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Dify Backend API

Usage

Important

In the v0.6.12 release, we deprecated pip as the package management tool for Dify API Backend service and replaced it with poetry.

  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

  3. Generate a SECRET_KEY in the .env file.

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

  4. Create environment.

    Dify API service uses Poetry to manage dependencies. You can execute poetry shell to activate the environment.

  5. Install dependencies

    poetry env use 3.10
poetry install

    In case of contributors missing to update dependencies for pyproject.toml, you can perform the following shell instead.

    poetry shell                                               # activate current environment
poetry add $(cat requirements.txt)           # install dependencies of production and update pyproject.toml
poetry add $(cat requirements-dev.txt) --group dev    # install dependencies of development and update pyproject.toml

  6. Run migrate

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

    poetry run python -m flask db upgrade

  7. Start backend

    poetry run python -m 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.

poetry run python -m 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

    poetry install -C api --with dev

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

    poetry run -C api bash dev/pytest/pytest_all_tests.sh