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chore(dependency): bump gunicorn to 23.0 (#11560)
10 月之前
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 年之前
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README.md chore: update base image to Python 3.12 in Dockerfile (#10358) 11 月之前
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app_factory.py refactor: assembling the app features in modular way (#9129) 11 月之前
commands.py fix: some typos using typos (#11374) 11 月之前
dify_app.py refactor: assembling the app features in modular way (#9129) 11 月之前
poetry.lock chore(dependency): bump gunicorn to 23.0 (#11560) 10 月之前
poetry.toml build: initial support for poetry build tool (#4513) 1 年之前
pyproject.toml chore(dependency): bump gunicorn to 23.0 (#11560) 10 月之前
pytest.ini feat: Add support for TEI API key authentication (#11006) 11 月之前

README.md

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.

   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 Poetry to manage dependencies. You can execute poetry shell to activate the environment.

  1. Install dependencies
   poetry env use 3.12
   poetry install
  1. Run migrate

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

   poetry run python -m flask db upgrade
  1. Start backend
   poetry run python -m 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.
   poetry run python -m 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
   poetry install -C api --with dev
  1. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml
   poetry run -C api bash dev/pytest/pytest_all_tests.sh