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controllers 875249eb00 Feat/vector db pgvector (#3879) hai 11 meses
core d8926a2571 feat: hide node detail outputs in webapp & installed app in explore (#3954) hai 11 meses
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tasks f257f2c396 Knowledge optimization (#3755) hai 1 ano
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README.md d463b82aba test: add scripts for running tests on api module both locally and CI jobs (#3497) hai 1 ano
app.py 8bca908f15 refactor: config file (#3852) hai 1 ano
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config.py 875249eb00 Feat/vector db pgvector (#3879) hai 11 meses
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requirements.txt 875249eb00 Feat/vector db pgvector (#3879) hai 11 meses

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:

    flask run --host 0.0.0.0 --port=5001 --debug
    
    1. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...
    2. 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.

    Testing

    1. Install dependencies for both the backend and the test environment bash pip install -r requirements.txt -r requirements-dev.txt
  2. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml

    dev/pytest/pytest_all_tests.sh