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gcgj-dify-1.7.0/api
History
Matri dfe10e9dfe
fix: generate_more_like_this function issue (#722) 		3 years ago
..
constants Initial commit 3 years ago
controllers feat: dashboard add tps chart (#706) 3 years ago
core fix: generate_more_like_this function issue (#722) 3 years ago
docker feat: add queue to celery task (#688) 3 years ago
events Feat/milvus support (#671) 3 years ago
extensions feat: member invitation and activation (#535) 3 years ago
libs feat: optimize current time (#661) 3 years ago
migrations Feat: Q&A format segmentation support (#668) 3 years ago
models fix: not annotation error in log (#686) 3 years ago
services Feat/milvus support (#671) 3 years ago
tasks feat: add queue to celery task (#688) 3 years ago
tests Initial commit 3 years ago
.dockerignore Initial commit 3 years ago
.env.example feat: member invitation and activation (#535) 3 years ago
Dockerfile feat: add bash before entrypoint.sh in Dockerfile (#592) 3 years ago
README.md feat: add queue to celery task (#688) 3 years ago
app.py feat: universal chat in explore (#649) 3 years ago
commands.py add clean unused dataset command (#609) 3 years ago
config.py feat: bump version to 0.3.12 (#674) 3 years ago
requirements.txt feat: universal chat in explore (#649) 3 years ago

README.md

Dify Backend API

Usage

  1. Start the docker-compose stack

    The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using docker-compose.

    cd ../docker
docker-compose -f docker-compose.middleware.yaml up -d
cd ../api

  2. Copy .env.example to .env

  3. Generate a SECRET_KEY in the .env file.

    openssl rand -base64 42

3.5 If you use annaconda, create a new environment and activate it

conda create --name dify python=3.10
conda activate dify

  1. Install dependencies

    pip install -r requirements.txt

  2. Run migrate

    Before the first launch, migrate the database to the latest version.

    flask db upgrade

  3. Start backend:

    flask run --host 0.0.0.0 --port=5001 --debug

  4. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...

  5. If you need to debug local async processing, you can run celery -A app.celery worker -Q dataset,generation,mail, celery can do dataset importing and other async tasks.