William Espegren f9e4b4e74c Fix docker command (#5681) 9 months ago
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configs 17d2f0bb0d fix(api/configs): Ignore empty environment variables when loading config. (#5647) 9 months ago
constants 2e718b85e9 fix(api): language list (#5649) 9 months ago
controllers 4c0a31d38b FR: #4048 - Add color customization to the chatbot (#4885) 9 months ago
core 2b080b5cfc feature: Add presence_penalty and frequency_penalty parameters to the … (#5637) 9 months ago
docker e8b8f6c6dd Feat/fix ops trace (#5672) 9 months ago
events d160d1ed02 feat: support opensearch approximate k-NN (#5322) 10 months ago
extensions 3cc6093e4b feat: introduce pydantic-settings for config definition and validation (#5202) 10 months ago
fields 4c0a31d38b FR: #4048 - Add color customization to the chatbot (#4885) 9 months ago
libs dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) 9 months ago
migrations e8b8f6c6dd Feat/fix ops trace (#5672) 9 months ago
models e8b8f6c6dd Feat/fix ops trace (#5672) 9 months ago
schedule 6c4e6bf1d6 Feat/dify rag (#2528) 1 year ago
services dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) 9 months ago
tasks e8b8f6c6dd Feat/fix ops trace (#5672) 9 months ago
templates 3d92784bd4 fix: email template style (#1914) 1 year ago
tests dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) 9 months ago
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 9 months ago
.env.example 964f0e1400 fix: Modify the incorrect configuration name for Google storage (#5595) 9 months ago
Dockerfile ea29007bc0 fix: apply best practices for the latest buildkit (#5527) 9 months ago
README.md f9e4b4e74c Fix docker command (#5681) 9 months ago
app.py e8b8f6c6dd Feat/fix ops trace (#5672) 9 months ago
commands.py d160d1ed02 feat: support opensearch approximate k-NN (#5322) 10 months ago
poetry.lock 2a13ef9ae0 chore: rearrange python dependencies in groups (#5603) 9 months ago
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 months ago
pyproject.toml 2a13ef9ae0 chore: rearrange python dependencies in groups (#5603) 9 months ago

README.md

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
   docker compose -f docker-compose.middleware.yaml -p dify up -d
   cd ../api
  1. Copy .env.example to .env
  2. 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
    
  3. Create environment.

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

  1. 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
  1. Start backend

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

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

  4. 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,ops_trace
    

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