Files
dify/api
-LAN- 9704319e10 fix: use automatic transaction commit in provider update handler
The provider update handler was missing proper transaction handling,
causing quota deductions to be lost. This fix uses session.begin()
context manager for automatic commit/rollback, ensuring provider
quota updates are properly persisted.

Fixes #24356
2025-08-22 21:24:55 +08:00
..
2025-07-31 10:30:54 +08:00
2025-06-19 10:27:38 +08:00

Dify Backend API

Usage

Important

In the v1.3.0 release, poetry has been replaced with uv as the package manager for Dify API backend service.

  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
    cp middleware.env.example middleware.env
    # change the profile to other vector database if you are not using weaviate
    docker compose -f docker-compose.middleware.yaml --profile weaviate -p dify up -d
    cd ../api
    
  2. Copy .env.example to .env

    cp .env.example .env 
    
  3. Generate a SECRET_KEY in the .env file.

    bash for Linux

    sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
    

    bash for Mac

    secret_key=$(openssl rand -base64 42)
    sed -i '' "/^SECRET_KEY=/c\\
    SECRET_KEY=${secret_key}" .env
    
  4. Create environment.

    Dify API service uses UV to manage dependencies. First, you need to add the uv package manager, if you don't have it already.

    pip install uv
    # Or on macOS
    brew install uv
    
  5. Install dependencies

    uv sync --dev
    
  6. Run migrate

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

    uv run flask db upgrade
    
  7. Start backend

    uv run flask run --host 0.0.0.0 --port=5001 --debug
    
  8. Start Dify web service.

  9. Setup your application by visiting http://localhost:3000.

  10. If you need to handle and debug the async tasks (e.g. dataset importing and documents indexing), please start the worker service.

uv run celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion,plugin

Addition, if you want to debug the celery scheduled tasks, you can use the following command in another terminal:

uv run celery -A app.celery beat 

Testing

  1. Install dependencies for both the backend and the test environment

    uv sync --dev
    
  2. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml

    uv run -P api bash dev/pytest/pytest_all_tests.sh