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app.py 552f319b9d feat: support HTTP response compression in api server (#2680) vor 1 Jahr
commands.py 7753ba2d37 FEAT: NEW WORKFLOW ENGINE (#3160) vor 1 Jahr
config.py 9c01bcb3e5 feat: support setting database used in Milvus (#3003) vor 1 Jahr
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README.md

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.

   cd ../docker
   docker-compose -f docker-compose.middleware.yaml -p dify up -d
   cd ../api
  1. Copy .env.example to .env
  2. Generate a SECRET_KEY in the .env file.
   sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
  1. If you use Anaconda, create a new environment and activate it

    conda create --name dify python=3.10
    conda activate dify
    
    1. Install dependencies bash pip install -r requirements.txt
  2. Run migrate

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

   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
  1. 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.