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gcgj-dify-1.7.0/api
History
John Wang a3ee037d6d
feat: optimize output parse failed error (#298) 		3 years ago
..
constants Initial commit 3 years ago
controllers feat: increase dataset description length to 400 (#283) 3 years ago
core feat: optimize output parse failed error (#298) 3 years ago
docker Initial commit 3 years ago
events Initial commit 3 years ago
extensions feat: add redis ssl support (#65) 3 years ago
libs feat: fix json end with `` (#285) 3 years ago
migrations feat: explore support multi language (#202) 3 years ago
models feat: new stats (#265) 3 years ago
services Feat: Support re-segmentation (#114) 3 years ago
tasks Feat: Support re-segmentation (#114) 3 years ago
tests Initial commit 3 years ago
.dockerignore Initial commit 3 years ago
.env.example fix: bootstrap env (#127) 3 years ago
Dockerfile Initial commit 3 years ago
README.md feat: add celery document (#118) 3 years ago
app.py Initial commit 3 years ago
commands.py feat: explore support multi language (#202) 3 years ago
config.py feat: bump to 0.3.1 (#253) 3 years ago
requirements.txt Initial commit 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

  4. Install dependencies

    pip install -r requirements.txt

  5. Run migrate

    Before the first launch, migrate the database to the latest version.

    flask db upgrade

  6. Start backend:

    flask run --host 0.0.0.0 --port=5001 --debug

  7. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...

  8. 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.