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dify/api/README.md

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# Dify Backend API
## Usage
> [!IMPORTANT]
>
> In the v1.3.0 release, `poetry` has been replaced with
> [`uv`](https://docs.astral.sh/uv/) as the package manager
> for Dify API backend service.
1. Start the docker-compose stack
The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using `docker-compose`.
```bash
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
```
1. Copy `.env.example` to `.env`
```cli
cp .env.example .env
```
1. Generate a `SECRET_KEY` in the `.env` file.
bash for Linux
```bash for Linux
sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
```
bash for Mac
```bash for Mac
secret_key=$(openssl rand -base64 42)
sed -i '' "/^SECRET_KEY=/c\\
SECRET_KEY=${secret_key}" .env
```
1. Create environment.
Dify API service uses [UV](https://docs.astral.sh/uv/) to manage dependencies.
First, you need to add the uv package manager, if you don't have it already.
```bash
pip install uv
# Or on macOS
brew install uv
```
1. Install dependencies
```bash
uv sync --dev
```
1. Run migrate
Before the first launch, migrate the database to the latest version.
```bash
uv run flask db upgrade
```
1. Start backend
```bash
uv run flask run --host 0.0.0.0 --port=5001 --debug
```
1. Start Dify [web](../web) service.
1. Setup your application by visiting `http://localhost:3000`.
1. If you need to handle and debug the async tasks (e.g. dataset importing and documents indexing), please start the worker service.
```bash
uv run celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion,plugin,workflow_storage,conversation
```
Addition, if you want to debug the celery scheduled tasks, you can use the following command in another terminal:
```bash
uv run celery -A app.celery beat
```
## Testing
1. Install dependencies for both the backend and the test environment
```bash
uv sync --dev
```
1. Run the tests locally with mocked system environment variables in `tool.pytest_env` section in `pyproject.toml`, more can check [Claude.md](../CLAUDE.md)
```bash
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
```