dify/api
Jyong 9eba6ffdd4
Optimize csv and excel extract (#3155)
Co-authored-by: jyong <jyong@dify.ai>
2024-04-08 16:34:43 +08:00
..
.vscode chore: replace outdated config in vscode debug settings (#3106) 2024-04-05 17:49:09 +08:00
constants
controllers
core Optimize csv and excel extract (#3155) 2024-04-08 16:34:43 +08:00
docker
events
extensions add embedding cache and clean embedding cache job (#3087) 2024-04-02 20:46:24 +08:00
fields
libs
migrations add embedding cache and clean embedding cache job (#3087) 2024-04-02 20:46:24 +08:00
models add embedding cache and clean embedding cache job (#3087) 2024-04-02 20:46:24 +08:00
schedule
services
tasks
templates
tests
.dockerignore
.env.example
app.py
commands.py
config.py
Dockerfile
pyproject.toml
README.md fix typo in readme (#3096) 2024-04-03 20:29:02 +08:00
requirements.txt feat: claude3 tool call (#3111) 2024-04-05 16:35:59 +09:00

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 Anaconda, 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.