments,
+            }
+            documents_status.append(marshal(document_dict, document_status_fields))
         data = {"data": documents_status}
         return data
 
@@ -616,11 +627,22 @@ class DocumentIndexingStatusApi(DocumentResource):
             .count()
         )
 
-        document.completed_segments = completed_segments
-        document.total_segments = total_segments
-        if document.is_paused:
-            document.indexing_status = "paused"
-        return marshal(document, document_status_fields)
+        # Create a dictionary with document attributes and additional fields
+        document_dict = {
+            "id": document.id,
+            "indexing_status": "paused" if document.is_paused else document.indexing_status,
+            "processing_started_at": document.processing_started_at,
+            "parsing_completed_at": document.parsing_completed_at,
+            "cleaning_completed_at": document.cleaning_completed_at,
+            "splitting_completed_at": document.splitting_completed_at,
+            "completed_at": document.completed_at,
+            "paused_at": document.paused_at,
+            "error": document.error,
+            "stopped_at": document.stopped_at,
+            "completed_segments": completed_segments,
+            "total_segments": total_segments,
+        }
+        return marshal(document_dict, document_status_fields)
 
 
 class DocumentDetailApi(DocumentResource):

api/controllers/console/workspace/plugin.py

@@ -41,12 +41,16 @@ class PluginListApi(Resource):
     @account_initialization_required
     def get(self):
         tenant_id = current_user.current_tenant_id
+        parser = reqparse.RequestParser()
+        parser.add_argument("page", type=int, required=False, location="args", default=1)
+        parser.add_argument("page_size", type=int, required=False, location="args", default=256)
+        args = parser.parse_args()
         try:
-            plugins = PluginService.list(tenant_id)
+            plugins_with_total = PluginService.list_with_total(tenant_id, args["page"], args["page_size"])
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
-        return jsonable_encoder({"plugins": plugins})
+        return jsonable_encoder({"plugins": plugins_with_total.list, "total": plugins_with_total.total})
 
 
 class PluginListLatestVersionsApi(Resource):

api/controllers/console/workspace/workspace.py

@@ -68,16 +68,24 @@ class TenantListApi(Resource):
     @account_initialization_required
     def get(self):
         tenants = TenantService.get_join_tenants(current_user)
+        tenant_dicts = []
 
         for tenant in tenants:
             features = FeatureService.get_features(tenant.id)
-            if features.billing.enabled:
-                tenant.plan = features.billing.subscription.plan
-            else:
-                tenant.plan = "sandbox"
-            if tenant.id == current_user.current_tenant_id:
-                tenant.current = True  # Set current=True for current tenant
-        return {"workspaces": marshal(tenants, tenants_fields)}, 200
+
+            # Create a dictionary with tenant attributes
+            tenant_dict = {
+                "id": tenant.id,
+                "name": tenant.name,
+                "status": tenant.status,
+                "created_at": tenant.created_at,
+                "plan": features.billing.subscription.plan if features.billing.enabled else "sandbox",
+                "current": tenant.id == current_user.current_tenant_id,
+            }
+
+            tenant_dicts.append(tenant_dict)
+
+        return {"workspaces": marshal(tenant_dicts, tenants_fields)}, 200
 
 
 class WorkspaceListApi(Resource):

api/controllers/files/upload.py

@@ -64,9 +64,24 @@ class PluginUploadFileApi(Resource):
 
             extension = guess_extension(tool_file.mimetype) or ".bin"
             preview_url = ToolFileManager.sign_file(tool_file_id=tool_file.id, extension=extension)
-            tool_file.mime_type = mimetype
-            tool_file.extension = extension
-            tool_file.preview_url = preview_url
+
+            # Create a dictionary with all the necessary attributes
+            result = {
+                "id": tool_file.id,
+                "user_id": tool_file.user_id,
+                "tenant_id": tool_file.tenant_id,
+                "conversation_id": tool_file.conversation_id,
+                "file_key": tool_file.file_key,
+                "mimetype": tool_file.mimetype,
+                "original_url": tool_file.original_url,
+                "name": tool_file.name,
+                "size": tool_file.size,
+                "mime_type": mimetype,
+                "extension": extension,
+                "preview_url": preview_url,
+            }
+
+            return result, 201
         except services.errors.file.FileTooLargeError as file_too_large_error:
             raise FileTooLargeError(file_too_large_error.description)
         except services.errors.file.UnsupportedFileTypeError:

api/controllers/inner_api/plugin/wraps.py

@@ -2,12 +2,14 @@ from collections.abc import Callable
 from functools import wraps
 from typing import Optional
 
-from flask import request
+from flask import current_app, request
+from flask_login import user_logged_in
 from flask_restful import reqparse
 from pydantic import BaseModel
 from sqlalchemy.orm import Session
 
 from extensions.ext_database import db
+from libs.login import _get_user
 from models.account import Account, Tenant
 from models.model import EndUser
 from services.account_service import AccountService
@@ -80,7 +82,12 @@ def get_user_tenant(view: Optional[Callable] = None):
                 raise ValueError("tenant not found")
 
             kwargs["tenant_model"] = tenant_model
-            kwargs["user_model"] = get_user(tenant_id, user_id)
+
+            user = get_user(tenant_id, user_id)
+            kwargs["user_model"] = user
+
+            current_app.login_manager._update_request_context_with_user(user)  # type: ignore
+            user_logged_in.send(current_app._get_current_object(), user=_get_user())  # type: ignore
 
             return view_func(*args, **kwargs)
 

api/controllers/service_api/app/annotation.py

@@ -3,19 +3,19 @@ from flask_restful import Resource, marshal, marshal_with, reqparse
 from werkzeug.exceptions import Forbidden
 
 from controllers.service_api import api
-from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
+from controllers.service_api.wraps import validate_app_token
 from extensions.ext_redis import redis_client
 from fields.annotation_fields import (
     annotation_fields,
 )
 from libs.login import current_user
-from models.model import App, EndUser
+from models.model import App
 from services.annotation_service import AppAnnotationService
 
 
 class AnnotationReplyActionApi(Resource):
-    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON))
-    def post(self, app_model: App, end_user: EndUser, action):
+    @validate_app_token
+    def post(self, app_model: App, action):
         parser = reqparse.RequestParser()
         parser.add_argument("score_threshold", required=True, type=float, location="json")
         parser.add_argument("embedding_provider_name", required=True, type=str, location="json")
@@ -31,8 +31,8 @@ class AnnotationReplyActionApi(Resource):
 
 
 class AnnotationReplyActionStatusApi(Resource):
-    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.QUERY))
-    def get(self, app_model: App, end_user: EndUser, job_id, action):
+    @validate_app_token
+    def get(self, app_model: App, job_id, action):
         job_id = str(job_id)
         app_annotation_job_key = "{}_app_annotation_job_{}".format(action, str(job_id))
         cache_result = redis_client.get(app_annotation_job_key)
@@ -49,8 +49,8 @@ class AnnotationReplyActionStatusApi(Resource):
 
 
 class AnnotationListApi(Resource):
-    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.QUERY))
-    def get(self, app_model: App, end_user: EndUser):
+    @validate_app_token
+    def get(self, app_model: App):
         page = request.args.get("page", default=1, type=int)
         limit = request.args.get("limit", default=20, type=int)
         keyword = request.args.get("keyword", default="", type=str)
@@ -65,9 +65,9 @@ class AnnotationListApi(Resource):
         }
         return response, 200
 
-    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON))
+    @validate_app_token
     @marshal_with(annotation_fields)
-    def post(self, app_model: App, end_user: EndUser):
+    def post(self, app_model: App):
         parser = reqparse.RequestParser()
         parser.add_argument("question", required=True, type=str, location="json")
         parser.add_argument("answer", required=True, type=str, location="json")
@@ -77,9 +77,9 @@ class AnnotationListApi(Resource):
 
 
 class AnnotationUpdateDeleteApi(Resource):
-    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.JSON))
+    @validate_app_token
     @marshal_with(annotation_fields)
-    def put(self, app_model: App, end_user: EndUser, annotation_id):
+    def put(self, app_model: App, annotation_id):
         if not current_user.is_editor:
             raise Forbidden()
 
@@ -91,8 +91,8 @@ class AnnotationUpdateDeleteApi(Resource):
         annotation = AppAnnotationService.update_app_annotation_directly(args, app_model.id, annotation_id)
         return annotation
 
-    @validate_app_token(fetch_user_arg=FetchUserArg(fetch_from=WhereisUserArg.QUERY))
-    def delete(self, app_model: App, end_user: EndUser, annotation_id):
+    @validate_app_token
+    def delete(self, app_model: App, annotation_id):
         if not current_user.is_editor:
             raise Forbidden()
 

api/controllers/service_api/app/workflow.py

@@ -24,12 +24,13 @@ from core.errors.error import (
     QuotaExceededError,
 )
 from core.model_runtime.errors.invoke import InvokeError
+from core.workflow.entities.workflow_execution import WorkflowExecutionStatus
 from extensions.ext_database import db
 from fields.workflow_app_log_fields import workflow_app_log_pagination_fields
 from libs import helper
 from libs.helper import TimestampField
 from models.model import App, AppMode, EndUser
-from models.workflow import WorkflowRun, WorkflowRunStatus
+from models.workflow import WorkflowRun
 from services.app_generate_service import AppGenerateService
 from services.errors.llm import InvokeRateLimitError
 from services.workflow_app_service import WorkflowAppService
@@ -138,7 +139,7 @@ class WorkflowAppLogApi(Resource):
         parser.add_argument("limit", type=int_range(1, 100), default=20, location="args")
         args = parser.parse_args()
 
-        args.status = WorkflowRunStatus(args.status) if args.status else None
+        args.status = WorkflowExecutionStatus(args.status) if args.status else None
         if args.created_at__before:
             args.created_at__before = isoparse(args.created_at__before)
 

api/controllers/service_api/dataset/dataset.py

@@ -1,19 +1,21 @@
 from flask import request
-from flask_restful import marshal, reqparse
+from flask_restful import marshal, marshal_with, reqparse
 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.wraps import DatasetApiResource
+from controllers.service_api.wraps import DatasetApiResource, validate_dataset_token
 from core.model_runtime.entities.model_entities import ModelType
 from core.plugin.entities.plugin import ModelProviderID
 from core.provider_manager import ProviderManager
 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.entities.knowledge_entities.knowledge_entities import RetrievalModel
+from services.tag_service import TagService
 
 
 def _validate_name(name):
@@ -320,5 +322,135 @@ class DatasetApi(DatasetApiResource):
             raise DatasetInUseError()
 
 
+class DatasetTagsApi(DatasetApiResource):
+    @validate_dataset_token
+    @marshal_with(tag_fields)
+    def get(self, _, dataset_id):
+        """Get all knowledge type tags."""
+        tags = TagService.get_tags("knowledge", current_user.current_tenant_id)
+
+        return tags, 200
+
+    @validate_dataset_token
+    def post(self, _, dataset_id):
+        """Add a knowledge type tag."""
+        if not (current_user.is_editor or current_user.is_dataset_editor):
+            raise Forbidden()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument(
+            "name",
+            nullable=False,
+            required=True,
+            help="Name must be between 1 to 50 characters.",
+            type=DatasetTagsApi._validate_tag_name,
+        )
+
+        args = parser.parse_args()
+        args["type"] = "knowledge"
+        tag = TagService.save_tags(args)
+
+        response = {"id": tag.id, "name": tag.name, "type": tag.type, "binding_count": 0}
+
+        return response, 200
+
+    @validate_dataset_token
+    def patch(self, _, dataset_id):
+        if not (current_user.is_editor or current_user.is_dataset_editor):
+            raise Forbidden()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument(
+            "name",
+            nullable=False,
+            required=True,
+            help="Name must be between 1 to 50 characters.",
+            type=DatasetTagsApi._validate_tag_name,
+        )
+        parser.add_argument("tag_id", nullable=False, required=True, help="Id of a tag.", type=str)
+        args = parser.parse_args()
+        args["type"] = "knowledge"
+        tag = TagService.update_tags(args, args.get("tag_id"))
+
+        binding_count = TagService.get_tag_binding_count(args.get("tag_id"))
+
+        response = {"id": tag.id, "name": tag.name, "type": tag.type, "binding_count": binding_count}
+
+        return response, 200
+
+    @validate_dataset_token
+    def delete(self, _, dataset_id):
+        """Delete a knowledge type tag."""
+        if not current_user.is_editor:
+            raise Forbidden()
+        parser = reqparse.RequestParser()
+        parser.add_argument("tag_id", nullable=False, required=True, help="Id of a tag.", type=str)
+        args = parser.parse_args()
+        TagService.delete_tag(args.get("tag_id"))
+
+        return 204
+
+    @staticmethod
+    def _validate_tag_name(name):
+        if not name or len(name) < 1 or len(name) > 50:
+            raise ValueError("Name must be between 1 to 50 characters.")
+        return name
+
+
+class DatasetTagBindingApi(DatasetApiResource):
+    @validate_dataset_token
+    def post(self, _, dataset_id):
+        # The role of the current user in the ta table must be admin, owner, editor, or dataset_operator
+        if not (current_user.is_editor or current_user.is_dataset_editor):
+            raise Forbidden()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument(
+            "tag_ids", type=list, nullable=False, required=True, location="json", help="Tag IDs is required."
+        )
+        parser.add_argument(
+            "target_id", type=str, nullable=False, required=True, location="json", help="Target Dataset ID is required."
+        )
+
+        args = parser.parse_args()
+        args["type"] = "knowledge"
+        TagService.save_tag_binding(args)
+
+        return 204
+
+
+class DatasetTagUnbindingApi(DatasetApiResource):
+    @validate_dataset_token
+    def post(self, _, dataset_id):
+        # The role of the current user in the ta table must be admin, owner, editor, or dataset_operator
+        if not (current_user.is_editor or current_user.is_dataset_editor):
+            raise Forbidden()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument("tag_id", type=str, nullable=False, required=True, help="Tag ID is required.")
+        parser.add_argument("target_id", type=str, nullable=False, required=True, help="Target ID is required.")
+
+        args = parser.parse_args()
+        args["type"] = "knowledge"
+        TagService.delete_tag_binding(args)
+
+        return 204
+
+
+class DatasetTagsBindingStatusApi(DatasetApiResource):
+    @validate_dataset_token
+    def get(self, _, *args, **kwargs):
+        """Get all knowledge type tags."""
+        dataset_id = kwargs.get("dataset_id")
+        tags = TagService.get_tags_by_target_id("knowledge", current_user.current_tenant_id, str(dataset_id))
+        tags_list = [{"id": tag.id, "name": tag.name} for tag in tags]
+        response = {"data": tags_list, "total": len(tags)}
+        return response, 200
+
+
 api.add_resource(DatasetListApi, "/datasets")
 api.add_resource(DatasetApi, "/datasets/<uuid:dataset_id>")
+api.add_resource(DatasetTagsApi, "/datasets/tags")
+api.add_resource(DatasetTagBindingApi, "/datasets/tags/binding")
+api.add_resource(DatasetTagUnbindingApi, "/datasets/tags/unbinding")
+api.add_resource(DatasetTagsBindingStatusApi, "/datasets/<uuid:dataset_id>/tags")

api/controllers/service_api/dataset/document.py

@@ -175,8 +175,11 @@ class DocumentAddByFileApi(DatasetApiResource):
 
         if not dataset:
             raise ValueError("Dataset does not exist.")
-        if not dataset.indexing_technique and not args.get("indexing_technique"):
+
+        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
 
         # save file info
         file = request.files["file"]
@@ -206,12 +209,16 @@ class DocumentAddByFileApi(DatasetApiResource):
         knowledge_config = KnowledgeConfig(**args)
         DocumentService.document_create_args_validate(knowledge_config)
 
+        dataset_process_rule = dataset.latest_process_rule if "process_rule" not in args else None
+        if not knowledge_config.original_document_id and not dataset_process_rule and not knowledge_config.process_rule:
+            raise ValueError("process_rule is required.")
+
         try:
             documents, batch = DocumentService.save_document_with_dataset_id(
                 dataset=dataset,
                 knowledge_config=knowledge_config,
                 account=dataset.created_by_account,
-                dataset_process_rule=dataset.latest_process_rule if "process_rule" not in args else None,
+                dataset_process_rule=dataset_process_rule,
                 created_from="api",
             )
         except ProviderTokenNotInitError as ex:
@@ -388,11 +395,22 @@ class DocumentIndexingStatusApi(DatasetApiResource):
                 .filter(DocumentSegment.document_id == str(document.id), DocumentSegment.status != "re_segment")
                 .count()
             )
-            document.completed_segments = completed_segments
-            document.total_segments = total_segments
-            if document.is_paused:
-                document.indexing_status = "paused"
-            documents_status.append(marshal(document, document_status_fields))
+            # Create a dictionary with document attributes and additional fields
+            document_dict = {
+                "id": document.id,
+                "indexing_status": "paused" if document.is_paused else document.indexing_status,
+                "processing_started_at": document.processing_started_at,
+                "parsing_completed_at": document.parsing_completed_at,
+                "cleaning_completed_at": document.cleaning_completed_at,
+                "splitting_completed_at": document.splitting_completed_at,
+                "completed_at": document.completed_at,
+                "paused_at": document.paused_at,
+                "error": document.error,
+                "stopped_at": document.stopped_at,
+                "completed_segments": completed_segments,
+                "total_segments": total_segments,
+            }
+            documents_status.append(marshal(document_dict, document_status_fields))
         data = {"data": documents_status}
         return data
 

api/controllers/service_api/dataset/segment.py

@@ -208,6 +208,28 @@ class DatasetSegmentApi(DatasetApiResource):
         )
         return {"data": marshal(updated_segment, segment_fields), "doc_form": document.doc_form}, 200
 
+    def get(self, tenant_id, dataset_id, document_id, segment_id):
+        # check dataset
+        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()
+        if not dataset:
+            raise NotFound("Dataset not found.")
+        # check user's model setting
+        DatasetService.check_dataset_model_setting(dataset)
+        # check document
+        document_id = str(document_id)
+        document = DocumentService.get_document(dataset_id, document_id)
+        if not document:
+            raise NotFound("Document not found.")
+        # check segment
+        segment_id = str(segment_id)
+        segment = SegmentService.get_segment_by_id(segment_id=segment_id, tenant_id=current_user.current_tenant_id)
+        if not segment:
+            raise NotFound("Segment not found.")
+
+        return {"data": marshal(segment, segment_fields), "doc_form": document.doc_form}, 200
+
 
 class ChildChunkApi(DatasetApiResource):
     """Resource for child chunks."""

api/controllers/service_api/wraps.py

@@ -99,7 +99,12 @@ def validate_app_token(view: Optional[Callable] = None, *, fetch_user_arg: Optio
                 if user_id:
                     user_id = str(user_id)
 
-                kwargs["end_user"] = create_or_update_end_user_for_user_id(app_model, user_id)
+                end_user = create_or_update_end_user_for_user_id(app_model, user_id)
+                kwargs["end_user"] = end_user
+
+                # Set EndUser as current logged-in user for flask_login.current_user
+                current_app.login_manager._update_request_context_with_user(end_user)  # type: ignore
+                user_logged_in.send(current_app._get_current_object(), user=end_user)  # type: ignore
 
             return view_func(*args, **kwargs)
 

api/core/agent/cot_agent_runner.py

@@ -63,7 +63,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
         self._instruction = self._fill_in_inputs_from_external_data_tools(instruction, inputs)
 
         iteration_step = 1
-        max_iteration_steps = min(app_config.agent.max_iteration if app_config.agent else 5, 5) + 1
+        max_iteration_steps = min(app_config.agent.max_iteration, 99) + 1
 
         # convert tools into ModelRuntime Tool format
         tool_instances, prompt_messages_tools = self._init_prompt_tools()

api/core/agent/entities.py

@@ -82,7 +82,7 @@ class AgentEntity(BaseModel):
     strategy: Strategy
     prompt: Optional[AgentPromptEntity] = None
     tools: Optional[list[AgentToolEntity]] = None
-    max_iteration: int = 5
+    max_iteration: int = 10
 
 
 class AgentInvokeMessage(ToolInvokeMessage):

api/core/agent/fc_agent_runner.py

@@ -48,7 +48,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
         assert app_config.agent
 
         iteration_step = 1
-        max_iteration_steps = min(app_config.agent.max_iteration, 5) + 1
+        max_iteration_steps = min(app_config.agent.max_iteration, 99) + 1
 
         # continue to run until there is not any tool call
         function_call_state = True

api/core/app/app_config/easy_ui_based_app/agent/manager.py

@@ -75,7 +75,7 @@ class AgentConfigManager:
                     strategy=strategy,
                     prompt=agent_prompt_entity,
                     tools=agent_tools,
-                    max_iteration=agent_dict.get("max_iteration", 5),
+                    max_iteration=agent_dict.get("max_iteration", 10),
                 )
 
         return None

api/core/app/app_config/easy_ui_based_app/model_config/converter.py

@@ -70,7 +70,7 @@ class ModelConfigConverter:
         if not model_mode:
             model_mode = LLMMode.CHAT.value
             if model_schema and model_schema.model_properties.get(ModelPropertyKey.MODE):
-                model_mode = LLMMode.value_of(model_schema.model_properties[ModelPropertyKey.MODE]).value
+                model_mode = LLMMode(model_schema.model_properties[ModelPropertyKey.MODE]).value
 
         if not model_schema:
             raise ValueError(f"Model {model_name} not exist.")

api/core/app/app_config/entities.py

@@ -109,6 +109,7 @@ class VariableEntity(BaseModel):
     description: str = ""
     type: VariableEntityType
     required: bool = False
+    hide: bool = False
     max_length: Optional[int] = None
     options: Sequence[str] = Field(default_factory=list)
     allowed_file_types: Sequence[FileType] = Field(default_factory=list)

api/core/app/apps/advanced_chat/app_generator.py

@@ -5,7 +5,7 @@ import uuid
 from collections.abc import Generator, Mapping
 from typing import Any, Literal, Optional, Union, overload
 
-from flask import Flask, current_app
+from flask import Flask, copy_current_request_context, current_app, has_request_context
 from pydantic import ValidationError
 from sqlalchemy.orm import sessionmaker
 
@@ -26,10 +26,13 @@ from core.model_runtime.errors.invoke import InvokeAuthorizationError
 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.workflow.repository.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository
+from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
+from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from extensions.ext_database import db
 from factories import file_factory
 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
 
@@ -155,12 +158,25 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             trace_manager=trace_manager,
             workflow_run_id=workflow_run_id,
         )
-        contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
         contexts.plugin_tool_providers.set({})
         contexts.plugin_tool_providers_lock.set(threading.Lock())
 
-        # Create workflow node execution repository
+        # Create repositories
+        #
+        # Create session factory
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
+        # Create workflow execution(aka workflow run) repository
+        if invoke_from == InvokeFrom.DEBUGGER:
+            workflow_triggered_from = WorkflowRunTriggeredFrom.DEBUGGING
+        else:
+            workflow_triggered_from = WorkflowRunTriggeredFrom.APP_RUN
+        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+            session_factory=session_factory,
+            user=user,
+            app_id=application_generate_entity.app_config.app_id,
+            triggered_from=workflow_triggered_from,
+        )
+        # Create workflow node execution repository
         workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
             session_factory=session_factory,
             user=user,
@@ -173,6 +189,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             user=user,
             invoke_from=invoke_from,
             application_generate_entity=application_generate_entity,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             conversation=conversation,
             stream=streaming,
@@ -222,12 +239,21 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 node_id=node_id, inputs=args["inputs"]
             ),
         )
-        contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
         contexts.plugin_tool_providers.set({})
         contexts.plugin_tool_providers_lock.set(threading.Lock())
 
-        # Create workflow node execution repository
+        # Create repositories
+        #
+        # Create session factory
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
+        # Create workflow execution(aka workflow run) repository
+        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+            session_factory=session_factory,
+            user=user,
+            app_id=application_generate_entity.app_config.app_id,
+            triggered_from=WorkflowRunTriggeredFrom.DEBUGGING,
+        )
+        # Create workflow node execution repository
         workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
             session_factory=session_factory,
             user=user,
@@ -240,6 +266,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             user=user,
             invoke_from=InvokeFrom.DEBUGGER,
             application_generate_entity=application_generate_entity,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             conversation=None,
             stream=streaming,
@@ -287,12 +314,21 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             extras={"auto_generate_conversation_name": False},
             single_loop_run=AdvancedChatAppGenerateEntity.SingleLoopRunEntity(node_id=node_id, inputs=args["inputs"]),
         )
-        contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
         contexts.plugin_tool_providers.set({})
         contexts.plugin_tool_providers_lock.set(threading.Lock())
 
-        # Create workflow node execution repository
+        # Create repositories
+        #
+        # Create session factory
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
+        # Create workflow execution(aka workflow run) repository
+        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+            session_factory=session_factory,
+            user=user,
+            app_id=application_generate_entity.app_config.app_id,
+            triggered_from=WorkflowRunTriggeredFrom.DEBUGGING,
+        )
+        # Create workflow node execution repository
         workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
             session_factory=session_factory,
             user=user,
@@ -305,6 +341,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             user=user,
             invoke_from=InvokeFrom.DEBUGGER,
             application_generate_entity=application_generate_entity,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             conversation=None,
             stream=streaming,
@@ -317,6 +354,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         user: Union[Account, EndUser],
         invoke_from: InvokeFrom,
         application_generate_entity: AdvancedChatAppGenerateEntity,
+        workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         conversation: Optional[Conversation] = None,
         stream: bool = True,
@@ -358,18 +396,23 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             message_id=message.id,
         )
 
-        # new thread
-        worker_thread = threading.Thread(
-            target=self._generate_worker,
-            kwargs={
-                "flask_app": current_app._get_current_object(),  # type: ignore
-                "application_generate_entity": application_generate_entity,
-                "queue_manager": queue_manager,
-                "conversation_id": conversation.id,
-                "message_id": message.id,
-                "context": contextvars.copy_context(),
-            },
-        )
+        # new thread with request context and contextvars
+        context = contextvars.copy_context()
+
+        @copy_current_request_context
+        def worker_with_context():
+            # Run the worker within the copied context
+            return context.run(
+                self._generate_worker,
+                flask_app=current_app._get_current_object(),  # type: ignore
+                application_generate_entity=application_generate_entity,
+                queue_manager=queue_manager,
+                conversation_id=conversation.id,
+                message_id=message.id,
+                context=context,
+            )
+
+        worker_thread = threading.Thread(target=worker_with_context)
 
         worker_thread.start()
 
@@ -381,6 +424,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             conversation=conversation,
             message=message,
             user=user,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             stream=stream,
         )
@@ -407,8 +451,22 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         """
         for var, val in context.items():
             var.set(val)
+
+        # FIXME(-LAN-): Save current user before entering new app context
+        from flask import g
+
+        saved_user = None
+        if has_request_context() and hasattr(g, "_login_user"):
+            saved_user = g._login_user
+
         with flask_app.app_context():
             try:
+                # Restore user in new app context
+                if saved_user is not None:
+                    from flask import g
+
+                    g._login_user = saved_user
+
                 # get conversation and message
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)
@@ -453,6 +511,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         conversation: Conversation,
         message: Message,
         user: Union[Account, EndUser],
+        workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         stream: bool = False,
     ) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
@@ -476,9 +535,10 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             conversation=conversation,
             message=message,
             user=user,
-            stream=stream,
             dialogue_count=self._dialogue_count,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
+            stream=stream,
         )
 
         try:

api/core/app/apps/advanced_chat/app_runner.py

@@ -140,7 +140,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
                 SystemVariableKey.DIALOGUE_COUNT: self._dialogue_count,
                 SystemVariableKey.APP_ID: app_config.app_id,
                 SystemVariableKey.WORKFLOW_ID: app_config.workflow_id,
-                SystemVariableKey.WORKFLOW_RUN_ID: self.application_generate_entity.workflow_run_id,
+                SystemVariableKey.WORKFLOW_EXECUTION_ID: self.application_generate_entity.workflow_run_id,
             }
 
             # init variable pool

api/core/app/apps/advanced_chat/generate_task_pipeline.py

@@ -1,4 +1,3 @@
-import json
 import logging
 import time
 from collections.abc import Generator, Mapping
@@ -10,6 +9,7 @@ from sqlalchemy.orm import Session
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
+from core.app.apps.common.workflow_response_converter import WorkflowResponseConverter
 from core.app.entities.app_invoke_entities import (
     AdvancedChatAppGenerateEntity,
     InvokeFrom,
@@ -56,25 +56,23 @@ from core.app.entities.task_entities import (
     WorkflowTaskState,
 )
 from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline
-from core.app.task_pipeline.message_cycle_manage import MessageCycleManage
+from core.app.task_pipeline.message_cycle_manager import MessageCycleManager
 from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
 from core.model_runtime.entities.llm_entities import LLMUsage
-from core.model_runtime.utils.encoders import jsonable_encoder
 from core.ops.ops_trace_manager import TraceQueueManager
+from core.workflow.entities.workflow_execution import WorkflowExecutionStatus, WorkflowType
 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.repository.workflow_node_execution_repository import WorkflowNodeExecutionRepository
-from core.workflow.workflow_cycle_manager import WorkflowCycleManager
+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
 from events.message_event import message_was_created
 from extensions.ext_database import db
 from models import Conversation, EndUser, Message, MessageFile
 from models.account import Account
 from models.enums import CreatorUserRole
-from models.workflow import (
-    Workflow,
-    WorkflowRunStatus,
-)
+from models.workflow import Workflow
 
 logger = logging.getLogger(__name__)
 
@@ -94,6 +92,7 @@ class AdvancedChatAppGenerateTaskPipeline:
         user: Union[Account, EndUser],
         stream: bool,
         dialogue_count: int,
+        workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
     ) -> None:
         self._base_task_pipeline = BasedGenerateTaskPipeline(
@@ -123,13 +122,24 @@ class AdvancedChatAppGenerateTaskPipeline:
                 SystemVariableKey.DIALOGUE_COUNT: dialogue_count,
                 SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
                 SystemVariableKey.WORKFLOW_ID: workflow.id,
-                SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
+                SystemVariableKey.WORKFLOW_EXECUTION_ID: application_generate_entity.workflow_run_id,
             },
+            workflow_info=CycleManagerWorkflowInfo(
+                workflow_id=workflow.id,
+                workflow_type=WorkflowType(workflow.type),
+                version=workflow.version,
+                graph_data=workflow.graph_dict,
+            ),
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
         )
 
+        self._workflow_response_converter = WorkflowResponseConverter(
+            application_generate_entity=application_generate_entity,
+        )
+
         self._task_state = WorkflowTaskState()
-        self._message_cycle_manager = MessageCycleManage(
+        self._message_cycle_manager = MessageCycleManager(
             application_generate_entity=application_generate_entity, task_state=self._task_state
         )
 
@@ -150,7 +160,7 @@ class AdvancedChatAppGenerateTaskPipeline:
         :return:
         """
         # start generate conversation name thread
-        self._conversation_name_generate_thread = self._message_cycle_manager._generate_conversation_name(
+        self._conversation_name_generate_thread = self._message_cycle_manager.generate_conversation_name(
             conversation_id=self._conversation_id, query=self._application_generate_entity.query
         )
 
@@ -294,19 +304,15 @@ class AdvancedChatAppGenerateTaskPipeline:
 
                 with Session(db.engine, expire_on_commit=False) as session:
                     # init workflow run
-                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_start(
-                        session=session,
-                        workflow_id=self._workflow_id,
-                        user_id=self._user_id,
-                        created_by_role=self._created_by_role,
-                    )
-                    self._workflow_run_id = workflow_run.id
+                    workflow_execution = self._workflow_cycle_manager.handle_workflow_run_start()
+                    self._workflow_run_id = workflow_execution.id_
                     message = self._get_message(session=session)
                     if not message:
                         raise ValueError(f"Message not found: {self._message_id}")
-                    message.workflow_run_id = workflow_run.id
-                    workflow_start_resp = self._workflow_cycle_manager._workflow_start_to_stream_response(
-                        session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
+                    message.workflow_run_id = workflow_execution.id_
+                    workflow_start_resp = self._workflow_response_converter.workflow_start_to_stream_response(
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution=workflow_execution,
                     )
                     session.commit()
 
@@ -319,13 +325,10 @@ class AdvancedChatAppGenerateTaskPipeline:
                     raise ValueError("workflow run not initialized.")
 
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
+                    workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_retried(
+                        workflow_execution_id=self._workflow_run_id, event=event
                     )
-                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_retried(
-                        workflow_run=workflow_run, event=event
-                    )
-                    node_retry_resp = self._workflow_cycle_manager._workflow_node_retry_to_stream_response(
+                    node_retry_resp = self._workflow_response_converter.workflow_node_retry_to_stream_response(
                         event=event,
                         task_id=self._application_generate_entity.task_id,
                         workflow_node_execution=workflow_node_execution,
@@ -338,20 +341,15 @@ class AdvancedChatAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    workflow_node_execution = self._workflow_cycle_manager._handle_node_execution_start(
-                        workflow_run=workflow_run, event=event
-                    )
+                workflow_node_execution = self._workflow_cycle_manager.handle_node_execution_start(
+                    workflow_execution_id=self._workflow_run_id, event=event
+                )
 
-                    node_start_resp = self._workflow_cycle_manager._workflow_node_start_to_stream_response(
-                        event=event,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_node_execution=workflow_node_execution,
-                    )
-                    session.commit()
+                node_start_resp = self._workflow_response_converter.workflow_node_start_to_stream_response(
+                    event=event,
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_node_execution=workflow_node_execution,
+                )
 
                 if node_start_resp:
                     yield node_start_resp
@@ -359,15 +357,15 @@ class AdvancedChatAppGenerateTaskPipeline:
                 # Record files if it's an answer node or end node
                 if event.node_type in [NodeType.ANSWER, NodeType.END]:
                     self._recorded_files.extend(
-                        self._workflow_cycle_manager._fetch_files_from_node_outputs(event.outputs or {})
+                        self._workflow_response_converter.fetch_files_from_node_outputs(event.outputs or {})
                     )
 
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
+                    workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_success(
                         event=event
                     )
 
-                    node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
+                    node_finish_resp = self._workflow_response_converter.workflow_node_finish_to_stream_response(
                         event=event,
                         task_id=self._application_generate_entity.task_id,
                         workflow_node_execution=workflow_node_execution,
@@ -383,11 +381,11 @@ class AdvancedChatAppGenerateTaskPipeline:
                 | QueueNodeInLoopFailedEvent
                 | QueueNodeExceptionEvent,
             ):
-                workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
+                workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_failed(
                     event=event
                 )
 
-                node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
+                node_finish_resp = self._workflow_response_converter.workflow_node_finish_to_stream_response(
                     event=event,
                     task_id=self._application_generate_entity.task_id,
                     workflow_node_execution=workflow_node_execution,
@@ -399,132 +397,92 @@ class AdvancedChatAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    parallel_start_resp = (
-                        self._workflow_cycle_manager._workflow_parallel_branch_start_to_stream_response(
-                            session=session,
-                            task_id=self._application_generate_entity.task_id,
-                            workflow_run=workflow_run,
-                            event=event,
-                        )
+                parallel_start_resp = (
+                    self._workflow_response_converter.workflow_parallel_branch_start_to_stream_response(
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution_id=self._workflow_run_id,
+                        event=event,
                     )
+                )
 
                 yield parallel_start_resp
             elif isinstance(event, QueueParallelBranchRunSucceededEvent | QueueParallelBranchRunFailedEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    parallel_finish_resp = (
-                        self._workflow_cycle_manager._workflow_parallel_branch_finished_to_stream_response(
-                            session=session,
-                            task_id=self._application_generate_entity.task_id,
-                            workflow_run=workflow_run,
-                            event=event,
-                        )
+                parallel_finish_resp = (
+                    self._workflow_response_converter.workflow_parallel_branch_finished_to_stream_response(
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution_id=self._workflow_run_id,
+                        event=event,
                     )
+                )
 
                 yield parallel_finish_resp
             elif isinstance(event, QueueIterationStartEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    iter_start_resp = self._workflow_cycle_manager._workflow_iteration_start_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                iter_start_resp = self._workflow_response_converter.workflow_iteration_start_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield iter_start_resp
             elif isinstance(event, QueueIterationNextEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    iter_next_resp = self._workflow_cycle_manager._workflow_iteration_next_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                iter_next_resp = self._workflow_response_converter.workflow_iteration_next_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield iter_next_resp
             elif isinstance(event, QueueIterationCompletedEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    iter_finish_resp = self._workflow_cycle_manager._workflow_iteration_completed_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                iter_finish_resp = self._workflow_response_converter.workflow_iteration_completed_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield iter_finish_resp
             elif isinstance(event, QueueLoopStartEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    loop_start_resp = self._workflow_cycle_manager._workflow_loop_start_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                loop_start_resp = self._workflow_response_converter.workflow_loop_start_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield loop_start_resp
             elif isinstance(event, QueueLoopNextEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    loop_next_resp = self._workflow_cycle_manager._workflow_loop_next_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                loop_next_resp = self._workflow_response_converter.workflow_loop_next_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield loop_next_resp
             elif isinstance(event, QueueLoopCompletedEvent):
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    loop_finish_resp = self._workflow_cycle_manager._workflow_loop_completed_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                loop_finish_resp = self._workflow_response_converter.workflow_loop_completed_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield loop_finish_resp
             elif isinstance(event, QueueWorkflowSucceededEvent):
@@ -535,10 +493,8 @@ class AdvancedChatAppGenerateTaskPipeline:
                     raise ValueError("workflow run not initialized.")
 
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_success(
-                        session=session,
+                    workflow_execution = self._workflow_cycle_manager.handle_workflow_run_success(
                         workflow_run_id=self._workflow_run_id,
-                        start_at=graph_runtime_state.start_at,
                         total_tokens=graph_runtime_state.total_tokens,
                         total_steps=graph_runtime_state.node_run_steps,
                         outputs=event.outputs,
@@ -546,10 +502,11 @@ class AdvancedChatAppGenerateTaskPipeline:
                         trace_manager=trace_manager,
                     )
 
-                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
-                        session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
+                    workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+                        session=session,
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution=workflow_execution,
                     )
-                    session.commit()
 
                 yield workflow_finish_resp
                 self._base_task_pipeline._queue_manager.publish(
@@ -562,10 +519,8 @@ class AdvancedChatAppGenerateTaskPipeline:
                     raise ValueError("graph runtime state not initialized.")
 
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_partial_success(
-                        session=session,
+                    workflow_execution = self._workflow_cycle_manager.handle_workflow_run_partial_success(
                         workflow_run_id=self._workflow_run_id,
-                        start_at=graph_runtime_state.start_at,
                         total_tokens=graph_runtime_state.total_tokens,
                         total_steps=graph_runtime_state.node_run_steps,
                         outputs=event.outputs,
@@ -573,10 +528,11 @@ class AdvancedChatAppGenerateTaskPipeline:
                         conversation_id=None,
                         trace_manager=trace_manager,
                     )
-                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
-                        session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
+                    workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+                        session=session,
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution=workflow_execution,
                     )
-                    session.commit()
 
                 yield workflow_finish_resp
                 self._base_task_pipeline._queue_manager.publish(
@@ -589,26 +545,25 @@ class AdvancedChatAppGenerateTaskPipeline:
                     raise ValueError("graph runtime state not initialized.")
 
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
-                        session=session,
+                    workflow_execution = self._workflow_cycle_manager.handle_workflow_run_failed(
                         workflow_run_id=self._workflow_run_id,
-                        start_at=graph_runtime_state.start_at,
                         total_tokens=graph_runtime_state.total_tokens,
                         total_steps=graph_runtime_state.node_run_steps,
-                        status=WorkflowRunStatus.FAILED,
-                        error=event.error,
+                        status=WorkflowExecutionStatus.FAILED,
+                        error_message=event.error,
                         conversation_id=self._conversation_id,
                         trace_manager=trace_manager,
                         exceptions_count=event.exceptions_count,
                     )
-                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
-                        session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
+                    workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+                        session=session,
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution=workflow_execution,
                     )
-                    err_event = QueueErrorEvent(error=ValueError(f"Run failed: {workflow_run.error}"))
+                    err_event = QueueErrorEvent(error=ValueError(f"Run failed: {workflow_execution.error_message}"))
                     err = self._base_task_pipeline._handle_error(
                         event=err_event, session=session, message_id=self._message_id
                     )
-                    session.commit()
 
                 yield workflow_finish_resp
                 yield self._base_task_pipeline._error_to_stream_response(err)
@@ -616,21 +571,19 @@ class AdvancedChatAppGenerateTaskPipeline:
             elif isinstance(event, QueueStopEvent):
                 if self._workflow_run_id and graph_runtime_state:
                     with Session(db.engine, expire_on_commit=False) as session:
-                        workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
-                            session=session,
+                        workflow_execution = self._workflow_cycle_manager.handle_workflow_run_failed(
                             workflow_run_id=self._workflow_run_id,
-                            start_at=graph_runtime_state.start_at,
                             total_tokens=graph_runtime_state.total_tokens,
                             total_steps=graph_runtime_state.node_run_steps,
-                            status=WorkflowRunStatus.STOPPED,
-                            error=event.get_stop_reason(),
+                            status=WorkflowExecutionStatus.STOPPED,
+                            error_message=event.get_stop_reason(),
                             conversation_id=self._conversation_id,
                             trace_manager=trace_manager,
                         )
-                        workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
+                        workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
                             session=session,
                             task_id=self._application_generate_entity.task_id,
-                            workflow_run=workflow_run,
+                            workflow_execution=workflow_execution,
                         )
                         # Save message
                         self._save_message(session=session, graph_runtime_state=graph_runtime_state)
@@ -650,22 +603,18 @@ class AdvancedChatAppGenerateTaskPipeline:
                 yield self._message_end_to_stream_response()
                 break
             elif isinstance(event, QueueRetrieverResourcesEvent):
-                self._message_cycle_manager._handle_retriever_resources(event)
+                self._message_cycle_manager.handle_retriever_resources(event)
 
                 with Session(db.engine, expire_on_commit=False) as session:
                     message = self._get_message(session=session)
-                    message.message_metadata = (
-                        json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
-                    )
+                    message.message_metadata = self._task_state.metadata.model_dump_json()
                     session.commit()
             elif isinstance(event, QueueAnnotationReplyEvent):
-                self._message_cycle_manager._handle_annotation_reply(event)
+                self._message_cycle_manager.handle_annotation_reply(event)
 
                 with Session(db.engine, expire_on_commit=False) as session:
                     message = self._get_message(session=session)
-                    message.message_metadata = (
-                        json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
-                    )
+                    message.message_metadata = self._task_state.metadata.model_dump_json()
                     session.commit()
             elif isinstance(event, QueueTextChunkEvent):
                 delta_text = event.text
@@ -682,12 +631,12 @@ class AdvancedChatAppGenerateTaskPipeline:
                     tts_publisher.publish(queue_message)
 
                 self._task_state.answer += delta_text
-                yield self._message_cycle_manager._message_to_stream_response(
+                yield self._message_cycle_manager.message_to_stream_response(
                     answer=delta_text, message_id=self._message_id, from_variable_selector=event.from_variable_selector
                 )
             elif isinstance(event, QueueMessageReplaceEvent):
                 # published by moderation
-                yield self._message_cycle_manager._message_replace_to_stream_response(
+                yield self._message_cycle_manager.message_replace_to_stream_response(
                     answer=event.text, reason=event.reason
                 )
             elif isinstance(event, QueueAdvancedChatMessageEndEvent):
@@ -699,7 +648,7 @@ class AdvancedChatAppGenerateTaskPipeline:
                 )
                 if output_moderation_answer:
                     self._task_state.answer = output_moderation_answer
-                    yield self._message_cycle_manager._message_replace_to_stream_response(
+                    yield self._message_cycle_manager.message_replace_to_stream_response(
                         answer=output_moderation_answer,
                         reason=QueueMessageReplaceEvent.MessageReplaceReason.OUTPUT_MODERATION,
                     )
@@ -711,7 +660,7 @@ class AdvancedChatAppGenerateTaskPipeline:
 
                 yield self._message_end_to_stream_response()
             elif isinstance(event, QueueAgentLogEvent):
-                yield self._workflow_cycle_manager._handle_agent_log(
+                yield self._workflow_response_converter.handle_agent_log(
                     task_id=self._application_generate_entity.task_id, event=event
                 )
             else:
@@ -728,9 +677,7 @@ class AdvancedChatAppGenerateTaskPipeline:
         message = self._get_message(session=session)
         message.answer = self._task_state.answer
         message.provider_response_latency = time.perf_counter() - self._base_task_pipeline._start_at
-        message.message_metadata = (
-            json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
-        )
+        message.message_metadata = self._task_state.metadata.model_dump_json()
         message_files = [
             MessageFile(
                 message_id=message.id,
@@ -758,9 +705,9 @@ class AdvancedChatAppGenerateTaskPipeline:
             message.answer_price_unit = usage.completion_price_unit
             message.total_price = usage.total_price
             message.currency = usage.currency
-            self._task_state.metadata["usage"] = jsonable_encoder(usage)
+            self._task_state.metadata.usage = usage
         else:
-            self._task_state.metadata["usage"] = jsonable_encoder(LLMUsage.empty_usage())
+            self._task_state.metadata.usage = LLMUsage.empty_usage()
         message_was_created.send(
             message,
             application_generate_entity=self._application_generate_entity,
@@ -771,18 +718,16 @@ class AdvancedChatAppGenerateTaskPipeline:
         Message end to stream response.
         :return:
         """
-        extras = {}
-        if self._task_state.metadata:
-            extras["metadata"] = self._task_state.metadata.copy()
+        extras = self._task_state.metadata.model_dump()
 
-            if "annotation_reply" in extras["metadata"]:
-                del extras["metadata"]["annotation_reply"]
+        if self._task_state.metadata.annotation_reply:
+            del extras["annotation_reply"]
 
         return MessageEndStreamResponse(
             task_id=self._application_generate_entity.task_id,
             id=self._message_id,
             files=self._recorded_files,
-            metadata=extras.get("metadata", {}),
+            metadata=extras,
         )
 
     def _handle_output_moderation_chunk(self, text: str) -> bool:

api/core/app/apps/agent_chat/app_generator.py

@@ -5,7 +5,7 @@ import uuid
 from collections.abc import Generator, Mapping
 from typing import Any, Literal, Union, overload
 
-from flask import Flask, current_app
+from flask import Flask, copy_current_request_context, current_app, has_request_context
 from pydantic import ValidationError
 
 from configs import dify_config
@@ -179,18 +179,23 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
             message_id=message.id,
         )
 
-        # new thread
-        worker_thread = threading.Thread(
-            target=self._generate_worker,
-            kwargs={
-                "flask_app": current_app._get_current_object(),  # type: ignore
-                "context": contextvars.copy_context(),
-                "application_generate_entity": application_generate_entity,
-                "queue_manager": queue_manager,
-                "conversation_id": conversation.id,
-                "message_id": message.id,
-            },
-        )
+        # new thread with request context and contextvars
+        context = contextvars.copy_context()
+
+        @copy_current_request_context
+        def worker_with_context():
+            # Run the worker within the copied context
+            return context.run(
+                self._generate_worker,
+                flask_app=current_app._get_current_object(),  # type: ignore
+                context=context,
+                application_generate_entity=application_generate_entity,
+                queue_manager=queue_manager,
+                conversation_id=conversation.id,
+                message_id=message.id,
+            )
+
+        worker_thread = threading.Thread(target=worker_with_context)
 
         worker_thread.start()
 
@@ -227,8 +232,21 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
         for var, val in context.items():
             var.set(val)
 
+        # FIXME(-LAN-): Save current user before entering new app context
+        from flask import g
+
+        saved_user = None
+        if has_request_context() and hasattr(g, "_login_user"):
+            saved_user = g._login_user
+
         with flask_app.app_context():
             try:
+                # Restore user in new app context
+                if saved_user is not None:
+                    from flask import g
+
+                    g._login_user = saved_user
+
                 # get conversation and message
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)

api/core/app/apps/chat/app_generator.py

@@ -4,7 +4,7 @@ import uuid
 from collections.abc import Generator, Mapping
 from typing import Any, Literal, Union, overload
 
-from flask import Flask, current_app
+from flask import Flask, copy_current_request_context, current_app
 from pydantic import ValidationError
 
 from configs import dify_config
@@ -170,17 +170,18 @@ class ChatAppGenerator(MessageBasedAppGenerator):
             message_id=message.id,
         )
 
-        # new thread
-        worker_thread = threading.Thread(
-            target=self._generate_worker,
-            kwargs={
-                "flask_app": current_app._get_current_object(),  # type: ignore
-                "application_generate_entity": application_generate_entity,
-                "queue_manager": queue_manager,
-                "conversation_id": conversation.id,
-                "message_id": message.id,
-            },
-        )
+        # new thread with request context
+        @copy_current_request_context
+        def worker_with_context():
+            return self._generate_worker(
+                flask_app=current_app._get_current_object(),  # type: ignore
+                application_generate_entity=application_generate_entity,
+                queue_manager=queue_manager,
+                conversation_id=conversation.id,
+                message_id=message.id,
+            )
+
+        worker_thread = threading.Thread(target=worker_with_context)
 
         worker_thread.start()
 

api/core/app/apps/common/workflow_response_converter.py

@@ -0,0 +1,561 @@
+import time
+from collections.abc import Mapping, Sequence
+from datetime import UTC, datetime
+from typing import Any, Optional, Union, cast
+
+from sqlalchemy import select
+from sqlalchemy.orm import Session
+
+from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity
+from core.app.entities.queue_entities import (
+    QueueAgentLogEvent,
+    QueueIterationCompletedEvent,
+    QueueIterationNextEvent,
+    QueueIterationStartEvent,
+    QueueLoopCompletedEvent,
+    QueueLoopNextEvent,
+    QueueLoopStartEvent,
+    QueueNodeExceptionEvent,
+    QueueNodeFailedEvent,
+    QueueNodeInIterationFailedEvent,
+    QueueNodeInLoopFailedEvent,
+    QueueNodeRetryEvent,
+    QueueNodeStartedEvent,
+    QueueNodeSucceededEvent,
+    QueueParallelBranchRunFailedEvent,
+    QueueParallelBranchRunStartedEvent,
+    QueueParallelBranchRunSucceededEvent,
+)
+from core.app.entities.task_entities import (
+    AgentLogStreamResponse,
+    IterationNodeCompletedStreamResponse,
+    IterationNodeNextStreamResponse,
+    IterationNodeStartStreamResponse,
+    LoopNodeCompletedStreamResponse,
+    LoopNodeNextStreamResponse,
+    LoopNodeStartStreamResponse,
+    NodeFinishStreamResponse,
+    NodeRetryStreamResponse,
+    NodeStartStreamResponse,
+    ParallelBranchFinishedStreamResponse,
+    ParallelBranchStartStreamResponse,
+    WorkflowFinishStreamResponse,
+    WorkflowStartStreamResponse,
+)
+from core.file import FILE_MODEL_IDENTITY, File
+from core.tools.tool_manager import ToolManager
+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 models import (
+    Account,
+    CreatorUserRole,
+    EndUser,
+    WorkflowRun,
+)
+
+
+class WorkflowResponseConverter:
+    def __init__(
+        self,
+        *,
+        application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity],
+    ) -> None:
+        self._application_generate_entity = application_generate_entity
+
+    def workflow_start_to_stream_response(
+        self,
+        *,
+        task_id: str,
+        workflow_execution: WorkflowExecution,
+    ) -> WorkflowStartStreamResponse:
+        return WorkflowStartStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution.id_,
+            data=WorkflowStartStreamResponse.Data(
+                id=workflow_execution.id_,
+                workflow_id=workflow_execution.workflow_id,
+                inputs=workflow_execution.inputs,
+                created_at=int(workflow_execution.started_at.timestamp()),
+            ),
+        )
+
+    def workflow_finish_to_stream_response(
+        self,
+        *,
+        session: Session,
+        task_id: str,
+        workflow_execution: WorkflowExecution,
+    ) -> WorkflowFinishStreamResponse:
+        created_by = None
+        workflow_run = session.scalar(select(WorkflowRun).where(WorkflowRun.id == workflow_execution.id_))
+        assert workflow_run is not None
+        if workflow_run.created_by_role == CreatorUserRole.ACCOUNT:
+            stmt = select(Account).where(Account.id == workflow_run.created_by)
+            account = session.scalar(stmt)
+            if account:
+                created_by = {
+                    "id": account.id,
+                    "name": account.name,
+                    "email": account.email,
+                }
+        elif workflow_run.created_by_role == CreatorUserRole.END_USER:
+            stmt = select(EndUser).where(EndUser.id == workflow_run.created_by)
+            end_user = session.scalar(stmt)
+            if end_user:
+                created_by = {
+                    "id": end_user.id,
+                    "user": end_user.session_id,
+                }
+        else:
+            raise NotImplementedError(f"unknown created_by_role: {workflow_run.created_by_role}")
+
+        # Handle the case where finished_at is None by using current time as default
+        finished_at_timestamp = (
+            int(workflow_execution.finished_at.timestamp())
+            if workflow_execution.finished_at
+            else int(datetime.now(UTC).timestamp())
+        )
+
+        return WorkflowFinishStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution.id_,
+            data=WorkflowFinishStreamResponse.Data(
+                id=workflow_execution.id_,
+                workflow_id=workflow_execution.workflow_id,
+                status=workflow_execution.status,
+                outputs=workflow_execution.outputs,
+                error=workflow_execution.error_message,
+                elapsed_time=workflow_execution.elapsed_time,
+                total_tokens=workflow_execution.total_tokens,
+                total_steps=workflow_execution.total_steps,
+                created_by=created_by,
+                created_at=int(workflow_execution.started_at.timestamp()),
+                finished_at=finished_at_timestamp,
+                files=self.fetch_files_from_node_outputs(workflow_execution.outputs),
+                exceptions_count=workflow_execution.exceptions_count,
+            ),
+        )
+
+    def workflow_node_start_to_stream_response(
+        self,
+        *,
+        event: QueueNodeStartedEvent,
+        task_id: str,
+        workflow_node_execution: WorkflowNodeExecution,
+    ) -> Optional[NodeStartStreamResponse]:
+        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
+            return None
+        if not workflow_node_execution.workflow_execution_id:
+            return None
+
+        response = NodeStartStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_node_execution.workflow_execution_id,
+            data=NodeStartStreamResponse.Data(
+                id=workflow_node_execution.id,
+                node_id=workflow_node_execution.node_id,
+                node_type=workflow_node_execution.node_type,
+                title=workflow_node_execution.title,
+                index=workflow_node_execution.index,
+                predecessor_node_id=workflow_node_execution.predecessor_node_id,
+                inputs=workflow_node_execution.inputs,
+                created_at=int(workflow_node_execution.created_at.timestamp()),
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+                parent_parallel_id=event.parent_parallel_id,
+                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
+                iteration_id=event.in_iteration_id,
+                loop_id=event.in_loop_id,
+                parallel_run_id=event.parallel_mode_run_id,
+                agent_strategy=event.agent_strategy,
+            ),
+        )
+
+        # extras logic
+        if event.node_type == NodeType.TOOL:
+            node_data = cast(ToolNodeData, event.node_data)
+            response.data.extras["icon"] = ToolManager.get_tool_icon(
+                tenant_id=self._application_generate_entity.app_config.tenant_id,
+                provider_type=node_data.provider_type,
+                provider_id=node_data.provider_id,
+            )
+
+        return response
+
+    def workflow_node_finish_to_stream_response(
+        self,
+        *,
+        event: QueueNodeSucceededEvent
+        | QueueNodeFailedEvent
+        | QueueNodeInIterationFailedEvent
+        | QueueNodeInLoopFailedEvent
+        | QueueNodeExceptionEvent,
+        task_id: str,
+        workflow_node_execution: WorkflowNodeExecution,
+    ) -> Optional[NodeFinishStreamResponse]:
+        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
+            return None
+        if not workflow_node_execution.workflow_execution_id:
+            return None
+        if not workflow_node_execution.finished_at:
+            return None
+
+        return NodeFinishStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_node_execution.workflow_execution_id,
+            data=NodeFinishStreamResponse.Data(
+                id=workflow_node_execution.id,
+                node_id=workflow_node_execution.node_id,
+                node_type=workflow_node_execution.node_type,
+                index=workflow_node_execution.index,
+                title=workflow_node_execution.title,
+                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,
+                status=workflow_node_execution.status,
+                error=workflow_node_execution.error,
+                elapsed_time=workflow_node_execution.elapsed_time,
+                execution_metadata=workflow_node_execution.metadata,
+                created_at=int(workflow_node_execution.created_at.timestamp()),
+                finished_at=int(workflow_node_execution.finished_at.timestamp()),
+                files=self.fetch_files_from_node_outputs(workflow_node_execution.outputs or {}),
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+                parent_parallel_id=event.parent_parallel_id,
+                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
+                iteration_id=event.in_iteration_id,
+                loop_id=event.in_loop_id,
+            ),
+        )
+
+    def workflow_node_retry_to_stream_response(
+        self,
+        *,
+        event: QueueNodeRetryEvent,
+        task_id: str,
+        workflow_node_execution: WorkflowNodeExecution,
+    ) -> Optional[Union[NodeRetryStreamResponse, NodeFinishStreamResponse]]:
+        if workflow_node_execution.node_type in {NodeType.ITERATION, NodeType.LOOP}:
+            return None
+        if not workflow_node_execution.workflow_execution_id:
+            return None
+        if not workflow_node_execution.finished_at:
+            return None
+
+        return NodeRetryStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_node_execution.workflow_execution_id,
+            data=NodeRetryStreamResponse.Data(
+                id=workflow_node_execution.id,
+                node_id=workflow_node_execution.node_id,
+                node_type=workflow_node_execution.node_type,
+                index=workflow_node_execution.index,
+                title=workflow_node_execution.title,
+                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,
+                status=workflow_node_execution.status,
+                error=workflow_node_execution.error,
+                elapsed_time=workflow_node_execution.elapsed_time,
+                execution_metadata=workflow_node_execution.metadata,
+                created_at=int(workflow_node_execution.created_at.timestamp()),
+                finished_at=int(workflow_node_execution.finished_at.timestamp()),
+                files=self.fetch_files_from_node_outputs(workflow_node_execution.outputs or {}),
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+                parent_parallel_id=event.parent_parallel_id,
+                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
+                iteration_id=event.in_iteration_id,
+                loop_id=event.in_loop_id,
+                retry_index=event.retry_index,
+            ),
+        )
+
+    def workflow_parallel_branch_start_to_stream_response(
+        self,
+        *,
+        task_id: str,
+        workflow_execution_id: str,
+        event: QueueParallelBranchRunStartedEvent,
+    ) -> ParallelBranchStartStreamResponse:
+        return ParallelBranchStartStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution_id,
+            data=ParallelBranchStartStreamResponse.Data(
+                parallel_id=event.parallel_id,
+                parallel_branch_id=event.parallel_start_node_id,
+                parent_parallel_id=event.parent_parallel_id,
+                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
+                iteration_id=event.in_iteration_id,
+                loop_id=event.in_loop_id,
+                created_at=int(time.time()),
+            ),
+        )
+
+    def workflow_parallel_branch_finished_to_stream_response(
+        self,
+        *,
+        task_id: str,
+        workflow_execution_id: str,
+        event: QueueParallelBranchRunSucceededEvent | QueueParallelBranchRunFailedEvent,
+    ) -> ParallelBranchFinishedStreamResponse:
+        return ParallelBranchFinishedStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution_id,
+            data=ParallelBranchFinishedStreamResponse.Data(
+                parallel_id=event.parallel_id,
+                parallel_branch_id=event.parallel_start_node_id,
+                parent_parallel_id=event.parent_parallel_id,
+                parent_parallel_start_node_id=event.parent_parallel_start_node_id,
+                iteration_id=event.in_iteration_id,
+                loop_id=event.in_loop_id,
+                status="succeeded" if isinstance(event, QueueParallelBranchRunSucceededEvent) else "failed",
+                error=event.error if isinstance(event, QueueParallelBranchRunFailedEvent) else None,
+                created_at=int(time.time()),
+            ),
+        )
+
+    def workflow_iteration_start_to_stream_response(
+        self,
+        *,
+        task_id: str,
+        workflow_execution_id: str,
+        event: QueueIterationStartEvent,
+    ) -> IterationNodeStartStreamResponse:
+        return IterationNodeStartStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution_id,
+            data=IterationNodeStartStreamResponse.Data(
+                id=event.node_id,
+                node_id=event.node_id,
+                node_type=event.node_type.value,
+                title=event.node_data.title,
+                created_at=int(time.time()),
+                extras={},
+                inputs=event.inputs or {},
+                metadata=event.metadata or {},
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+            ),
+        )
+
+    def workflow_iteration_next_to_stream_response(
+        self,
+        *,
+        task_id: str,
+        workflow_execution_id: str,
+        event: QueueIterationNextEvent,
+    ) -> IterationNodeNextStreamResponse:
+        return IterationNodeNextStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution_id,
+            data=IterationNodeNextStreamResponse.Data(
+                id=event.node_id,
+                node_id=event.node_id,
+                node_type=event.node_type.value,
+                title=event.node_data.title,
+                index=event.index,
+                pre_iteration_output=event.output,
+                created_at=int(time.time()),
+                extras={},
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+                parallel_mode_run_id=event.parallel_mode_run_id,
+                duration=event.duration,
+            ),
+        )
+
+    def workflow_iteration_completed_to_stream_response(
+        self,
+        *,
+        task_id: str,
+        workflow_execution_id: str,
+        event: QueueIterationCompletedEvent,
+    ) -> IterationNodeCompletedStreamResponse:
+        return IterationNodeCompletedStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution_id,
+            data=IterationNodeCompletedStreamResponse.Data(
+                id=event.node_id,
+                node_id=event.node_id,
+                node_type=event.node_type.value,
+                title=event.node_data.title,
+                outputs=event.outputs,
+                created_at=int(time.time()),
+                extras={},
+                inputs=event.inputs or {},
+                status=WorkflowNodeExecutionStatus.SUCCEEDED
+                if event.error is None
+                else WorkflowNodeExecutionStatus.FAILED,
+                error=None,
+                elapsed_time=(datetime.now(UTC).replace(tzinfo=None) - event.start_at).total_seconds(),
+                total_tokens=event.metadata.get("total_tokens", 0) if event.metadata else 0,
+                execution_metadata=event.metadata,
+                finished_at=int(time.time()),
+                steps=event.steps,
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+            ),
+        )
+
+    def workflow_loop_start_to_stream_response(
+        self, *, task_id: str, workflow_execution_id: str, event: QueueLoopStartEvent
+    ) -> LoopNodeStartStreamResponse:
+        return LoopNodeStartStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution_id,
+            data=LoopNodeStartStreamResponse.Data(
+                id=event.node_id,
+                node_id=event.node_id,
+                node_type=event.node_type.value,
+                title=event.node_data.title,
+                created_at=int(time.time()),
+                extras={},
+                inputs=event.inputs or {},
+                metadata=event.metadata or {},
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+            ),
+        )
+
+    def workflow_loop_next_to_stream_response(
+        self,
+        *,
+        task_id: str,
+        workflow_execution_id: str,
+        event: QueueLoopNextEvent,
+    ) -> LoopNodeNextStreamResponse:
+        return LoopNodeNextStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution_id,
+            data=LoopNodeNextStreamResponse.Data(
+                id=event.node_id,
+                node_id=event.node_id,
+                node_type=event.node_type.value,
+                title=event.node_data.title,
+                index=event.index,
+                pre_loop_output=event.output,
+                created_at=int(time.time()),
+                extras={},
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+                parallel_mode_run_id=event.parallel_mode_run_id,
+                duration=event.duration,
+            ),
+        )
+
+    def workflow_loop_completed_to_stream_response(
+        self,
+        *,
+        task_id: str,
+        workflow_execution_id: str,
+        event: QueueLoopCompletedEvent,
+    ) -> LoopNodeCompletedStreamResponse:
+        return LoopNodeCompletedStreamResponse(
+            task_id=task_id,
+            workflow_run_id=workflow_execution_id,
+            data=LoopNodeCompletedStreamResponse.Data(
+                id=event.node_id,
+                node_id=event.node_id,
+                node_type=event.node_type.value,
+                title=event.node_data.title,
+                outputs=event.outputs,
+                created_at=int(time.time()),
+                extras={},
+                inputs=event.inputs or {},
+                status=WorkflowNodeExecutionStatus.SUCCEEDED
+                if event.error is None
+                else WorkflowNodeExecutionStatus.FAILED,
+                error=None,
+                elapsed_time=(datetime.now(UTC).replace(tzinfo=None) - event.start_at).total_seconds(),
+                total_tokens=event.metadata.get("total_tokens", 0) if event.metadata else 0,
+                execution_metadata=event.metadata,
+                finished_at=int(time.time()),
+                steps=event.steps,
+                parallel_id=event.parallel_id,
+                parallel_start_node_id=event.parallel_start_node_id,
+            ),
+        )
+
+    def fetch_files_from_node_outputs(self, outputs_dict: Mapping[str, Any] | None) -> Sequence[Mapping[str, Any]]:
+        """
+        Fetch files from node outputs
+        :param outputs_dict: node outputs dict
+        :return:
+        """
+        if not outputs_dict:
+            return []
+
+        files = [self._fetch_files_from_variable_value(output_value) for output_value in outputs_dict.values()]
+        # Remove None
+        files = [file for file in files if file]
+        # Flatten list
+        # Flatten the list of sequences into a single list of mappings
+        flattened_files = [file for sublist in files if sublist for file in sublist]
+
+        # 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]]:
+        """
+        Fetch files from variable value
+        :param value: variable value
+        :return:
+        """
+        if not value:
+            return []
+
+        files = []
+        if isinstance(value, list):
+            for item in value:
+                file = self._get_file_var_from_value(item)
+                if file:
+                    files.append(file)
+        elif isinstance(value, dict):
+            file = self._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:
+        """
+        Get file var from value
+        :param value: variable value
+        :return:
+        """
+        if not value:
+            return None
+
+        if isinstance(value, dict) and value.get("dify_model_identity") == FILE_MODEL_IDENTITY:
+            return value
+        elif isinstance(value, File):
+            return value.to_dict()
+
+        return None
+
+    def handle_agent_log(self, task_id: str, event: QueueAgentLogEvent) -> AgentLogStreamResponse:
+        """
+        Handle agent log
+        :param task_id: task id
+        :param event: agent log event
+        :return:
+        """
+        return AgentLogStreamResponse(
+            task_id=task_id,
+            data=AgentLogStreamResponse.Data(
+                node_execution_id=event.node_execution_id,
+                id=event.id,
+                parent_id=event.parent_id,
+                label=event.label,
+                error=event.error,
+                status=event.status,
+                data=event.data,
+                metadata=event.metadata,
+                node_id=event.node_id,
+            ),
+        )

api/core/app/apps/completion/app_generator.py

@@ -4,7 +4,7 @@ import uuid
 from collections.abc import Generator, Mapping
 from typing import Any, Literal, Union, overload
 
-from flask import Flask, current_app
+from flask import Flask, copy_current_request_context, current_app
 from pydantic import ValidationError
 
 from configs import dify_config
@@ -151,16 +151,17 @@ class CompletionAppGenerator(MessageBasedAppGenerator):
             message_id=message.id,
         )
 
-        # new thread
-        worker_thread = threading.Thread(
-            target=self._generate_worker,
-            kwargs={
-                "flask_app": current_app._get_current_object(),  # type: ignore
-                "application_generate_entity": application_generate_entity,
-                "queue_manager": queue_manager,
-                "message_id": message.id,
-            },
-        )
+        # new thread with request context
+        @copy_current_request_context
+        def worker_with_context():
+            return self._generate_worker(
+                flask_app=current_app._get_current_object(),  # type: ignore
+                application_generate_entity=application_generate_entity,
+                queue_manager=queue_manager,
+                message_id=message.id,
+            )
+
+        worker_thread = threading.Thread(target=worker_with_context)
 
         worker_thread.start()
 
@@ -313,16 +314,17 @@ class CompletionAppGenerator(MessageBasedAppGenerator):
             message_id=message.id,
         )
 
-        # new thread
-        worker_thread = threading.Thread(
-            target=self._generate_worker,
-            kwargs={
-                "flask_app": current_app._get_current_object(),  # type: ignore
-                "application_generate_entity": application_generate_entity,
-                "queue_manager": queue_manager,
-                "message_id": message.id,
-            },
-        )
+        # new thread with request context
+        @copy_current_request_context
+        def worker_with_context():
+            return self._generate_worker(
+                flask_app=current_app._get_current_object(),  # type: ignore
+                application_generate_entity=application_generate_entity,
+                queue_manager=queue_manager,
+                message_id=message.id,
+            )
+
+        worker_thread = threading.Thread(target=worker_with_context)
 
         worker_thread.start()
 

api/core/app/apps/workflow/app_generator.py

@@ -5,7 +5,7 @@ import uuid
 from collections.abc import Generator, Mapping, Sequence
 from typing import Any, Literal, Optional, Union, overload
 
-from flask import Flask, current_app
+from flask import Flask, copy_current_request_context, current_app, has_request_context
 from pydantic import ValidationError
 from sqlalchemy.orm import sessionmaker
 
@@ -18,16 +18,19 @@ from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager
 from core.app.apps.workflow.app_queue_manager import WorkflowAppQueueManager
 from core.app.apps.workflow.app_runner import WorkflowAppRunner
 from core.app.apps.workflow.generate_response_converter import WorkflowAppGenerateResponseConverter
+from core.app.apps.workflow.generate_task_pipeline import WorkflowAppGenerateTaskPipeline
 from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerateEntity
 from core.app.entities.task_entities import WorkflowAppBlockingResponse, WorkflowAppStreamResponse
 from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.ops.ops_trace_manager import TraceQueueManager
 from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
-from core.workflow.repository.workflow_node_execution_repository import WorkflowNodeExecutionRepository
-from core.workflow.workflow_app_generate_task_pipeline import WorkflowAppGenerateTaskPipeline
+from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository
+from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
+from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from extensions.ext_database import db
 from factories import file_factory
 from models import Account, App, EndUser, Workflow, WorkflowNodeExecutionTriggeredFrom
+from models.enums import WorkflowRunTriggeredFrom
 
 logger = logging.getLogger(__name__)
 
@@ -129,16 +132,28 @@ class WorkflowAppGenerator(BaseAppGenerator):
             invoke_from=invoke_from,
             call_depth=call_depth,
             trace_manager=trace_manager,
-            workflow_run_id=workflow_run_id,
+            workflow_execution_id=workflow_run_id,
         )
 
-        contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
         contexts.plugin_tool_providers.set({})
         contexts.plugin_tool_providers_lock.set(threading.Lock())
 
-        # Create workflow node execution repository
+        # Create repositories
+        #
+        # Create session factory
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
-
+        # Create workflow execution(aka workflow run) repository
+        if invoke_from == InvokeFrom.DEBUGGER:
+            workflow_triggered_from = WorkflowRunTriggeredFrom.DEBUGGING
+        else:
+            workflow_triggered_from = WorkflowRunTriggeredFrom.APP_RUN
+        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+            session_factory=session_factory,
+            user=user,
+            app_id=application_generate_entity.app_config.app_id,
+            triggered_from=workflow_triggered_from,
+        )
+        # Create workflow node execution repository
         workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
             session_factory=session_factory,
             user=user,
@@ -152,6 +167,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             user=user,
             application_generate_entity=application_generate_entity,
             invoke_from=invoke_from,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             streaming=streaming,
             workflow_thread_pool_id=workflow_thread_pool_id,
@@ -165,6 +181,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
         user: Union[Account, EndUser],
         application_generate_entity: WorkflowAppGenerateEntity,
         invoke_from: InvokeFrom,
+        workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         streaming: bool = True,
         workflow_thread_pool_id: Optional[str] = None,
@@ -189,17 +206,22 @@ class WorkflowAppGenerator(BaseAppGenerator):
             app_mode=app_model.mode,
         )
 
-        # new thread
-        worker_thread = threading.Thread(
-            target=self._generate_worker,
-            kwargs={
-                "flask_app": current_app._get_current_object(),  # type: ignore
-                "application_generate_entity": application_generate_entity,
-                "queue_manager": queue_manager,
-                "context": contextvars.copy_context(),
-                "workflow_thread_pool_id": workflow_thread_pool_id,
-            },
-        )
+        # new thread with request context and contextvars
+        context = contextvars.copy_context()
+
+        @copy_current_request_context
+        def worker_with_context():
+            # Run the worker within the copied context
+            return context.run(
+                self._generate_worker,
+                flask_app=current_app._get_current_object(),  # type: ignore
+                application_generate_entity=application_generate_entity,
+                queue_manager=queue_manager,
+                context=context,
+                workflow_thread_pool_id=workflow_thread_pool_id,
+            )
+
+        worker_thread = threading.Thread(target=worker_with_context)
 
         worker_thread.start()
 
@@ -209,6 +231,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             workflow=workflow,
             queue_manager=queue_manager,
             user=user,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             stream=streaming,
         )
@@ -256,12 +279,22 @@ class WorkflowAppGenerator(BaseAppGenerator):
             single_iteration_run=WorkflowAppGenerateEntity.SingleIterationRunEntity(
                 node_id=node_id, inputs=args["inputs"]
             ),
-            workflow_run_id=str(uuid.uuid4()),
+            workflow_execution_id=str(uuid.uuid4()),
         )
-        contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
         contexts.plugin_tool_providers.set({})
         contexts.plugin_tool_providers_lock.set(threading.Lock())
 
+        # Create repositories
+        #
+        # Create session factory
+        session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
+        # Create workflow execution(aka workflow run) repository
+        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+            session_factory=session_factory,
+            user=user,
+            app_id=application_generate_entity.app_config.app_id,
+            triggered_from=WorkflowRunTriggeredFrom.DEBUGGING,
+        )
         # Create workflow node execution repository
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
 
@@ -278,6 +311,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             user=user,
             invoke_from=InvokeFrom.DEBUGGER,
             application_generate_entity=application_generate_entity,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             streaming=streaming,
         )
@@ -321,12 +355,22 @@ class WorkflowAppGenerator(BaseAppGenerator):
             invoke_from=InvokeFrom.DEBUGGER,
             extras={"auto_generate_conversation_name": False},
             single_loop_run=WorkflowAppGenerateEntity.SingleLoopRunEntity(node_id=node_id, inputs=args["inputs"]),
-            workflow_run_id=str(uuid.uuid4()),
+            workflow_execution_id=str(uuid.uuid4()),
         )
-        contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
         contexts.plugin_tool_providers.set({})
         contexts.plugin_tool_providers_lock.set(threading.Lock())
 
+        # Create repositories
+        #
+        # Create session factory
+        session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
+        # Create workflow execution(aka workflow run) repository
+        workflow_execution_repository = SQLAlchemyWorkflowExecutionRepository(
+            session_factory=session_factory,
+            user=user,
+            app_id=application_generate_entity.app_config.app_id,
+            triggered_from=WorkflowRunTriggeredFrom.DEBUGGING,
+        )
         # Create workflow node execution repository
         session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
 
@@ -343,6 +387,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             user=user,
             invoke_from=InvokeFrom.DEBUGGER,
             application_generate_entity=application_generate_entity,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             streaming=streaming,
         )
@@ -365,8 +410,22 @@ class WorkflowAppGenerator(BaseAppGenerator):
         """
         for var, val in context.items():
             var.set(val)
+
+        # FIXME(-LAN-): Save current user before entering new app context
+        from flask import g
+
+        saved_user = None
+        if has_request_context() and hasattr(g, "_login_user"):
+            saved_user = g._login_user
+
         with flask_app.app_context():
             try:
+                # Restore user in new app context
+                if saved_user is not None:
+                    from flask import g
+
+                    g._login_user = saved_user
+
                 # workflow app
                 runner = WorkflowAppRunner(
                     application_generate_entity=application_generate_entity,
@@ -400,6 +459,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
         workflow: Workflow,
         queue_manager: AppQueueManager,
         user: Union[Account, EndUser],
+        workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         stream: bool = False,
     ) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
@@ -419,8 +479,9 @@ class WorkflowAppGenerator(BaseAppGenerator):
             workflow=workflow,
             queue_manager=queue_manager,
             user=user,
-            stream=stream,
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
+            stream=stream,
         )
 
         try:

api/core/app/apps/workflow/app_runner.py

@@ -95,7 +95,7 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
                 SystemVariableKey.USER_ID: user_id,
                 SystemVariableKey.APP_ID: app_config.app_id,
                 SystemVariableKey.WORKFLOW_ID: app_config.workflow_id,
-                SystemVariableKey.WORKFLOW_RUN_ID: self.application_generate_entity.workflow_run_id,
+                SystemVariableKey.WORKFLOW_EXECUTION_ID: self.application_generate_entity.workflow_execution_id,
             }
 
             variable_pool = VariablePool(

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -3,10 +3,12 @@ import time
 from collections.abc import Generator
 from typing import Optional, Union
 
+from sqlalchemy import select
 from sqlalchemy.orm import Session
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
 from core.app.apps.base_app_queue_manager import AppQueueManager
+from core.app.apps.common.workflow_response_converter import WorkflowResponseConverter
 from core.app.entities.app_invoke_entities import (
     InvokeFrom,
     WorkflowAppGenerateEntity,
@@ -48,14 +50,15 @@ from core.app.entities.task_entities import (
     WorkflowAppStreamResponse,
     WorkflowFinishStreamResponse,
     WorkflowStartStreamResponse,
-    WorkflowTaskState,
 )
 from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline
 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.repository.workflow_node_execution_repository import WorkflowNodeExecutionRepository
-from core.workflow.workflow_cycle_manager import WorkflowCycleManager
+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
 from extensions.ext_database import db
 from models.account import Account
 from models.enums import CreatorUserRole
@@ -65,7 +68,6 @@ from models.workflow import (
     WorkflowAppLog,
     WorkflowAppLogCreatedFrom,
     WorkflowRun,
-    WorkflowRunStatus,
 )
 
 logger = logging.getLogger(__name__)
@@ -83,6 +85,7 @@ class WorkflowAppGenerateTaskPipeline:
         queue_manager: AppQueueManager,
         user: Union[Account, EndUser],
         stream: bool,
+        workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
     ) -> None:
         self._base_task_pipeline = BasedGenerateTaskPipeline(
@@ -109,15 +112,24 @@ class WorkflowAppGenerateTaskPipeline:
                 SystemVariableKey.USER_ID: user_session_id,
                 SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
                 SystemVariableKey.WORKFLOW_ID: workflow.id,
-                SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
+                SystemVariableKey.WORKFLOW_EXECUTION_ID: application_generate_entity.workflow_execution_id,
             },
+            workflow_info=CycleManagerWorkflowInfo(
+                workflow_id=workflow.id,
+                workflow_type=WorkflowType(workflow.type),
+                version=workflow.version,
+                graph_data=workflow.graph_dict,
+            ),
+            workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
         )
 
+        self._workflow_response_converter = WorkflowResponseConverter(
+            application_generate_entity=application_generate_entity,
+        )
+
         self._application_generate_entity = application_generate_entity
-        self._workflow_id = workflow.id
         self._workflow_features_dict = workflow.features_dict
-        self._task_state = WorkflowTaskState()
         self._workflow_run_id = ""
 
     def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
@@ -256,19 +268,13 @@ class WorkflowAppGenerateTaskPipeline:
                 # override graph runtime state
                 graph_runtime_state = event.graph_runtime_state
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    # init workflow run
-                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_start(
-                        session=session,
-                        workflow_id=self._workflow_id,
-                        user_id=self._user_id,
-                        created_by_role=self._created_by_role,
-                    )
-                    self._workflow_run_id = workflow_run.id
-                    start_resp = self._workflow_cycle_manager._workflow_start_to_stream_response(
-                        session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
-                    )
-                    session.commit()
+                # init workflow run
+                workflow_execution = self._workflow_cycle_manager.handle_workflow_run_start()
+                self._workflow_run_id = workflow_execution.id_
+                start_resp = self._workflow_response_converter.workflow_start_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution=workflow_execution,
+                )
 
                 yield start_resp
             elif isinstance(
@@ -278,13 +284,11 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_retried(
-                        workflow_run=workflow_run, event=event
+                    workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_retried(
+                        workflow_execution_id=self._workflow_run_id,
+                        event=event,
                     )
-                    response = self._workflow_cycle_manager._workflow_node_retry_to_stream_response(
+                    response = self._workflow_response_converter.workflow_node_retry_to_stream_response(
                         event=event,
                         task_id=self._application_generate_entity.task_id,
                         workflow_node_execution=workflow_node_execution,
@@ -297,27 +301,22 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    workflow_node_execution = self._workflow_cycle_manager._handle_node_execution_start(
-                        workflow_run=workflow_run, event=event
-                    )
-                    node_start_response = self._workflow_cycle_manager._workflow_node_start_to_stream_response(
-                        event=event,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_node_execution=workflow_node_execution,
-                    )
-                    session.commit()
+                workflow_node_execution = self._workflow_cycle_manager.handle_node_execution_start(
+                    workflow_execution_id=self._workflow_run_id, event=event
+                )
+                node_start_response = self._workflow_response_converter.workflow_node_start_to_stream_response(
+                    event=event,
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_node_execution=workflow_node_execution,
+                )
 
                 if node_start_response:
                     yield node_start_response
             elif isinstance(event, QueueNodeSucceededEvent):
-                workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
+                workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_success(
                     event=event
                 )
-                node_success_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
+                node_success_response = self._workflow_response_converter.workflow_node_finish_to_stream_response(
                     event=event,
                     task_id=self._application_generate_entity.task_id,
                     workflow_node_execution=workflow_node_execution,
@@ -332,10 +331,10 @@ class WorkflowAppGenerateTaskPipeline:
                 | QueueNodeInLoopFailedEvent
                 | QueueNodeExceptionEvent,
             ):
-                workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
+                workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_failed(
                     event=event,
                 )
-                node_failed_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
+                node_failed_response = self._workflow_response_converter.workflow_node_finish_to_stream_response(
                     event=event,
                     task_id=self._application_generate_entity.task_id,
                     workflow_node_execution=workflow_node_execution,
@@ -348,18 +347,13 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    parallel_start_resp = (
-                        self._workflow_cycle_manager._workflow_parallel_branch_start_to_stream_response(
-                            session=session,
-                            task_id=self._application_generate_entity.task_id,
-                            workflow_run=workflow_run,
-                            event=event,
-                        )
+                parallel_start_resp = (
+                    self._workflow_response_converter.workflow_parallel_branch_start_to_stream_response(
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution_id=self._workflow_run_id,
+                        event=event,
                     )
+                )
 
                 yield parallel_start_resp
 
@@ -367,18 +361,13 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    parallel_finish_resp = (
-                        self._workflow_cycle_manager._workflow_parallel_branch_finished_to_stream_response(
-                            session=session,
-                            task_id=self._application_generate_entity.task_id,
-                            workflow_run=workflow_run,
-                            event=event,
-                        )
+                parallel_finish_resp = (
+                    self._workflow_response_converter.workflow_parallel_branch_finished_to_stream_response(
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution_id=self._workflow_run_id,
+                        event=event,
                     )
+                )
 
                 yield parallel_finish_resp
 
@@ -386,16 +375,11 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    iter_start_resp = self._workflow_cycle_manager._workflow_iteration_start_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                iter_start_resp = self._workflow_response_converter.workflow_iteration_start_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield iter_start_resp
 
@@ -403,16 +387,11 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    iter_next_resp = self._workflow_cycle_manager._workflow_iteration_next_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                iter_next_resp = self._workflow_response_converter.workflow_iteration_next_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield iter_next_resp
 
@@ -420,16 +399,11 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    iter_finish_resp = self._workflow_cycle_manager._workflow_iteration_completed_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                iter_finish_resp = self._workflow_response_converter.workflow_iteration_completed_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield iter_finish_resp
 
@@ -437,16 +411,11 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    loop_start_resp = self._workflow_cycle_manager._workflow_loop_start_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                loop_start_resp = self._workflow_response_converter.workflow_loop_start_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield loop_start_resp
 
@@ -454,16 +423,11 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    loop_next_resp = self._workflow_cycle_manager._workflow_loop_next_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                loop_next_resp = self._workflow_response_converter.workflow_loop_next_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield loop_next_resp
 
@@ -471,16 +435,11 @@ class WorkflowAppGenerateTaskPipeline:
                 if not self._workflow_run_id:
                     raise ValueError("workflow run not initialized.")
 
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._get_workflow_run(
-                        session=session, workflow_run_id=self._workflow_run_id
-                    )
-                    loop_finish_resp = self._workflow_cycle_manager._workflow_loop_completed_to_stream_response(
-                        session=session,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
-                        event=event,
-                    )
+                loop_finish_resp = self._workflow_response_converter.workflow_loop_completed_to_stream_response(
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_execution_id=self._workflow_run_id,
+                    event=event,
+                )
 
                 yield loop_finish_resp
 
@@ -491,10 +450,8 @@ class WorkflowAppGenerateTaskPipeline:
                     raise ValueError("graph runtime state not initialized.")
 
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_success(
-                        session=session,
+                    workflow_execution = self._workflow_cycle_manager.handle_workflow_run_success(
                         workflow_run_id=self._workflow_run_id,
-                        start_at=graph_runtime_state.start_at,
                         total_tokens=graph_runtime_state.total_tokens,
                         total_steps=graph_runtime_state.node_run_steps,
                         outputs=event.outputs,
@@ -503,12 +460,12 @@ class WorkflowAppGenerateTaskPipeline:
                     )
 
                     # save workflow app log
-                    self._save_workflow_app_log(session=session, workflow_run=workflow_run)
+                    self._save_workflow_app_log(session=session, workflow_execution=workflow_execution)
 
-                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
+                    workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
                         session=session,
                         task_id=self._application_generate_entity.task_id,
-                        workflow_run=workflow_run,
+                        workflow_execution=workflow_execution,
                     )
                     session.commit()
 
@@ -520,10 +477,8 @@ class WorkflowAppGenerateTaskPipeline:
                     raise ValueError("graph runtime state not initialized.")
 
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_partial_success(
-                        session=session,
+                    workflow_execution = self._workflow_cycle_manager.handle_workflow_run_partial_success(
                         workflow_run_id=self._workflow_run_id,
-                        start_at=graph_runtime_state.start_at,
                         total_tokens=graph_runtime_state.total_tokens,
                         total_steps=graph_runtime_state.node_run_steps,
                         outputs=event.outputs,
@@ -533,10 +488,12 @@ class WorkflowAppGenerateTaskPipeline:
                     )
 
                     # save workflow app log
-                    self._save_workflow_app_log(session=session, workflow_run=workflow_run)
+                    self._save_workflow_app_log(session=session, workflow_execution=workflow_execution)
 
-                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
-                        session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
+                    workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+                        session=session,
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution=workflow_execution,
                     )
                     session.commit()
 
@@ -548,26 +505,28 @@ class WorkflowAppGenerateTaskPipeline:
                     raise ValueError("graph runtime state not initialized.")
 
                 with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
-                        session=session,
+                    workflow_execution = self._workflow_cycle_manager.handle_workflow_run_failed(
                         workflow_run_id=self._workflow_run_id,
-                        start_at=graph_runtime_state.start_at,
                         total_tokens=graph_runtime_state.total_tokens,
                         total_steps=graph_runtime_state.node_run_steps,
-                        status=WorkflowRunStatus.FAILED
+                        status=WorkflowExecutionStatus.FAILED
                         if isinstance(event, QueueWorkflowFailedEvent)
-                        else WorkflowRunStatus.STOPPED,
-                        error=event.error if isinstance(event, QueueWorkflowFailedEvent) else event.get_stop_reason(),
+                        else WorkflowExecutionStatus.STOPPED,
+                        error_message=event.error
+                        if isinstance(event, QueueWorkflowFailedEvent)
+                        else event.get_stop_reason(),
                         conversation_id=None,
                         trace_manager=trace_manager,
                         exceptions_count=event.exceptions_count if isinstance(event, QueueWorkflowFailedEvent) else 0,
                     )
 
                     # save workflow app log
-                    self._save_workflow_app_log(session=session, workflow_run=workflow_run)
+                    self._save_workflow_app_log(session=session, workflow_execution=workflow_execution)
 
-                    workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
-                        session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
+                    workflow_finish_resp = self._workflow_response_converter.workflow_finish_to_stream_response(
+                        session=session,
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_execution=workflow_execution,
                     )
                     session.commit()
 
@@ -581,12 +540,11 @@ class WorkflowAppGenerateTaskPipeline:
                 if tts_publisher:
                     tts_publisher.publish(queue_message)
 
-                self._task_state.answer += delta_text
                 yield self._text_chunk_to_stream_response(
                     delta_text, from_variable_selector=event.from_variable_selector
                 )
             elif isinstance(event, QueueAgentLogEvent):
-                yield self._workflow_cycle_manager._handle_agent_log(
+                yield self._workflow_response_converter.handle_agent_log(
                     task_id=self._application_generate_entity.task_id, event=event
                 )
             else:
@@ -595,11 +553,9 @@ class WorkflowAppGenerateTaskPipeline:
         if tts_publisher:
             tts_publisher.publish(None)
 
-    def _save_workflow_app_log(self, *, session: Session, workflow_run: WorkflowRun) -> None:
-        """
-        Save workflow app log.
-        :return:
-        """
+    def _save_workflow_app_log(self, *, session: Session, workflow_execution: WorkflowExecution) -> None:
+        workflow_run = session.scalar(select(WorkflowRun).where(WorkflowRun.id == workflow_execution.id_))
+        assert workflow_run is not None
         invoke_from = self._application_generate_entity.invoke_from
         if invoke_from == InvokeFrom.SERVICE_API:
             created_from = WorkflowAppLogCreatedFrom.SERVICE_API

api/core/app/apps/workflow_app_runner.py

@@ -29,8 +29,8 @@ from core.app.entities.queue_entities import (
     QueueWorkflowStartedEvent,
     QueueWorkflowSucceededEvent,
 )
-from core.workflow.entities.node_entities import NodeRunMetadataKey
 from core.workflow.entities.variable_pool import VariablePool
+from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey
 from core.workflow.graph_engine.entities.event import (
     AgentLogEvent,
     GraphEngineEvent,
@@ -295,7 +295,7 @@ class WorkflowBasedAppRunner(AppRunner):
             inputs: Mapping[str, Any] | None = {}
             process_data: Mapping[str, Any] | None = {}
             outputs: Mapping[str, Any] | None = {}
-            execution_metadata: Mapping[NodeRunMetadataKey, Any] | None = {}
+            execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] | None = {}
             if node_run_result:
                 inputs = node_run_result.inputs
                 process_data = node_run_result.process_data

api/core/app/entities/app_invoke_entities.py

@@ -76,6 +76,8 @@ class AppGenerateEntity(BaseModel):
     App Generate Entity.
     """
 
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
     task_id: str
 
     # app config
@@ -99,9 +101,6 @@ class AppGenerateEntity(BaseModel):
     # tracing instance
     trace_manager: Optional[TraceQueueManager] = None
 
-    class Config:
-        arbitrary_types_allowed = True
-
 
 class EasyUIBasedAppGenerateEntity(AppGenerateEntity):
     """
@@ -205,7 +204,7 @@ class WorkflowAppGenerateEntity(AppGenerateEntity):
 
     # app config
     app_config: WorkflowUIBasedAppConfig
-    workflow_run_id: str
+    workflow_execution_id: str
 
     class SingleIterationRunEntity(BaseModel):
         """

api/core/app/entities/queue_entities.py

@@ -1,4 +1,4 @@
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from datetime import datetime
 from enum import Enum, StrEnum
 from typing import Any, Optional
@@ -6,7 +6,9 @@ from typing import Any, Optional
 from pydantic import BaseModel
 
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
-from core.workflow.entities.node_entities import AgentNodeStrategyInit, NodeRunMetadataKey
+from core.rag.entities.citation_metadata import RetrievalSourceMetadata
+from core.workflow.entities.node_entities import AgentNodeStrategyInit
+from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey
 from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
 from core.workflow.nodes import NodeType
 from core.workflow.nodes.base import BaseNodeData
@@ -282,7 +284,7 @@ class QueueRetrieverResourcesEvent(AppQueueEvent):
     """
 
     event: QueueEvent = QueueEvent.RETRIEVER_RESOURCES
-    retriever_resources: list[dict]
+    retriever_resources: Sequence[RetrievalSourceMetadata]
     in_iteration_id: Optional[str] = None
     """iteration id if node is in iteration"""
     in_loop_id: Optional[str] = None
@@ -412,7 +414,7 @@ class QueueNodeSucceededEvent(AppQueueEvent):
     inputs: Optional[Mapping[str, Any]] = None
     process_data: Optional[Mapping[str, Any]] = None
     outputs: Optional[Mapping[str, Any]] = None
-    execution_metadata: Optional[Mapping[NodeRunMetadataKey, Any]] = None
+    execution_metadata: Optional[Mapping[WorkflowNodeExecutionMetadataKey, Any]] = None
 
     error: Optional[str] = None
     """single iteration duration map"""
@@ -446,7 +448,7 @@ class QueueNodeRetryEvent(QueueNodeStartedEvent):
     inputs: Optional[Mapping[str, Any]] = None
     process_data: Optional[Mapping[str, Any]] = None
     outputs: Optional[Mapping[str, Any]] = None
-    execution_metadata: Optional[Mapping[NodeRunMetadataKey, Any]] = None
+    execution_metadata: Optional[Mapping[WorkflowNodeExecutionMetadataKey, Any]] = None
 
     error: str
     retry_index: int  # retry index
@@ -480,7 +482,7 @@ class QueueNodeInIterationFailedEvent(AppQueueEvent):
     inputs: Optional[Mapping[str, Any]] = None
     process_data: Optional[Mapping[str, Any]] = None
     outputs: Optional[Mapping[str, Any]] = None
-    execution_metadata: Optional[Mapping[NodeRunMetadataKey, Any]] = None
+    execution_metadata: Optional[Mapping[WorkflowNodeExecutionMetadataKey, Any]] = None
 
     error: str
 
@@ -513,7 +515,7 @@ class QueueNodeInLoopFailedEvent(AppQueueEvent):
     inputs: Optional[Mapping[str, Any]] = None
     process_data: Optional[Mapping[str, Any]] = None
     outputs: Optional[Mapping[str, Any]] = None
-    execution_metadata: Optional[Mapping[NodeRunMetadataKey, Any]] = None
+    execution_metadata: Optional[Mapping[WorkflowNodeExecutionMetadataKey, Any]] = None
 
     error: str
 
@@ -546,7 +548,7 @@ class QueueNodeExceptionEvent(AppQueueEvent):
     inputs: Optional[Mapping[str, Any]] = None
     process_data: Optional[Mapping[str, Any]] = None
     outputs: Optional[Mapping[str, Any]] = None
-    execution_metadata: Optional[Mapping[NodeRunMetadataKey, Any]] = None
+    execution_metadata: Optional[Mapping[WorkflowNodeExecutionMetadataKey, Any]] = None
 
     error: str
 
@@ -579,7 +581,7 @@ class QueueNodeFailedEvent(AppQueueEvent):
     inputs: Optional[Mapping[str, Any]] = None
     process_data: Optional[Mapping[str, Any]] = None
     outputs: Optional[Mapping[str, Any]] = None
-    execution_metadata: Optional[Mapping[NodeRunMetadataKey, Any]] = None
+    execution_metadata: Optional[Mapping[WorkflowNodeExecutionMetadataKey, Any]] = None
 
     error: str
 

api/core/app/entities/task_entities.py

@@ -2,12 +2,29 @@ from collections.abc import Mapping, Sequence
 from enum import Enum
 from typing import Any, Optional
 
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel, ConfigDict, Field
 
-from core.model_runtime.entities.llm_entities import LLMResult
+from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage
 from core.model_runtime.utils.encoders import jsonable_encoder
-from core.workflow.entities.node_entities import AgentNodeStrategyInit, NodeRunMetadataKey
-from models.workflow import WorkflowNodeExecutionStatus
+from core.rag.entities.citation_metadata import RetrievalSourceMetadata
+from core.workflow.entities.node_entities import AgentNodeStrategyInit
+from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus
+
+
+class AnnotationReplyAccount(BaseModel):
+    id: str
+    name: str
+
+
+class AnnotationReply(BaseModel):
+    id: str
+    account: AnnotationReplyAccount
+
+
+class TaskStateMetadata(BaseModel):
+    annotation_reply: AnnotationReply | None = None
+    retriever_resources: Sequence[RetrievalSourceMetadata] = Field(default_factory=list)
+    usage: LLMUsage | None = None
 
 
 class TaskState(BaseModel):
@@ -15,7 +32,7 @@ class TaskState(BaseModel):
     TaskState entity
     """
 
-    metadata: dict = {}
+    metadata: TaskStateMetadata = Field(default_factory=TaskStateMetadata)
 
 
 class EasyUITaskState(TaskState):
@@ -189,8 +206,7 @@ class WorkflowStartStreamResponse(StreamResponse):
 
         id: str
         workflow_id: str
-        sequence_number: int
-        inputs: dict
+        inputs: Mapping[str, Any]
         created_at: int
 
     event: StreamEvent = StreamEvent.WORKFLOW_STARTED
@@ -210,9 +226,8 @@ class WorkflowFinishStreamResponse(StreamResponse):
 
         id: str
         workflow_id: str
-        sequence_number: int
         status: str
-        outputs: Optional[dict] = None
+        outputs: Optional[Mapping[str, Any]] = None
         error: Optional[str] = None
         elapsed_time: float
         total_tokens: int
@@ -307,7 +322,7 @@ class NodeFinishStreamResponse(StreamResponse):
         status: str
         error: Optional[str] = None
         elapsed_time: float
-        execution_metadata: Optional[Mapping[NodeRunMetadataKey, Any]] = None
+        execution_metadata: Optional[Mapping[WorkflowNodeExecutionMetadataKey, Any]] = None
         created_at: int
         finished_at: int
         files: Optional[Sequence[Mapping[str, Any]]] = []
@@ -376,7 +391,7 @@ class NodeRetryStreamResponse(StreamResponse):
         status: str
         error: Optional[str] = None
         elapsed_time: float
-        execution_metadata: Optional[Mapping[NodeRunMetadataKey, Any]] = None
+        execution_metadata: Optional[Mapping[WorkflowNodeExecutionMetadataKey, Any]] = None
         created_at: int
         finished_at: int
         files: Optional[Sequence[Mapping[str, Any]]] = []
@@ -788,7 +803,7 @@ class WorkflowAppBlockingResponse(AppBlockingResponse):
         id: str
         workflow_id: str
         status: str
-        outputs: Optional[dict] = None
+        outputs: Optional[Mapping[str, Any]] = None
         error: Optional[str] = None
         elapsed_time: float
         total_tokens: int

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -1,4 +1,3 @@
-import json
 import logging
 import time
 from collections.abc import Generator
@@ -43,7 +42,7 @@ from core.app.entities.task_entities import (
     StreamResponse,
 )
 from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline
-from core.app.task_pipeline.message_cycle_manage import MessageCycleManage
+from core.app.task_pipeline.message_cycle_manager import MessageCycleManager
 from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
@@ -51,7 +50,6 @@ from core.model_runtime.entities.message_entities import (
     AssistantPromptMessage,
 )
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from core.model_runtime.utils.encoders import jsonable_encoder
 from core.ops.entities.trace_entity import TraceTaskName
 from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
@@ -63,7 +61,7 @@ from models.model import AppMode, Conversation, Message, MessageAgentThought
 logger = logging.getLogger(__name__)
 
 
-class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleManage):
+class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
     """
     EasyUIBasedGenerateTaskPipeline is a class that generate stream output and state management for Application.
     """
@@ -104,6 +102,11 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
             )
         )
 
+        self._message_cycle_manager = MessageCycleManager(
+            application_generate_entity=application_generate_entity,
+            task_state=self._task_state,
+        )
+
         self._conversation_name_generate_thread: Optional[Thread] = None
 
     def process(
@@ -115,7 +118,7 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
     ]:
         if self._application_generate_entity.app_config.app_mode != AppMode.COMPLETION:
             # start generate conversation name thread
-            self._conversation_name_generate_thread = self._generate_conversation_name(
+            self._conversation_name_generate_thread = self._message_cycle_manager.generate_conversation_name(
                 conversation_id=self._conversation_id, query=self._application_generate_entity.query or ""
             )
 
@@ -136,9 +139,9 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
             if isinstance(stream_response, ErrorStreamResponse):
                 raise stream_response.err
             elif isinstance(stream_response, MessageEndStreamResponse):
-                extras = {"usage": jsonable_encoder(self._task_state.llm_result.usage)}
+                extras = {"usage": self._task_state.llm_result.usage.model_dump()}
                 if self._task_state.metadata:
-                    extras["metadata"] = self._task_state.metadata
+                    extras["metadata"] = self._task_state.metadata.model_dump()
                 response: Union[ChatbotAppBlockingResponse, CompletionAppBlockingResponse]
                 if self._conversation_mode == AppMode.COMPLETION.value:
                     response = CompletionAppBlockingResponse(
@@ -277,7 +280,9 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
                 )
                 if output_moderation_answer:
                     self._task_state.llm_result.message.content = output_moderation_answer
-                    yield self._message_replace_to_stream_response(answer=output_moderation_answer)
+                    yield self._message_cycle_manager.message_replace_to_stream_response(
+                        answer=output_moderation_answer
+                    )
 
                 with Session(db.engine) as session:
                     # Save message
@@ -286,9 +291,9 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
                 message_end_resp = self._message_end_to_stream_response()
                 yield message_end_resp
             elif isinstance(event, QueueRetrieverResourcesEvent):
-                self._handle_retriever_resources(event)
+                self._message_cycle_manager.handle_retriever_resources(event)
             elif isinstance(event, QueueAnnotationReplyEvent):
-                annotation = self._handle_annotation_reply(event)
+                annotation = self._message_cycle_manager.handle_annotation_reply(event)
                 if annotation:
                     self._task_state.llm_result.message.content = annotation.content
             elif isinstance(event, QueueAgentThoughtEvent):
@@ -296,7 +301,7 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
                 if agent_thought_response is not None:
                     yield agent_thought_response
             elif isinstance(event, QueueMessageFileEvent):
-                response = self._message_file_to_stream_response(event)
+                response = self._message_cycle_manager.message_file_to_stream_response(event)
                 if response:
                     yield response
             elif isinstance(event, QueueLLMChunkEvent | QueueAgentMessageEvent):
@@ -318,7 +323,7 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
                 self._task_state.llm_result.message.content = current_content
 
                 if isinstance(event, QueueLLMChunkEvent):
-                    yield self._message_to_stream_response(
+                    yield self._message_cycle_manager.message_to_stream_response(
                         answer=cast(str, delta_text),
                         message_id=self._message_id,
                     )
@@ -328,7 +333,7 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
                         message_id=self._message_id,
                     )
             elif isinstance(event, QueueMessageReplaceEvent):
-                yield self._message_replace_to_stream_response(answer=event.text)
+                yield self._message_cycle_manager.message_replace_to_stream_response(answer=event.text)
             elif isinstance(event, QueuePingEvent):
                 yield self._ping_stream_response()
             else:
@@ -372,9 +377,7 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
         message.provider_response_latency = time.perf_counter() - self._start_at
         message.total_price = usage.total_price
         message.currency = usage.currency
-        message.message_metadata = (
-            json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
-        )
+        message.message_metadata = self._task_state.metadata.model_dump_json()
 
         if trace_manager:
             trace_manager.add_trace_task(
@@ -423,16 +426,12 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
         Message end to stream response.
         :return:
         """
-        self._task_state.metadata["usage"] = jsonable_encoder(self._task_state.llm_result.usage)
-
-        extras = {}
-        if self._task_state.metadata:
-            extras["metadata"] = self._task_state.metadata
-
+        self._task_state.metadata.usage = self._task_state.llm_result.usage
+        metadata_dict = self._task_state.metadata.model_dump()
         return MessageEndStreamResponse(
             task_id=self._application_generate_entity.task_id,
             id=self._message_id,
-            metadata=extras.get("metadata", {}),
+            metadata=metadata_dict,
         )
 
     def _agent_message_to_stream_response(self, answer: str, message_id: str) -> AgentMessageStreamResponse:
@@ -455,8 +454,6 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
         agent_thought: Optional[MessageAgentThought] = (
             db.session.query(MessageAgentThought).filter(MessageAgentThought.id == event.agent_thought_id).first()
         )
-        db.session.refresh(agent_thought)
-        db.session.close()
 
         if agent_thought:
             return AgentThoughtStreamResponse(

api/core/app/task_pipeline/message_cycle_manager.py

@@ -17,6 +17,8 @@ from core.app.entities.queue_entities import (
     QueueRetrieverResourcesEvent,
 )
 from core.app.entities.task_entities import (
+    AnnotationReply,
+    AnnotationReplyAccount,
     EasyUITaskState,
     MessageFileStreamResponse,
     MessageReplaceStreamResponse,
@@ -30,7 +32,7 @@ from models.model import AppMode, Conversation, MessageAnnotation, MessageFile
 from services.annotation_service import AppAnnotationService
 
 
-class MessageCycleManage:
+class MessageCycleManager:
     def __init__(
         self,
         *,
@@ -45,7 +47,7 @@ class MessageCycleManage:
         self._application_generate_entity = application_generate_entity
         self._task_state = task_state
 
-    def _generate_conversation_name(self, *, conversation_id: str, query: str) -> Optional[Thread]:
+    def generate_conversation_name(self, *, conversation_id: str, query: str) -> Optional[Thread]:
         """
         Generate conversation name.
         :param conversation_id: conversation id
@@ -102,7 +104,7 @@ class MessageCycleManage:
                 db.session.commit()
                 db.session.close()
 
-    def _handle_annotation_reply(self, event: QueueAnnotationReplyEvent) -> Optional[MessageAnnotation]:
+    def handle_annotation_reply(self, event: QueueAnnotationReplyEvent) -> Optional[MessageAnnotation]:
         """
         Handle annotation reply.
         :param event: event
@@ -111,25 +113,28 @@ class MessageCycleManage:
         annotation = AppAnnotationService.get_annotation_by_id(event.message_annotation_id)
         if annotation:
             account = annotation.account
-            self._task_state.metadata["annotation_reply"] = {
-                "id": annotation.id,
-                "account": {"id": annotation.account_id, "name": account.name if account else "Dify user"},
-            }
+            self._task_state.metadata.annotation_reply = AnnotationReply(
+                id=annotation.id,
+                account=AnnotationReplyAccount(
+                    id=annotation.account_id,
+                    name=account.name if account else "Dify user",
+                ),
+            )
 
             return annotation
 
         return None
 
-    def _handle_retriever_resources(self, event: QueueRetrieverResourcesEvent) -> None:
+    def handle_retriever_resources(self, event: QueueRetrieverResourcesEvent) -> None:
         """
         Handle retriever resources.
         :param event: event
         :return:
         """
         if self._application_generate_entity.app_config.additional_features.show_retrieve_source:
-            self._task_state.metadata["retriever_resources"] = event.retriever_resources
+            self._task_state.metadata.retriever_resources = event.retriever_resources
 
-    def _message_file_to_stream_response(self, event: QueueMessageFileEvent) -> Optional[MessageFileStreamResponse]:
+    def message_file_to_stream_response(self, event: QueueMessageFileEvent) -> Optional[MessageFileStreamResponse]:
         """
         Message file to stream response.
         :param event: event
@@ -166,7 +171,7 @@ class MessageCycleManage:
 
         return None
 
-    def _message_to_stream_response(
+    def message_to_stream_response(
         self, answer: str, message_id: str, from_variable_selector: Optional[list[str]] = None
     ) -> MessageStreamResponse:
         """
@@ -182,7 +187,7 @@ class MessageCycleManage:
             from_variable_selector=from_variable_selector,
         )
 
-    def _message_replace_to_stream_response(self, answer: str, reason: str = "") -> MessageReplaceStreamResponse:
+    def message_replace_to_stream_response(self, answer: str, reason: str = "") -> MessageReplaceStreamResponse:
         """
         Message replace to stream response.
         :param answer: answer

api/core/callback_handler/index_tool_callback_handler.py

@@ -1,8 +1,10 @@
 import logging
+from collections.abc import Sequence
 
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.app.entities.queue_entities import QueueRetrieverResourcesEvent
+from core.rag.entities.citation_metadata import RetrievalSourceMetadata
 from core.rag.index_processor.constant.index_type import IndexType
 from core.rag.models.document import Document
 from extensions.ext_database import db
@@ -85,7 +87,8 @@ class DatasetIndexToolCallbackHandler:
 
                 db.session.commit()
 
-    def return_retriever_resource_info(self, resource: list):
+    # TODO(-LAN-): Improve type check
+    def return_retriever_resource_info(self, resource: Sequence[RetrievalSourceMetadata]):
         """Handle return_retriever_resource_info."""
         self._queue_manager.publish(
             QueueRetrieverResourcesEvent(retriever_resources=resource), PublishFrom.APPLICATION_MANAGER

api/core/entities/model_entities.py

@@ -55,6 +55,25 @@ class ProviderModelWithStatusEntity(ProviderModel):
     status: ModelStatus
     load_balancing_enabled: bool = False
 
+    def raise_for_status(self) -> None:
+        """
+        Check model status and raise ValueError if not active.
+
+        :raises ValueError: When model status is not active, with a descriptive message
+        """
+        if self.status == ModelStatus.ACTIVE:
+            return
+
+        error_messages = {
+            ModelStatus.NO_CONFIGURE: "Model is not configured",
+            ModelStatus.QUOTA_EXCEEDED: "Model quota has been exceeded",
+            ModelStatus.NO_PERMISSION: "No permission to use this model",
+            ModelStatus.DISABLED: "Model is disabled",
+        }
+
+        if self.status in error_messages:
+            raise ValueError(error_messages[self.status])
+
 
 class ModelWithProviderEntity(ProviderModelWithStatusEntity):
     """

api/core/entities/provider_configuration.py

@@ -754,7 +754,7 @@ class ProviderConfiguration(BaseModel):
         :param only_active: return active model only
         :return:
         """
-        provider_models = self.get_provider_models(model_type, only_active)
+        provider_models = self.get_provider_models(model_type, only_active, model)
 
         for provider_model in provider_models:
             if provider_model.model == model:
@@ -763,12 +763,13 @@ class ProviderConfiguration(BaseModel):
         return None
 
     def get_provider_models(
-        self, model_type: Optional[ModelType] = None, only_active: bool = False
+        self, model_type: Optional[ModelType] = None, only_active: bool = False, model: Optional[str] = None
     ) -> list[ModelWithProviderEntity]:
         """
         Get provider models.
         :param model_type: model type
         :param only_active: only active models
+        :param model: model name
         :return:
         """
         model_provider_factory = ModelProviderFactory(self.tenant_id)
@@ -791,7 +792,10 @@ class ProviderConfiguration(BaseModel):
             )
         else:
             provider_models = self._get_custom_provider_models(
-                model_types=model_types, provider_schema=provider_schema, model_setting_map=model_setting_map
+                model_types=model_types,
+                provider_schema=provider_schema,
+                model_setting_map=model_setting_map,
+                model=model,
             )
 
         if only_active:
@@ -943,6 +947,7 @@ class ProviderConfiguration(BaseModel):
         model_types: Sequence[ModelType],
         provider_schema: ProviderEntity,
         model_setting_map: dict[ModelType, dict[str, ModelSettings]],
+        model: Optional[str] = None,
     ) -> list[ModelWithProviderEntity]:
         """
         Get custom provider models.
@@ -995,7 +1000,8 @@ class ProviderConfiguration(BaseModel):
         for model_configuration in self.custom_configuration.models:
             if model_configuration.model_type not in model_types:
                 continue
-
+            if model and model != model_configuration.model:
+                continue
             try:
                 custom_model_schema = self.get_model_schema(
                     model_type=model_configuration.model_type,

api/core/extension/extensible.py

@@ -41,45 +41,53 @@ class Extensible:
         extensions = []
         position_map: dict[str, int] = {}
 
-        # get the path of the current class
-        current_path = os.path.abspath(cls.__module__.replace(".", os.path.sep) + ".py")
-        current_dir_path = os.path.dirname(current_path)
-
-        # traverse subdirectories
-        for subdir_name in os.listdir(current_dir_path):
-            if subdir_name.startswith("__"):
-                continue
-
-            subdir_path = os.path.join(current_dir_path, subdir_name)
-            extension_name = subdir_name
-            if os.path.isdir(subdir_path):
+        # Get the package name from the module path
+        package_name = ".".join(cls.__module__.split(".")[:-1])
+
+        try:
+            # Get package directory path
+            package_spec = importlib.util.find_spec(package_name)
+            if not package_spec or not package_spec.origin:
+                raise ImportError(f"Could not find package {package_name}")
+
+            package_dir = os.path.dirname(package_spec.origin)
+
+            # Traverse subdirectories
+            for subdir_name in os.listdir(package_dir):
+                if subdir_name.startswith("__"):
+                    continue
+
+                subdir_path = os.path.join(package_dir, subdir_name)
+                if not os.path.isdir(subdir_path):
+                    continue
+
+                extension_name = subdir_name
                 file_names = os.listdir(subdir_path)
 
-                # is builtin extension, builtin extension
-                # in the front-end page and business logic, there are special treatments.
+                # Check for extension module file
+                if (extension_name + ".py") not in file_names:
+                    logging.warning(f"Missing {extension_name}.py file in {subdir_path}, Skip.")
+                    continue
+
+                # Check for builtin flag and position
                 builtin = False
-                # default position is 0 can not be None for sort_to_dict_by_position_map
                 position = 0
                 if "__builtin__" in file_names:
                     builtin = True
-
                     builtin_file_path = os.path.join(subdir_path, "__builtin__")
                     if os.path.exists(builtin_file_path):
                         position = int(Path(builtin_file_path).read_text(encoding="utf-8").strip())
                     position_map[extension_name] = position
 
-                if (extension_name + ".py") not in file_names:
-                    logging.warning(f"Missing {extension_name}.py file in {subdir_path}, Skip.")
-                    continue
-
-                # Dynamic loading {subdir_name}.py file and find the subclass of Extensible
-                py_path = os.path.join(subdir_path, extension_name + ".py")
-                spec = importlib.util.spec_from_file_location(extension_name, py_path)
+                # Import the extension module
+                module_name = f"{package_name}.{extension_name}.{extension_name}"
+                spec = importlib.util.find_spec(module_name)
                 if not spec or not spec.loader:
-                    raise Exception(f"Failed to load module {extension_name} from {py_path}")
+                    raise ImportError(f"Failed to load module {module_name}")
                 mod = importlib.util.module_from_spec(spec)
                 spec.loader.exec_module(mod)
 
+                # Find extension class
                 extension_class = None
                 for name, obj in vars(mod).items():
                     if isinstance(obj, type) and issubclass(obj, cls) and obj != cls:
@@ -87,21 +95,21 @@ class Extensible:
                         break
 
                 if not extension_class:
-                    logging.warning(f"Missing subclass of {cls.__name__} in {py_path}, Skip.")
+                    logging.warning(f"Missing subclass of {cls.__name__} in {module_name}, Skip.")
                     continue
 
+                # Load schema if not builtin
                 json_data: dict[str, Any] = {}
                 if not builtin:
-                    if "schema.json" not in file_names:
+                    json_path = os.path.join(subdir_path, "schema.json")
+                    if not os.path.exists(json_path):
                         logging.warning(f"Missing schema.json file in {subdir_path}, Skip.")
                         continue
 
-                    json_path = os.path.join(subdir_path, "schema.json")
-                    json_data = {}
-                    if os.path.exists(json_path):
-                        with open(json_path, encoding="utf-8") as f:
-                            json_data = json.load(f)
+                    with open(json_path, encoding="utf-8") as f:
+                        json_data = json.load(f)
 
+                # Create extension
                 extensions.append(
                     ModuleExtension(
                         extension_class=extension_class,
@@ -113,6 +121,11 @@ class Extensible:
                     )
                 )
 
+        except Exception as e:
+            logging.exception("Error scanning extensions")
+            raise
+
+        # Sort extensions by position
         sorted_extensions = sort_to_dict_by_position_map(
             position_map=position_map, data=extensions, name_func=lambda x: x.name
         )

api/core/helper/code_executor/code_executor.py

@@ -15,6 +15,7 @@ from core.helper.code_executor.python3.python3_transformer import Python3Templat
 from core.helper.code_executor.template_transformer import TemplateTransformer
 
 logger = logging.getLogger(__name__)
+code_execution_endpoint_url = URL(str(dify_config.CODE_EXECUTION_ENDPOINT))
 
 
 class CodeExecutionError(Exception):
@@ -64,7 +65,7 @@ class CodeExecutor:
         :param code: code
         :return:
         """
-        url = URL(str(dify_config.CODE_EXECUTION_ENDPOINT)) / "v1" / "sandbox" / "run"
+        url = code_execution_endpoint_url / "v1" / "sandbox" / "run"
 
         headers = {"X-Api-Key": dify_config.CODE_EXECUTION_API_KEY}
 

api/core/helper/marketplace.py

@@ -7,29 +7,28 @@ from configs import dify_config
 from core.helper.download import download_with_size_limit
 from core.plugin.entities.marketplace import MarketplacePluginDeclaration
 
+marketplace_api_url = URL(str(dify_config.MARKETPLACE_API_URL))
 
-def get_plugin_pkg_url(plugin_unique_identifier: str):
-    return (URL(str(dify_config.MARKETPLACE_API_URL)) / "api/v1/plugins/download").with_query(
-        unique_identifier=plugin_unique_identifier
-    )
+
+def get_plugin_pkg_url(plugin_unique_identifier: str) -> str:
+    return str((marketplace_api_url / "api/v1/plugins/download").with_query(unique_identifier=plugin_unique_identifier))
 
 
 def download_plugin_pkg(plugin_unique_identifier: str):
-    url = str(get_plugin_pkg_url(plugin_unique_identifier))
-    return download_with_size_limit(url, dify_config.PLUGIN_MAX_PACKAGE_SIZE)
+    return download_with_size_limit(get_plugin_pkg_url(plugin_unique_identifier), dify_config.PLUGIN_MAX_PACKAGE_SIZE)
 
 
 def batch_fetch_plugin_manifests(plugin_ids: list[str]) -> Sequence[MarketplacePluginDeclaration]:
     if len(plugin_ids) == 0:
         return []
 
-    url = str(URL(str(dify_config.MARKETPLACE_API_URL)) / "api/v1/plugins/batch")
+    url = str(marketplace_api_url / "api/v1/plugins/batch")
     response = requests.post(url, json={"plugin_ids": plugin_ids})
     response.raise_for_status()
     return [MarketplacePluginDeclaration(**plugin) for plugin in response.json()["data"]["plugins"]]
 
 
 def record_install_plugin_event(plugin_unique_identifier: str):
-    url = str(URL(str(dify_config.MARKETPLACE_API_URL)) / "api/v1/stats/plugins/install_count")
+    url = str(marketplace_api_url / "api/v1/stats/plugins/install_count")
     response = requests.post(url, json={"unique_identifier": plugin_unique_identifier})
     response.raise_for_status()

api/core/llm_generator/llm_generator.py

@@ -51,15 +51,19 @@ class LLMGenerator:
             response = cast(
                 LLMResult,
                 model_instance.invoke_llm(
-                    prompt_messages=list(prompts), model_parameters={"max_tokens": 100, "temperature": 1}, stream=False
+                    prompt_messages=list(prompts), model_parameters={"max_tokens": 500, "temperature": 1}, stream=False
                 ),
             )
         answer = cast(str, response.message.content)
         cleaned_answer = re.sub(r"^.*(\{.*\}).*$", r"\1", answer, flags=re.DOTALL)
         if cleaned_answer is None:
             return ""
-        result_dict = json.loads(cleaned_answer)
-        answer = result_dict["Your Output"]
+        try:
+            result_dict = json.loads(cleaned_answer)
+            answer = result_dict["Your Output"]
+        except json.JSONDecodeError as e:
+            logging.exception("Failed to generate name after answer, use query instead")
+            answer = query
         name = answer.strip()
 
         if len(name) > 75:

api/core/llm_generator/prompts.py

@@ -1,61 +1,20 @@
-# Written by YORKI MINAKO🤡, Edited by Xiaoyi
-CONVERSATION_TITLE_PROMPT = """You need to decompose the user's input into "subject" and "intention" in order to accurately figure out what the user's input language actually is.
-Notice: the language type user uses could be diverse, which can be English, Chinese, Italian, Español, Arabic, Japanese, French, and etc.
-ENSURE your output is in the SAME language as the user's input!
-Your output is restricted only to: (Input language) Intention + Subject(short as possible)
-Your output MUST be a valid JSON.
+# Written by YORKI MINAKO🤡, Edited by Xiaoyi, Edited by yasu-oh
+CONVERSATION_TITLE_PROMPT = """You are asked to generate a concise chat title by decomposing the user’s input into two parts: “Intention” and “Subject”.
 
-Tip: When the user's question is directed at you (the language model), you can add an emoji to make it more fun.
+1. Detect Input Language
+Automatically identify the language of the user’s input (e.g. English, Chinese, Italian, Español, Arabic, Japanese, French, and etc.).
 
+2. Generate Title
+- Combine Intention + Subject into a single, as-short-as-possible phrase.
+- The title must be natural, friendly, and in the same language as the input.
+- If the input is a direct question to the model, you may add an emoji at the end.
 
-example 1:
-User Input: hi, yesterday i had some burgers.
+3. Output Format
+Return **only** a valid JSON object with these exact keys and no additional text:
 {
-  "Language Type": "The user's input is pure English",
-  "Your Reasoning": "The language of my output must be pure English.",
-  "Your Output": "sharing yesterday's food"
-}
-
-example 2:
-User Input: hello
-{
-  "Language Type": "The user's input is pure English",
-  "Your Reasoning": "The language of my output must be pure English.",
-  "Your Output": "Greeting myself☺️"
-}
-
-
-example 3:
-User Input: why mmap file: oom
-{
-  "Language Type": "The user's input is written in pure English",
-  "Your Reasoning": "The language of my output must be pure English.",
-  "Your Output": "Asking about the reason for mmap file: oom"
-}
-
-
-example 4:
-User Input: www.convinceme.yesterday-you-ate-seafood.tv讲了什么？
-{
-  "Language Type": "The user's input English-Chinese mixed",
-  "Your Reasoning": "The English-part is an URL, the main intention is still written in Chinese, so the language of my output must be using Chinese.",
-  "Your Output": "询问网站www.convinceme.yesterday-you-ate-seafood.tv"
-}
-
-example 5:
-User Input: why小红的年龄is老than小明？
-{
-  "Language Type": "The user's input is English-Chinese mixed",
-  "Your Reasoning": "The English parts are filler words, the main intention is written in Chinese, besides, Chinese occupies a greater \"actual meaning\" than English, so the language of my output must be using Chinese.",
-  "Your Output": "询问小红和小明的年龄"
-}
-
-example 6:
-User Input: yo, 你今天咋样？
-{
-  "Language Type": "The user's input is English-Chinese mixed",
-  "Your Reasoning": "The English-part is a subjective particle, the main intention is written in Chinese, so the language of my output must be using Chinese.",
-  "Your Output": "查询今日我的状态☺️"
+  "Language Type": "<Detected language>",
+  "Your Reasoning": "<Brief explanation in that language>",
+  "Your Output": "<Intention + Subject>"
 }
 
 User Input:

api/core/model_runtime/entities/llm_entities.py

@@ -17,19 +17,6 @@ class LLMMode(StrEnum):
     COMPLETION = "completion"
     CHAT = "chat"
 
-    @classmethod
-    def value_of(cls, value: str) -> "LLMMode":
-        """
-        Get value of given mode.
-
-        :param value: mode value
-        :return: mode
-        """
-        for mode in cls:
-            if mode.value == value:
-                return mode
-        raise ValueError(f"invalid mode value {value}")
-
 
 class LLMUsage(ModelUsage):
     """

api/core/model_runtime/entities/model_entities.py

@@ -160,6 +160,10 @@ class ProviderModel(BaseModel):
     deprecated: bool = False
     model_config = ConfigDict(protected_namespaces=())
 
+    @property
+    def support_structure_output(self) -> bool:
+        return self.features is not None and ModelFeature.STRUCTURED_OUTPUT in self.features
+
 
 class ParameterRule(BaseModel):
     """

api/core/model_runtime/utils/encoders.py

@@ -129,17 +129,18 @@ def jsonable_encoder(
             sqlalchemy_safe=sqlalchemy_safe,
         )
     if dataclasses.is_dataclass(obj):
-        # FIXME: mypy error, try to fix it instead of using type: ignore
-        obj_dict = dataclasses.asdict(obj)  # type: ignore
-        return jsonable_encoder(
-            obj_dict,
-            by_alias=by_alias,
-            exclude_unset=exclude_unset,
-            exclude_defaults=exclude_defaults,
-            exclude_none=exclude_none,
-            custom_encoder=custom_encoder,
-            sqlalchemy_safe=sqlalchemy_safe,
-        )
+        # Ensure obj is a dataclass instance, not a dataclass type
+        if not isinstance(obj, type):
+            obj_dict = dataclasses.asdict(obj)
+            return jsonable_encoder(
+                obj_dict,
+                by_alias=by_alias,
+                exclude_unset=exclude_unset,
+                exclude_defaults=exclude_defaults,
+                exclude_none=exclude_none,
+                custom_encoder=custom_encoder,
+                sqlalchemy_safe=sqlalchemy_safe,
+            )
     if isinstance(obj, Enum):
         return obj.value
     if isinstance(obj, PurePath):

api/core/ops/base_trace_instance.py

@@ -1,7 +1,11 @@
 from abc import ABC, abstractmethod
 
+from sqlalchemy.orm import Session
+
 from core.ops.entities.config_entity import BaseTracingConfig
 from core.ops.entities.trace_entity import BaseTraceInfo
+from extensions.ext_database import db
+from models import Account, App, TenantAccountJoin
 
 
 class BaseTraceInstance(ABC):
@@ -24,3 +28,38 @@ class BaseTraceInstance(ABC):
         Subclasses must implement specific tracing logic for activities.
         """
         ...
+
+    def get_service_account_with_tenant(self, app_id: str) -> Account:
+        """
+        Get service account for an app and set up its tenant.
+
+        Args:
+            app_id: The ID of the app
+
+        Returns:
+            Account: The service account with tenant set up
+
+        Raises:
+            ValueError: If app, creator account or tenant cannot be found
+        """
+        with Session(db.engine, expire_on_commit=False) as session:
+            # Get the app to find its creator
+            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)
+
+            return service_account

api/core/ops/entities/trace_entity.py

@@ -3,7 +3,7 @@ from datetime import datetime
 from enum import StrEnum
 from typing import Any, Optional, Union
 
-from pydantic import BaseModel, ConfigDict, field_validator
+from pydantic import BaseModel, ConfigDict, field_serializer, field_validator
 
 
 class BaseTraceInfo(BaseModel):
@@ -24,10 +24,13 @@ class BaseTraceInfo(BaseModel):
             return v
         return ""
 
-    class Config:
-        json_encoders = {
-            datetime: lambda v: v.isoformat(),
-        }
+    model_config = ConfigDict(protected_namespaces=())
+
+    @field_serializer("start_time", "end_time")
+    def serialize_datetime(self, dt: datetime | None) -> str | None:
+        if dt is None:
+            return None
+        return dt.isoformat()
 
 
 class WorkflowTraceInfo(BaseTraceInfo):

api/core/ops/langfuse_trace/langfuse_trace.py

@@ -4,7 +4,7 @@ from datetime import datetime, timedelta
 from typing import Optional
 
 from langfuse import Langfuse  # type: ignore
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import sessionmaker
 
 from core.ops.base_trace_instance import BaseTraceInstance
 from core.ops.entities.config_entity import LangfuseConfig
@@ -31,7 +31,7 @@ from core.ops.utils import filter_none_values
 from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
 from core.workflow.nodes.enums import NodeType
 from extensions.ext_database import db
-from models import Account, App, EndUser, WorkflowNodeExecutionTriggeredFrom
+from models import EndUser, WorkflowNodeExecutionTriggeredFrom
 
 logger = logging.getLogger(__name__)
 
@@ -114,22 +114,11 @@ class LangFuseDataTrace(BaseTraceInstance):
         # 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}")
+        app_id = trace_info.metadata.get("app_id")
+        if not app_id:
+            raise ValueError("No app_id found in trace_info metadata")
+
+        service_account = self.get_service_account_with_tenant(app_id)
 
         workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
             session_factory=session_factory,

api/core/ops/langsmith_trace/langsmith_trace.py

@@ -6,7 +6,7 @@ from typing import Optional, cast
 
 from langsmith import Client
 from langsmith.schemas import RunBase
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import sessionmaker
 
 from core.ops.base_trace_instance import BaseTraceInstance
 from core.ops.entities.config_entity import LangSmithConfig
@@ -28,10 +28,10 @@ from core.ops.langsmith_trace.entities.langsmith_trace_entity import (
 )
 from core.ops.utils import filter_none_values, generate_dotted_order
 from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
-from core.workflow.entities.node_entities import NodeRunMetadataKey
+from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey
 from core.workflow.nodes.enums import NodeType
 from extensions.ext_database import db
-from models import Account, App, EndUser, MessageFile, WorkflowNodeExecutionTriggeredFrom
+from models import EndUser, MessageFile, WorkflowNodeExecutionTriggeredFrom
 
 logger = logging.getLogger(__name__)
 
@@ -139,22 +139,11 @@ class LangSmithDataTrace(BaseTraceInstance):
         # 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_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}")
+        service_account = self.get_service_account_with_tenant(app_id)
 
         workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
             session_factory=session_factory,
@@ -185,7 +174,7 @@ class LangSmithDataTrace(BaseTraceInstance):
             finished_at = created_at + timedelta(seconds=elapsed_time)
 
             execution_metadata = node_execution.metadata if node_execution.metadata else {}
-            node_total_tokens = execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS) or 0
+            node_total_tokens = execution_metadata.get(WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS) or 0
             metadata = {str(key): value for key, value in execution_metadata.items()}
             metadata.update(
                 {

api/core/ops/opik_trace/opik_trace.py

@@ -6,7 +6,7 @@ from typing import Optional, cast
 
 from opik import Opik, Trace
 from opik.id_helpers import uuid4_to_uuid7
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import sessionmaker
 
 from core.ops.base_trace_instance import BaseTraceInstance
 from core.ops.entities.config_entity import OpikConfig
@@ -22,10 +22,10 @@ from core.ops.entities.trace_entity import (
     WorkflowTraceInfo,
 )
 from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
-from core.workflow.entities.node_entities import NodeRunMetadataKey
+from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey
 from core.workflow.nodes.enums import NodeType
 from extensions.ext_database import db
-from models import Account, App, EndUser, MessageFile, WorkflowNodeExecutionTriggeredFrom
+from models import EndUser, MessageFile, WorkflowNodeExecutionTriggeredFrom
 
 logger = logging.getLogger(__name__)
 
@@ -115,6 +115,7 @@ class OpikDataTrace(BaseTraceInstance):
                 "metadata": workflow_metadata,
                 "input": wrap_dict("input", trace_info.workflow_run_inputs),
                 "output": wrap_dict("output", trace_info.workflow_run_outputs),
+                "thread_id": trace_info.conversation_id,
                 "tags": ["message", "workflow"],
                 "project_name": self.project,
             }
@@ -144,6 +145,7 @@ class OpikDataTrace(BaseTraceInstance):
                 "metadata": workflow_metadata,
                 "input": wrap_dict("input", trace_info.workflow_run_inputs),
                 "output": wrap_dict("output", trace_info.workflow_run_outputs),
+                "thread_id": trace_info.conversation_id,
                 "tags": ["workflow"],
                 "project_name": self.project,
             }
@@ -152,22 +154,11 @@ class OpikDataTrace(BaseTraceInstance):
         # 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_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}")
+        service_account = self.get_service_account_with_tenant(app_id)
 
         workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
             session_factory=session_factory,
@@ -244,7 +235,7 @@ class OpikDataTrace(BaseTraceInstance):
             parent_span_id = trace_info.workflow_app_log_id or trace_info.workflow_run_id
 
             if not total_tokens:
-                total_tokens = execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS) or 0
+                total_tokens = execution_metadata.get(WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS) or 0
 
             span_data = {
                 "trace_id": opik_trace_id,
@@ -306,6 +297,7 @@ class OpikDataTrace(BaseTraceInstance):
             "metadata": wrap_metadata(metadata),
             "input": trace_info.inputs,
             "output": message_data.answer,
+            "thread_id": message_data.conversation_id,
             "tags": ["message", str(trace_info.conversation_mode)],
             "project_name": self.project,
         }
@@ -420,6 +412,7 @@ class OpikDataTrace(BaseTraceInstance):
             "metadata": wrap_metadata(trace_info.metadata),
             "input": trace_info.inputs,
             "output": trace_info.outputs,
+            "thread_id": trace_info.conversation_id,
             "tags": ["generate_name"],
             "project_name": self.project,
         }

api/core/ops/ops_trace_manager.py

@@ -30,6 +30,7 @@ from core.ops.entities.trace_entity import (
     WorkflowTraceInfo,
 )
 from core.ops.utils import get_message_data
+from core.workflow.entities.workflow_execution import WorkflowExecution
 from extensions.ext_database import db
 from extensions.ext_storage import storage
 from models.model import App, AppModelConfig, Conversation, Message, MessageFile, TraceAppConfig
@@ -234,7 +235,11 @@ class OpsTraceManager:
             return None
 
         tracing_provider = app_ops_trace_config.get("tracing_provider")
-        if tracing_provider is None or tracing_provider not in provider_config_map:
+        if tracing_provider is None:
+            return None
+        try:
+            provider_config_map[tracing_provider]
+        except KeyError:
             return None
 
         # decrypt_token
@@ -287,10 +292,14 @@ class OpsTraceManager:
         :return:
         """
         # auth check
-        try:
-            provider_config_map[tracing_provider]
-        except KeyError:
-            raise ValueError(f"Invalid tracing provider: {tracing_provider}")
+        if enabled == True:
+            try:
+                provider_config_map[tracing_provider]
+            except KeyError:
+                raise ValueError(f"Invalid tracing provider: {tracing_provider}")
+        else:
+            if tracing_provider is not None:
+                raise ValueError(f"Invalid tracing provider: {tracing_provider}")
 
         app_config: Optional[App] = db.session.query(App).filter(App.id == app_id).first()
         if not app_config:
@@ -369,7 +378,7 @@ class TraceTask:
         self,
         trace_type: Any,
         message_id: Optional[str] = None,
-        workflow_run: Optional[WorkflowRun] = None,
+        workflow_execution: Optional[WorkflowExecution] = None,
         conversation_id: Optional[str] = None,
         user_id: Optional[str] = None,
         timer: Optional[Any] = None,
@@ -377,7 +386,7 @@ class TraceTask:
     ):
         self.trace_type = trace_type
         self.message_id = message_id
-        self.workflow_run_id = workflow_run.id if workflow_run else None
+        self.workflow_run_id = workflow_execution.id_ if workflow_execution else None
         self.conversation_id = conversation_id
         self.user_id = user_id
         self.timer = timer
@@ -478,6 +487,7 @@ class TraceTask:
                 "file_list": file_list,
                 "triggered_from": workflow_run.triggered_from,
                 "user_id": user_id,
+                "app_id": workflow_run.app_id,
             }
 
             workflow_trace_info = WorkflowTraceInfo(

api/core/ops/weave_trace/weave_trace.py

@@ -6,7 +6,7 @@ from typing import Any, Optional, cast
 
 import wandb
 import weave
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import sessionmaker
 
 from core.ops.base_trace_instance import BaseTraceInstance
 from core.ops.entities.config_entity import WeaveConfig
@@ -23,10 +23,10 @@ from core.ops.entities.trace_entity import (
 )
 from core.ops.weave_trace.entities.weave_trace_entity import WeaveTraceModel
 from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
-from core.workflow.entities.node_entities import NodeRunMetadataKey
+from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey
 from core.workflow.nodes.enums import NodeType
 from extensions.ext_database import db
-from models import Account, App, EndUser, MessageFile, WorkflowNodeExecutionTriggeredFrom
+from models import EndUser, MessageFile, WorkflowNodeExecutionTriggeredFrom
 
 logger = logging.getLogger(__name__)
 
@@ -133,22 +133,11 @@ class WeaveDataTrace(BaseTraceInstance):
         # 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_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}")
+        service_account = self.get_service_account_with_tenant(app_id)
 
         workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
             session_factory=session_factory,
@@ -179,7 +168,7 @@ class WeaveDataTrace(BaseTraceInstance):
             finished_at = created_at + timedelta(seconds=elapsed_time)
 
             execution_metadata = node_execution.metadata if node_execution.metadata else {}
-            node_total_tokens = execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS) or 0
+            node_total_tokens = execution_metadata.get(WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS) or 0
             attributes = {str(k): v for k, v in execution_metadata.items()}
             attributes.update(
                 {

api/core/plugin/backwards_invocation/model.py

@@ -58,6 +58,7 @@ class PluginModelBackwardsInvocation(BaseBackwardsInvocation):
                         LLMNode.deduct_llm_quota(
                             tenant_id=tenant.id, model_instance=model_instance, usage=chunk.delta.usage
                         )
+                    chunk.prompt_messages = []
                     yield chunk
 
             return handle()
@@ -68,7 +69,7 @@ class PluginModelBackwardsInvocation(BaseBackwardsInvocation):
             def handle_non_streaming(response: LLMResult) -> Generator[LLMResultChunk, None, None]:
                 yield LLMResultChunk(
                     model=response.model,
-                    prompt_messages=response.prompt_messages,
+                    prompt_messages=[],
                     system_fingerprint=response.system_fingerprint,
                     delta=LLMResultChunkDelta(
                         index=0,

api/core/plugin/entities/plugin_daemon.py

@@ -9,7 +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.plugin import PluginDeclaration
+from core.plugin.entities.plugin import PluginDeclaration, PluginEntity
 from core.tools.entities.common_entities import I18nObject
 from core.tools.entities.tool_entities import ToolProviderEntityWithPlugin
 
@@ -167,3 +167,8 @@ class PluginOAuthAuthorizationUrlResponse(BaseModel):
 
 class PluginOAuthCredentialsResponse(BaseModel):
     credentials: Mapping[str, Any] = Field(description="The credentials of the OAuth.")
+
+
+class PluginListResponse(BaseModel):
+    list: list[PluginEntity]
+    total: int

api/core/plugin/impl/base.py

@@ -6,6 +6,7 @@ from typing import TypeVar
 
 import requests
 from pydantic import BaseModel
+from requests.exceptions import HTTPError
 from yarl import URL
 
 from configs import dify_config
@@ -30,8 +31,7 @@ from core.plugin.impl.exc import (
     PluginUniqueIdentifierError,
 )
 
-plugin_daemon_inner_api_baseurl = dify_config.PLUGIN_DAEMON_URL
-plugin_daemon_inner_api_key = dify_config.PLUGIN_DAEMON_KEY
+plugin_daemon_inner_api_baseurl = URL(str(dify_config.PLUGIN_DAEMON_URL))
 
 T = TypeVar("T", bound=(BaseModel | dict | list | bool | str))
 
@@ -52,9 +52,9 @@ class BasePluginClient:
         """
         Make a request to the plugin daemon inner API.
         """
-        url = URL(str(plugin_daemon_inner_api_baseurl)) / path
+        url = plugin_daemon_inner_api_baseurl / path
         headers = headers or {}
-        headers["X-Api-Key"] = plugin_daemon_inner_api_key
+        headers["X-Api-Key"] = dify_config.PLUGIN_DAEMON_KEY
         headers["Accept-Encoding"] = "gzip, deflate, br"
 
         if headers.get("Content-Type") == "application/json" and isinstance(data, dict):
@@ -136,12 +136,31 @@ class BasePluginClient:
         """
         Make a request to the plugin daemon inner API and return the response as a model.
         """
-        response = self._request(method, path, headers, data, params, files)
-        json_response = response.json()
-        if transformer:
-            json_response = transformer(json_response)
+        try:
+            response = self._request(method, path, headers, data, params, files)
+            response.raise_for_status()
+        except HTTPError as e:
+            msg = f"Failed to request plugin daemon, status: {e.response.status_code}, url: {path}"
+            logging.exception(msg)
+            raise e
+        except Exception as e:
+            msg = f"Failed to request plugin daemon, url: {path}"
+            logging.exception(msg)
+            raise ValueError(msg) from e
+
+        try:
+            json_response = response.json()
+            if transformer:
+                json_response = transformer(json_response)
+            rep = PluginDaemonBasicResponse[type](**json_response)  # type: ignore
+        except Exception:
+            msg = (
+                f"Failed to parse response from plugin daemon to PluginDaemonBasicResponse [{str(type.__name__)}],"
+                f" url: {path}"
+            )
+            logging.exception(msg)
+            raise ValueError(msg)
 
-        rep = PluginDaemonBasicResponse[type](**json_response)  # type: ignore
         if rep.code != 0:
             try:
                 error = PluginDaemonError(**json.loads(rep.message))

api/core/plugin/impl/plugin.py

@@ -9,7 +9,12 @@ from core.plugin.entities.plugin import (
     PluginInstallation,
     PluginInstallationSource,
 )
-from core.plugin.entities.plugin_daemon import PluginInstallTask, PluginInstallTaskStartResponse, PluginUploadResponse
+from core.plugin.entities.plugin_daemon import (
+    PluginInstallTask,
+    PluginInstallTaskStartResponse,
+    PluginListResponse,
+    PluginUploadResponse,
+)
 from core.plugin.impl.base import BasePluginClient
 
 
@@ -27,12 +32,21 @@ class PluginInstaller(BasePluginClient):
         )
 
     def list_plugins(self, tenant_id: str) -> list[PluginEntity]:
-        return self._request_with_plugin_daemon_response(
+        result = self._request_with_plugin_daemon_response(
             "GET",
             f"plugin/{tenant_id}/management/list",
-            list[PluginEntity],
+            PluginListResponse,
             params={"page": 1, "page_size": 256},
         )
+        return result.list
+
+    def list_plugins_with_total(self, tenant_id: str, page: int, page_size: int) -> PluginListResponse:
+        return self._request_with_plugin_daemon_response(
+            "GET",
+            f"plugin/{tenant_id}/management/list",
+            PluginListResponse,
+            params={"page": page, "page_size": page_size},
+        )
 
     def upload_pkg(
         self,

api/core/provider_manager.py

@@ -3,7 +3,9 @@ from collections import defaultdict
 from json import JSONDecodeError
 from typing import Any, Optional, cast
 
+from sqlalchemy import select
 from sqlalchemy.exc import IntegrityError
+from sqlalchemy.orm import Session
 
 from configs import dify_config
 from core.entities.model_entities import DefaultModelEntity, DefaultModelProviderEntity
@@ -393,19 +395,13 @@ class ProviderManager:
 
     @staticmethod
     def _get_all_providers(tenant_id: str) -> dict[str, list[Provider]]:
-        """
-        Get all provider records of the workspace.
-
-        :param tenant_id: workspace id
-        :return:
-        """
-        providers = db.session.query(Provider).filter(Provider.tenant_id == tenant_id, Provider.is_valid == True).all()
-
         provider_name_to_provider_records_dict = defaultdict(list)
-        for provider in providers:
-            # TODO: Use provider name with prefix after the data migration
-            provider_name_to_provider_records_dict[str(ModelProviderID(provider.provider_name))].append(provider)
-
+        with Session(db.engine, expire_on_commit=False) as session:
+            stmt = select(Provider).where(Provider.tenant_id == tenant_id, Provider.is_valid == True)
+            providers = session.scalars(stmt)
+            for provider in providers:
+                # Use provider name with prefix after the data migration
+                provider_name_to_provider_records_dict[str(ModelProviderID(provider.provider_name))].append(provider)
         return provider_name_to_provider_records_dict
 
     @staticmethod
@@ -416,17 +412,12 @@ class ProviderManager:
         :param tenant_id: workspace id
         :return:
         """
-        # Get all provider model records of the workspace
-        provider_models = (
-            db.session.query(ProviderModel)
-            .filter(ProviderModel.tenant_id == tenant_id, ProviderModel.is_valid == True)
-            .all()
-        )
-
         provider_name_to_provider_model_records_dict = defaultdict(list)
-        for provider_model in provider_models:
-            provider_name_to_provider_model_records_dict[provider_model.provider_name].append(provider_model)
-
+        with Session(db.engine, expire_on_commit=False) as session:
+            stmt = select(ProviderModel).where(ProviderModel.tenant_id == tenant_id, ProviderModel.is_valid == True)
+            provider_models = session.scalars(stmt)
+            for provider_model in provider_models:
+                provider_name_to_provider_model_records_dict[provider_model.provider_name].append(provider_model)
         return provider_name_to_provider_model_records_dict
 
     @staticmethod
@@ -437,17 +428,14 @@ class ProviderManager:
         :param tenant_id: workspace id
         :return:
         """
-        preferred_provider_types = (
-            db.session.query(TenantPreferredModelProvider)
-            .filter(TenantPreferredModelProvider.tenant_id == tenant_id)
-            .all()
-        )
-
-        provider_name_to_preferred_provider_type_records_dict = {
-            preferred_provider_type.provider_name: preferred_provider_type
-            for preferred_provider_type in preferred_provider_types
-        }
-
+        provider_name_to_preferred_provider_type_records_dict = {}
+        with Session(db.engine, expire_on_commit=False) as session:
+            stmt = select(TenantPreferredModelProvider).where(TenantPreferredModelProvider.tenant_id == tenant_id)
+            preferred_provider_types = session.scalars(stmt)
+            provider_name_to_preferred_provider_type_records_dict = {
+                preferred_provider_type.provider_name: preferred_provider_type
+                for preferred_provider_type in preferred_provider_types
+            }
         return provider_name_to_preferred_provider_type_records_dict
 
     @staticmethod
@@ -458,18 +446,14 @@ class ProviderManager:
         :param tenant_id: workspace id
         :return:
         """
-        provider_model_settings = (
-            db.session.query(ProviderModelSetting).filter(ProviderModelSetting.tenant_id == tenant_id).all()
-        )
-
         provider_name_to_provider_model_settings_dict = defaultdict(list)
-        for provider_model_setting in provider_model_settings:
-            (
+        with Session(db.engine, expire_on_commit=False) as session:
+            stmt = select(ProviderModelSetting).where(ProviderModelSetting.tenant_id == tenant_id)
+            provider_model_settings = session.scalars(stmt)
+            for provider_model_setting in provider_model_settings:
                 provider_name_to_provider_model_settings_dict[provider_model_setting.provider_name].append(
                     provider_model_setting
                 )
-            )
-
         return provider_name_to_provider_model_settings_dict
 
     @staticmethod
@@ -492,15 +476,14 @@ class ProviderManager:
         if not model_load_balancing_enabled:
             return {}
 
-        provider_load_balancing_configs = (
-            db.session.query(LoadBalancingModelConfig).filter(LoadBalancingModelConfig.tenant_id == tenant_id).all()
-        )
-
         provider_name_to_provider_load_balancing_model_configs_dict = defaultdict(list)
-        for provider_load_balancing_config in provider_load_balancing_configs:
-            provider_name_to_provider_load_balancing_model_configs_dict[
-                provider_load_balancing_config.provider_name
-            ].append(provider_load_balancing_config)
+        with Session(db.engine, expire_on_commit=False) as session:
+            stmt = select(LoadBalancingModelConfig).where(LoadBalancingModelConfig.tenant_id == tenant_id)
+            provider_load_balancing_configs = session.scalars(stmt)
+            for provider_load_balancing_config in provider_load_balancing_configs:
+                provider_name_to_provider_load_balancing_model_configs_dict[
+                    provider_load_balancing_config.provider_name
+                ].append(provider_load_balancing_config)
 
         return provider_name_to_provider_load_balancing_model_configs_dict
 
@@ -626,10 +609,9 @@ class ProviderManager:
             if not cached_provider_credentials:
                 try:
                     # fix origin data
-                    if (
-                        custom_provider_record.encrypted_config
-                        and not custom_provider_record.encrypted_config.startswith("{")
-                    ):
+                    if custom_provider_record.encrypted_config is None:
+                        raise ValueError("No credentials found")
+                    if not custom_provider_record.encrypted_config.startswith("{"):
                         provider_credentials = {"openai_api_key": custom_provider_record.encrypted_config}
                     else:
                         provider_credentials = json.loads(custom_provider_record.encrypted_config)
@@ -733,7 +715,7 @@ class ProviderManager:
             return SystemConfiguration(enabled=False)
 
         # Convert provider_records to dict
-        quota_type_to_provider_records_dict = {}
+        quota_type_to_provider_records_dict: dict[ProviderQuotaType, Provider] = {}
         for provider_record in provider_records:
             if provider_record.provider_type != ProviderType.SYSTEM.value:
                 continue
@@ -758,6 +740,11 @@ class ProviderManager:
             else:
                 provider_record = quota_type_to_provider_records_dict[provider_quota.quota_type]
 
+                if provider_record.quota_used is None:
+                    raise ValueError("quota_used is None")
+                if provider_record.quota_limit is None:
+                    raise ValueError("quota_limit is None")
+
                 quota_configuration = QuotaConfiguration(
                     quota_type=provider_quota.quota_type,
                     quota_unit=provider_hosting_configuration.quota_unit or QuotaUnit.TOKENS,
@@ -791,10 +778,9 @@ class ProviderManager:
                 cached_provider_credentials = provider_credentials_cache.get()
 
                 if not cached_provider_credentials:
-                    try:
-                        provider_credentials: dict[str, Any] = json.loads(provider_record.encrypted_config)
-                    except JSONDecodeError:
-                        provider_credentials = {}
+                    provider_credentials: dict[str, Any] = {}
+                    if provider_records and provider_records[0].encrypted_config:
+                        provider_credentials = json.loads(provider_records[0].encrypted_config)
 
                     # Get provider credential secret variables
                     provider_credential_secret_variables = self._extract_secret_variables(

api/core/rag/datasource/keyword/jieba/stopwords.py

@@ -720,7 +720,7 @@ STOPWORDS = {
     "〉",
     "〈",
     "…",
-    "　",
+    " ",
     "0",
     "1",
     "2",
@@ -731,16 +731,6 @@ STOPWORDS = {
     "7",
     "8",
     "9",
-    "０",
-    "１",
-    "２",
-    "３",
-    "４",
-    "５",
-    "６",
-    "７",
-    "８",
-    "９",
     "二",
     "三",
     "四",

api/core/rag/datasource/retrieval_service.py

@@ -405,7 +405,29 @@ class RetrievalService:
                     record["child_chunks"] = segment_child_map[record["segment"].id].get("child_chunks")  # type: ignore
                     record["score"] = segment_child_map[record["segment"].id]["max_score"]
 
-            return [RetrievalSegments(**record) for record in records]
+            result = []
+            for record in records:
+                # Extract segment
+                segment = record["segment"]
+
+                # Extract child_chunks, ensuring it's a list or None
+                child_chunks = record.get("child_chunks")
+                if not isinstance(child_chunks, list):
+                    child_chunks = None
+
+                # Extract score, ensuring it's a float or None
+                score_value = record.get("score")
+                score = (
+                    float(score_value)
+                    if score_value is not None and isinstance(score_value, int | float | str)
+                    else None
+                )
+
+                # Create RetrievalSegments object
+                retrieval_segment = RetrievalSegments(segment=segment, child_chunks=child_chunks, score=score)
+                result.append(retrieval_segment)
+
+            return result
         except Exception as e:
             db.session.rollback()
             raise e

api/core/rag/datasource/vdb/baidu/baidu_vector.py

@@ -85,7 +85,6 @@ class BaiduVector(BaseVector):
             end = min(start + batch_size, total_count)
             rows = []
             assert len(metadatas) == total_count, "metadatas length should be equal to total_count"
-            # FIXME do you need this assert?
             for i in range(start, end, 1):
                 row = Row(
                     id=metadatas[i].get("doc_id", str(uuid.uuid4())),

api/core/rag/datasource/vdb/elasticsearch/elasticsearch_vector.py

@@ -142,7 +142,7 @@ class ElasticSearchVector(BaseVector):
             if score > score_threshold:
                 if doc.metadata is not None:
                     doc.metadata["score"] = score
-            docs.append(doc)
+                    docs.append(doc)
 
         return docs
 

api/core/rag/datasource/vdb/milvus/milvus_vector.py

@@ -97,6 +97,10 @@ class MilvusVector(BaseVector):
 
         try:
             milvus_version = self._client.get_server_version()
+            # Check if it's Zilliz Cloud - it supports full-text search with Milvus 2.5 compatibility
+            if "Zilliz Cloud" in milvus_version:
+                return True
+            # For standard Milvus installations, check version number
             return version.parse(milvus_version).base_version >= version.parse("2.5.0").base_version
         except Exception as e:
             logger.warning(f"Failed to check Milvus version: {str(e)}. Disabling hybrid search.")

api/core/rag/datasource/vdb/opensearch/opensearch_vector.py

@@ -23,7 +23,8 @@ logger = logging.getLogger(__name__)
 class OpenSearchConfig(BaseModel):
     host: str
     port: int
-    secure: bool = False
+    secure: bool = False  # use_ssl
+    verify_certs: bool = True
     auth_method: Literal["basic", "aws_managed_iam"] = "basic"
     user: Optional[str] = None
     password: Optional[str] = None
@@ -42,6 +43,8 @@ class OpenSearchConfig(BaseModel):
                 raise ValueError("config OPENSEARCH_AWS_REGION is required for AWS_MANAGED_IAM auth method")
             if not values.get("aws_service"):
                 raise ValueError("config OPENSEARCH_AWS_SERVICE is required for AWS_MANAGED_IAM auth method")
+        if not values.get("OPENSEARCH_SECURE") and values.get("OPENSEARCH_VERIFY_CERTS"):
+            raise ValueError("verify_certs=True requires secure (HTTPS) connection")
         return values
 
     def create_aws_managed_iam_auth(self) -> Urllib3AWSV4SignerAuth:
@@ -57,7 +60,7 @@ class OpenSearchConfig(BaseModel):
         params = {
             "hosts": [{"host": self.host, "port": self.port}],
             "use_ssl": self.secure,
-            "verify_certs": self.secure,
+            "verify_certs": self.verify_certs,
             "connection_class": Urllib3HttpConnection,
             "pool_maxsize": 20,
         }
@@ -279,6 +282,7 @@ class OpenSearchVectorFactory(AbstractVectorFactory):
             host=dify_config.OPENSEARCH_HOST or "localhost",
             port=dify_config.OPENSEARCH_PORT,
             secure=dify_config.OPENSEARCH_SECURE,
+            verify_certs=dify_config.OPENSEARCH_VERIFY_CERTS,
             auth_method=dify_config.OPENSEARCH_AUTH_METHOD.value,
             user=dify_config.OPENSEARCH_USER,
             password=dify_config.OPENSEARCH_PASSWORD,

api/core/rag/datasource/vdb/oracle/oraclevector.py

@@ -261,7 +261,7 @@ class OracleVector(BaseVector):
                 words = pseg.cut(query)
                 current_entity = ""
                 for word, pos in words:
-                    if pos in {"nr", "Ng", "eng", "nz", "n", "ORG", "v"}:  # nr: 人名, ns: 地名, nt: 机构名
+                    if pos in {"nr", "Ng", "eng", "nz", "n", "ORG", "v"}:  # nr: 人名，ns: 地名，nt: 机构名
                         current_entity += word
                     else:
                         if current_entity:

api/core/rag/datasource/vdb/qdrant/qdrant_vector.py

@@ -46,6 +46,7 @@ class QdrantConfig(BaseModel):
     root_path: Optional[str] = None
     grpc_port: int = 6334
     prefer_grpc: bool = False
+    replication_factor: int = 1
 
     def to_qdrant_params(self):
         if self.endpoint and self.endpoint.startswith("path:"):
@@ -119,11 +120,13 @@ class QdrantVector(BaseVector):
                     max_indexing_threads=0,
                     on_disk=False,
                 )
+
                 self._client.create_collection(
                     collection_name=collection_name,
                     vectors_config=vectors_config,
                     hnsw_config=hnsw_config,
                     timeout=int(self._client_config.timeout),
+                    replication_factor=self._client_config.replication_factor,
                 )
 
                 # create group_id payload index
@@ -466,5 +469,6 @@ class QdrantVectorFactory(AbstractVectorFactory):
                 timeout=dify_config.QDRANT_CLIENT_TIMEOUT,
                 grpc_port=dify_config.QDRANT_GRPC_PORT,
                 prefer_grpc=dify_config.QDRANT_GRPC_ENABLED,
+                replication_factor=dify_config.QDRANT_REPLICATION_FACTOR,
             ),
         )

api/core/rag/datasource/vdb/tencent/tencent_vector.py

@@ -271,12 +271,15 @@ class TencentVector(BaseVector):
 
         for result in res[0]:
             meta = result.get(self.field_metadata)
+            if isinstance(meta, str):
+                # Compatible with version 1.1.3 and below.
+                meta = json.loads(meta)
+                score = 1 - result.get("score", 0.0)
             score = result.get("score", 0.0)
             if score > score_threshold:
                 meta["score"] = score
                 doc = Document(page_content=result.get(self.field_text), metadata=meta)
                 docs.append(doc)
-
         return docs
 
     def delete(self) -> None:

api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_on_qdrant_vector.py

@@ -49,6 +49,7 @@ class TidbOnQdrantConfig(BaseModel):
     root_path: Optional[str] = None
     grpc_port: int = 6334
     prefer_grpc: bool = False
+    replication_factor: int = 1
 
     def to_qdrant_params(self):
         if self.endpoint and self.endpoint.startswith("path:"):
@@ -134,6 +135,7 @@ class TidbOnQdrantVector(BaseVector):
                     vectors_config=vectors_config,
                     hnsw_config=hnsw_config,
                     timeout=int(self._client_config.timeout),
+                    replication_factor=self._client_config.replication_factor,
                 )
 
                 # create group_id payload index
@@ -484,6 +486,7 @@ class TidbOnQdrantVectorFactory(AbstractVectorFactory):
                 timeout=dify_config.TIDB_ON_QDRANT_CLIENT_TIMEOUT,
                 grpc_port=dify_config.TIDB_ON_QDRANT_GRPC_PORT,
                 prefer_grpc=dify_config.TIDB_ON_QDRANT_GRPC_ENABLED,
+                replication_factor=dify_config.QDRANT_REPLICATION_FACTOR,
             ),
         )
 

api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_service.py

@@ -245,4 +245,4 @@ class TidbService:
             return cluster_infos
         else:
             response.raise_for_status()
-            return []  # FIXME for mypy, This line will not be reached as raise_for_status() will raise an exception
+            return []

api/core/rag/entities/citation_metadata.py

@@ -0,0 +1,23 @@
+from typing import Any, Optional
+
+from pydantic import BaseModel
+
+
+class RetrievalSourceMetadata(BaseModel):
+    position: Optional[int] = None
+    dataset_id: Optional[str] = None
+    dataset_name: Optional[str] = None
+    document_id: Optional[str] = None
+    document_name: Optional[str] = None
+    data_source_type: Optional[str] = None
+    segment_id: Optional[str] = None
+    retriever_from: Optional[str] = None
+    score: Optional[float] = None
+    hit_count: Optional[int] = None
+    word_count: Optional[int] = None
+    segment_position: Optional[int] = None
+    index_node_hash: Optional[str] = None
+    content: Optional[str] = None
+    page: Optional[int] = None
+    doc_metadata: Optional[dict[str, Any]] = None
+    title: Optional[str] = None

api/core/rag/extractor/entity/extract_setting.py

@@ -27,6 +27,8 @@ class WebsiteInfo(BaseModel):
     website import info.
     """
 
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
     provider: str
     job_id: str
     url: str
@@ -34,12 +36,6 @@ class WebsiteInfo(BaseModel):
     tenant_id: str
     only_main_content: bool = False
 
-    class Config:
-        arbitrary_types_allowed = True
-
-    def __init__(self, **data) -> None:
-        super().__init__(**data)
-
 
 class ExtractSetting(BaseModel):
     """