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.

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 mysql if you are not using postgres,change the profile to other vector database if you are not using weaviate
docker compose -f docker-compose.middleware.yaml --profile postgresql --profile weaviate -p dify up -d
cd ../api

Copy .env.example to .env
```
cp .env.example .env
```

Important

When the frontend and backend run on different subdomains, set COOKIE_DOMAIN to the site’s top-level domain (e.g., example.com). The frontend and backend must be under the same top-level domain in order to share authentication cookies.

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

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
```
Install dependencies
```
uv sync --dev
```
Run migrate

Before the first launch, migrate the database to the latest version.
```
uv run flask db upgrade
```

Start backend

uv run flask run --host 0.0.0.0 --port=5001 --debug

Start Dify web service.
Setup your application by visiting http://localhost:3000.
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 threads -c 2 --loglevel INFO -Q dataset,priority_dataset,priority_pipeline,pipeline,mail,ops_trace,app_deletion,plugin,workflow_storage,conversation,workflow,schedule_poller,schedule_executor,triggered_workflow_dispatcher,trigger_refresh_executor

Additionally, if you want to debug the celery scheduled tasks, you can run the following command in another terminal to start the beat service:

uv run celery -A app.celery beat

Testing

Install dependencies for both the backend and the test environment
```
uv sync --dev
```

Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml, more can check Claude.md

uv run pytest                           # Run all tests
uv run pytest tests/unit_tests/         # Unit tests only
uv run pytest tests/integration_tests/  # Integration tests

# Code quality
../dev/reformat               # Run all formatters and linters
uv run ruff check --fix ./    # Fix linting issues
uv run ruff format ./         # Format code
uv run basedpyright .         # Type checking

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Dify Backend API

Usage

Testing

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