dify/api
2024-03-29 13:45:55 +08:00
..
.vscode
constants
controllers
core optionally specify available bedrock model used in validation 2024-03-29 13:45:55 +08:00
docker
events
extensions
fields
libs some optimization for admin api key, create tenant and reset-encrypt-key-pair command (#3013) 2024-03-28 17:02:52 +08:00
migrations
models
schedule
services some optimization for admin api key, create tenant and reset-encrypt-key-pair command (#3013) 2024-03-28 17:02:52 +08:00
tasks
templates
tests generalize helper for loading module from source (#2862) 2024-03-28 11:37:26 +08:00
.dockerignore
.env.example
app.py
commands.py some optimization for admin api key, create tenant and reset-encrypt-key-pair command (#3013) 2024-03-28 17:02:52 +08:00
config.py
Dockerfile
pyproject.toml
README.md
requirements.txt bump celery from 5.2 to 5.3 (#2478) 2024-03-28 11:53:48 +08:00

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
    
  2. Copy .env.example to .env

  3. 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

    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
    
  3. Start backend:

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

  5. 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.