117 lines
3.3 KiB
Markdown
117 lines
3.3 KiB
Markdown
# Dify Backend API
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## Usage
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> [!IMPORTANT]
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>
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> In the v1.3.0 release, `poetry` has been replaced with
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> [`uv`](https://docs.astral.sh/uv/) as the package manager
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> for Dify API backend service.
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1. Start the docker-compose stack
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The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using `docker-compose`.
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```bash
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cd ../docker
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cp middleware.env.example middleware.env
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# change the profile to mysql if you are not using postgres,change the profile to other vector database if you are not using weaviate
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docker compose -f docker-compose.middleware.yaml --profile postgresql --profile weaviate -p dify up -d
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cd ../api
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```
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1. Copy `.env.example` to `.env`
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```cli
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cp .env.example .env
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```
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> [!IMPORTANT]
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>
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> 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.
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1. Generate a `SECRET_KEY` in the `.env` file.
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bash for Linux
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```bash for Linux
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sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
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```
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bash for Mac
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```bash for Mac
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secret_key=$(openssl rand -base64 42)
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sed -i '' "/^SECRET_KEY=/c\\
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SECRET_KEY=${secret_key}" .env
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```
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1. Create environment.
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Dify API service uses [UV](https://docs.astral.sh/uv/) to manage dependencies.
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First, you need to add the uv package manager, if you don't have it already.
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```bash
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pip install uv
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# Or on macOS
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brew install uv
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```
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1. Install dependencies
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```bash
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uv sync --dev
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```
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1. Run migrate
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Before the first launch, migrate the database to the latest version.
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```bash
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uv run flask db upgrade
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```
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1. Start backend
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```bash
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uv run flask run --host 0.0.0.0 --port=5001 --debug
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```
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1. Start Dify [web](../web) service.
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1. Setup your application by visiting `http://localhost:3000`.
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1. If you need to handle and debug the async tasks (e.g. dataset importing and documents indexing), please start the worker service.
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```bash
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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
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```
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Additionally, if you want to debug the celery scheduled tasks, you can run the following command in another terminal to start the beat service:
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```bash
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uv run celery -A app.celery beat
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```
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## Testing
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1. Install dependencies for both the backend and the test environment
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```bash
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uv sync --dev
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```
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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)
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```bash
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uv run pytest # Run all tests
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uv run pytest tests/unit_tests/ # Unit tests only
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uv run pytest tests/integration_tests/ # Integration tests
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# Code quality
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../dev/reformat # Run all formatters and linters
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uv run ruff check --fix ./ # Fix linting issues
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uv run ruff format ./ # Format code
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uv run basedpyright . # Type checking
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```
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