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add embedding cache and clean embedding cache job (#3087)
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fields feat: add `introduction` field in log detail response of chat app (#2445) pirms 1 gada
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app.py feat: support HTTP response compression in api server (#2680) pirms 1 gada
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config.py version to 0.5.11-fix1 (#3073) pirms 1 gada
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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

3.5 If you use annaconda, 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
  2. Setup your application by visiting http://localhost:5001/console/api/setup or other apis…
  3. If you need to debug local async processing, you can run celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail, celery can do dataset importing and other async tasks.