Files
dify/api
QuantumGhost 268da31332 fix(api): adding variable to variable pool recursively while loading draft variables. (#21478)
This PR fix the issue that `ObjectSegment` are not recursively added to the draft variable pool while loading draft variables from database. It also fixes an issue about loading variables with more than two elements in the its selector.

Enhances #19735.
Closes #21477.
2025-06-25 12:39:22 +08:00
..
2025-06-19 10:27:38 +08:00
2025-04-11 20:33:52 +08:00
2025-06-19 10:27:38 +08:00
2025-06-04 19:56:34 +08:00
2025-06-04 19:56:34 +08:00
2025-06-19 10:27:38 +08:00
2025-06-06 09:09:31 +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

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