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John Wang 9d98669e7d
fix: dataset destination error (#477)
2 vuotta sitten
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constants Initial commit 2 vuotta sitten
controllers Feature/add is deleted to conversations (#470) 2 vuotta sitten
core fix: dataset destination error (#477) 2 vuotta sitten
docker Initial commit 2 vuotta sitten
events Initial commit 2 vuotta sitten
extensions feat: upgrade langchain (#430) 2 vuotta sitten
libs feat: upgrade langchain (#430) 2 vuotta sitten
migrations Feature/add is deleted to conversations (#470) 2 vuotta sitten
models Feature/add is deleted to conversations (#470) 2 vuotta sitten
services Feature/add is deleted to conversations (#470) 2 vuotta sitten
tasks feat: upgrade langchain (#430) 2 vuotta sitten
tests Initial commit 2 vuotta sitten
.dockerignore Initial commit 2 vuotta sitten
.env.example fix REDIS_USERNAME format (#414) 2 vuotta sitten
Dockerfile Initial commit 2 vuotta sitten
README.md doc: add annaconda info (#402) 2 vuotta sitten
app.py feat: upgrade langchain (#430) 2 vuotta sitten
commands.py feat: upgrade langchain (#430) 2 vuotta sitten
config.py feat: bump to 0.3.6 (#474) 2 vuotta sitten
requirements.txt feat: upgrade langchain (#430) 2 vuotta sitten

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
  1. Copy .env.example to .env
  2. 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 bash pip install -r requirements.txt
  2. Run migrate

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

   flask db upgrade
  1. Start backend: bash flask run --host 0.0.0.0 --port=5001 --debug
  2. Setup your application by visiting http://localhost:5001/console/api/setup or other apis…
  3. 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.