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# Dify Backend API
## Usage
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
sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
```
4. If you use Anaconda, create a new environment and activate it
```bash
conda create --name dify python=3.10
conda activate dify
```
5. Install dependencies
```bash
pip install -r requirements.txt
```
6. Run migrate
Before the first launch, migrate the database to the latest version.
```bash
flask db upgrade
```
⚠️ If you encounter problems with jieba, for example
```
> flask db upgrade
Error: While importing 'app', an ImportError was raised:
```
Please run the following command instead.
```
pip install -r requirements.txt --upgrade --force-reinstall
```
7. Start backend:
```bash
flask run --host 0.0.0.0 --port=5001 --debug
```
8. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...
9. If you need to debug local async processing, please start the worker service by running
`celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail`.
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
pip install -r requirements.txt -r requirements-dev.txt
```
2. Run the tests locally with mocked system environment variables in `tool.pytest_env` section in `pyproject.toml`
```bash
dev/pytest/pytest_all_tests.sh
```
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