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Bump release references to 1.9.1 (#26453)
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 рік тому
.vscode feat/enhance the multi-modal support (#8818) 1 рік тому
configs Chore/remove add node restrict of workflow (#26218) 1 місяць тому
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core Fix: Remove core/tools from pyrightconfig.json and fix type errors (#26413) 1 місяць тому
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README.md

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.

  1. 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 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
   cp .env.example .env
  1. 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
  1. 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
  1. Install dependencies
   uv sync --dev
  1. Run migrate

Before the first launch, migrate the database to the latest version.

   uv run flask db upgrade
  1. Start backend
   uv run flask run --host 0.0.0.0 --port=5001 --debug
  1. Start Dify web service.

  2. Setup your application by visiting http://localhost:3000.

  3. 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 gevent -c 2 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion,plugin,workflow_storage,conversation

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

  1. Install dependencies for both the backend and the test environment
   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
   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