dify/api/README.md

3.8 KiB

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 -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.

    Using pip can be found below.

  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
  1. Run migrate

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

    poetry run python -m flask db upgrade
    
  2. Start backend

    poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug
    
  3. Start Dify web service.

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

  5. If you need to debug local async processing, please start the worker service.

poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail

The started celery app handles the async tasks, e.g. dataset importing and documents indexing.

Testing

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

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

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

Usage with pip

[!NOTE]
In the next version, we will deprecate pip as the primary package management tool for dify api service, currently Poetry and pip coexist.

  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 -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
    
  4. Create environment.

    If you use Anaconda, create a new environment and activate it

    conda create --name dify python=3.10
    conda activate dify
    
  5. Install dependencies

    pip install -r requirements.txt
    
  6. Run migrate

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

    flask db upgrade
    
  7. Start backend:

    flask run --host 0.0.0.0 --port=5001 --debug
    
  8. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...

  9. If you need to debug local async processing, please start the worker service.

    celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail
    

    The started celery app handles the async tasks, e.g. dataset importing and documents indexing.