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feat(agent_node): ensure that the enum-checking syntax is compatible with Python 3.11. (#20373)
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) il y a 1 an
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schedule chore: model.query change to db.session.query (#19551) il y a 5 mois
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app_factory.py feat: add debug log for request and response (#19781) (#19783) il y a 5 mois
commands.py chore: model.query change to db.session.query (#19551) il y a 5 mois
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pyproject.toml feat(agent_node): ensure that the enum-checking syntax is compatible with Python 3.11. (#20373) il y a 5 mois
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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 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion

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
   uv run -P api bash dev/pytest/pytest_all_tests.sh