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gcgj-dify-1.7.0/api
History
John Wang e9810a6df2
fix: azure openai embedding model name error (#612) 		3 years ago
..
constants Initial commit 3 years ago
controllers Feat/clean vector dataset (#605) 3 years ago
core fix: azure openai embedding model name error (#612) 3 years ago
docker Initial commit 3 years ago
events feat: claude api support (#572) 3 years ago
extensions feat: member invitation and activation (#535) 3 years ago
libs Feature/use jwt in web (#533) 3 years ago
migrations Feat/chat support voice input (#532) 3 years ago
models feat: member invitation and activation (#535) 3 years ago
services feat: claude api support (#572) 3 years ago
tasks index add to db when dataset updated (#588) 3 years ago
tests Initial commit 3 years ago
.dockerignore Initial commit 3 years ago
.env.example feat: member invitation and activation (#535) 3 years ago
Dockerfile feat: add bash before entrypoint.sh in Dockerfile (#592) 3 years ago
README.md doc: add annaconda info (#402) 3 years ago
app.py fix: account check in runtime (#569) 3 years ago
commands.py add clean unused dataset command (#609) 3 years ago
config.py Feat/clean vector dataset (#605) 3 years ago
requirements.txt feat: claude api support (#572) 3 years ago

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 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

  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, celery can do dataset importing and other async tasks.