dify/api
Charlie.Wei 5b24d7129e
Azure openai init (#1929)
Co-authored-by: luowei <glpat-EjySCyNjWiLqAED-YmwM>
Co-authored-by: crazywoola <427733928@qq.com>
Co-authored-by: crazywoola <100913391+crazywoola@users.noreply.github.com>
2024-01-09 19:17:47 +08:00
..
.vscode
constants
controllers prohibit enable and disable function when segment is not completed (#1954) 2024-01-05 18:18:38 +08:00
core Azure openai init (#1929) 2024-01-09 19:17:47 +08:00
docker improvement: introduce Super-Linter actions to check style for shell script, dockerfile and yaml files (#1966) 2024-01-09 10:31:52 +08:00
events
extensions
fields
libs
migrations
models
schedule
services
tasks prohibit enable and disable function when segment is not completed (#1954) 2024-01-05 18:18:38 +08:00
templates
tests Add Together.ai's OpenAI API-compatible inference endpoints (#1947) 2024-01-05 16:36:29 +08:00
.dockerignore
.env.example
app.py
commands.py
config.py bump version to 0.4.4 (#1962) 2024-01-06 03:08:05 +08:00
Dockerfile
README.md
requirements.txt

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.

    openssl rand -base64 42
    

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.