dify/api/README.md

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# 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`.
```bash
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.
```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](https://python-poetry.org/docs/) to manage dependencies. You can execute `poetry shell` to activate the environment.
5. Install dependencies
```bash
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.
```bash
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
```
6. Run migrate
Before the first launch, migrate the database to the latest version.
```bash
poetry run python -m flask db upgrade
```
7. Start backend
```bash
poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug
```
8. Start Dify [web](../web) service.
9. Setup your application by visiting `http://localhost:3000`...
10. If you need to debug local async processing, please start the worker service.
```bash
poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion
```
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
```bash
poetry install --with dev
```
2. Run the tests locally with mocked system environment variables in `tool.pytest_env` section in `pyproject.toml`
```bash
cd ../
poetry run -C api bash dev/pytest/pytest_all_tests.sh
```