dify/api
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configs feat: support openGauss vector database (#15865) 2025-03-17 19:42:54 +08:00
constants
contexts
controllers refactor: format query for dataset retrieval in DatasetChildChunkApi for improved readability 2025-03-18 19:07:25 +08:00
core Support knowledge metadata filter (#15982) 2025-03-18 16:42:19 +08:00
docker
events
extensions chore: update opendal version (#14343) 2025-03-11 20:44:09 +08:00
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schedule
services refactor: replace direct ChildChunk queries with SegmentService.get_child_chunk_by_id for improved code clarity and maintainability 2025-03-18 19:05:29 +08:00
tasks chore: bump ruff to 0.11.0 and fix linting violations (#15953) 2025-03-17 16:13:11 +08:00
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tests feat: support openGauss vector database (#15865) 2025-03-17 19:42:54 +08:00
.dockerignore
.env.example feat: support openGauss vector database (#15865) 2025-03-17 19:42:54 +08:00
.ruff.toml
app_factory.py
app.py
commands.py fix: error in migrate_annotation_vector_database when exec vdb-migrate (#15937) 2025-03-18 14:15:48 +08:00
dify_app.py
Dockerfile chore: remove useless doc and font (#15838) 2025-03-14 16:47:42 +08:00
mypy.ini
poetry.lock Support knowledge metadata filter (#15982) 2025-03-18 16:42:19 +08:00
poetry.toml
pyproject.toml chore: bump ruff to 0.11.0 and fix linting violations (#15953) 2025-03-17 16:13:11 +08:00
pytest.ini
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
    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 Poetry to manage dependencies. First, you need to add the poetry shell plugin, if you don't have it already, in order to run in a virtual environment. [Note: Poetry shell is no longer a native command so you need to install the poetry plugin beforehand]

    poetry self add poetry-plugin-shell
    

    Then, You can execute poetry shell to activate the environment.

  5. Install dependencies

    poetry env use 3.12
    poetry install
    
  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 -P api bash dev/pytest/pytest_all_tests.sh