crazywoola e7a4cfac4d fix: name of llama-3.3-70b-specdec (#11596) 4 hónapja
..
.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 8 hónapja
.vscode e61752bd3a feat/enhance the multi-modal support (#8818) 6 hónapja
configs 0d04cdc323 Lindorm vdb (#11574) 4 hónapja
constants 36cb25b341 fix: support mdx files close #11557 (#11565) 4 hónapja
contexts e61752bd3a feat/enhance the multi-modal support (#8818) 6 hónapja
controllers 5c166b3f40 fix: tags could not be saved when the Workflow Tool was created (#11481) 4 hónapja
core e7a4cfac4d fix: name of llama-3.3-70b-specdec (#11596) 4 hónapja
docker 8d4bb9b40d feat: integrate opendal storage (#11508) 4 hónapja
events 6c8e208ef3 chore: bump minimum supported Python version to 3.11 (#10386) 5 hónapja
extensions 180743612c fix: better opendal tests (#11569) 4 hónapja
factories e135ffc2c1 Feat: upgrade variable assigner (#11285) 4 hónapja
fields 79a710ce98 Feat: continue on error (#11458) 4 hónapja
libs 41d90c2408 fix(api): throw error when notion block can not find (#11433) 4 hónapja
migrations 79a710ce98 Feat: continue on error (#11458) 4 hónapja
models 79a710ce98 Feat: continue on error (#11458) 4 hónapja
schedule 00ac7edeb3 improve message clean logic (#11487) 4 hónapja
services d05f189049 Fix: RateLimit requests were not released when a streaming generation exception occurred (#11540) 4 hónapja
tasks 9d975750bc fix: update DocumentIsPausedError (#11405) 4 hónapja
templates 4fd2743efa Feat/new login (#8120) 6 hónapja
tests 0d04cdc323 Lindorm vdb (#11574) 4 hónapja
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 10 hónapja
.env.example 0d04cdc323 Lindorm vdb (#11574) 4 hónapja
.ruff.toml e79eac688a chore(lint): sort __all__ definitions (#11243) 4 hónapja
Dockerfile ef204817ae chore(api/Dockerfile): Bump perl to 0.40.0-8 (#11234) 4 hónapja
README.md da601f0bef chore: update base image to Python 3.12 in Dockerfile (#10358) 5 hónapja
app.py 9b46b02717 refactor: assembling the app features in modular way (#9129) 4 hónapja
app_factory.py 9b46b02717 refactor: assembling the app features in modular way (#9129) 4 hónapja
commands.py 5669cac16d fix: some typos using typos (#11374) 4 hónapja
dify_app.py 9b46b02717 refactor: assembling the app features in modular way (#9129) 4 hónapja
poetry.lock 8d4bb9b40d feat: integrate opendal storage (#11508) 4 hónapja
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 hónapja
pyproject.toml 8d4bb9b40d feat: integrate opendal storage (#11508) 4 hónapja
pytest.ini 096c0ad564 feat: Add support for TEI API key authentication (#11006) 5 hónapja

README.md

Dify Backend API

Usage

[!IMPORTANT] In the v0.6.12 release, we deprecated pip as the package management tool for Dify API Backend service and replaced it with poetry.

  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
   cp middleware.env.example middleware.env
   # change the profile to other vector database if you are not using weaviate
   docker compose -f docker-compose.middleware.yaml --profile weaviate -p dify up -d
   cd ../api
  1. Copy .env.example to .env
   cp .env.example .env 
  1. Generate a SECRET_KEY in the .env file.

bash for Linux

   sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env

bash for Mac

   secret_key=$(openssl rand -base64 42)
   sed -i '' "/^SECRET_KEY=/c\\
   SECRET_KEY=${secret_key}" .env
  1. Create environment.

Dify API service uses Poetry to manage dependencies. You can execute poetry shell to activate the environment.

  1. Install dependencies
   poetry env use 3.12
   poetry install
  1. Run migrate

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

   poetry run python -m flask db upgrade
  1. Start backend
   poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug
  1. Start Dify web service.
  2. Setup your application by visiting http://localhost:3000...
  3. If you need to handle and debug the async tasks (e.g. dataset importing and documents indexing), please start the worker service.
   poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion

Testing

  1. Install dependencies for both the backend and the test environment
   poetry install -C api --with dev
  1. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml
   poetry run -C api bash dev/pytest/pytest_all_tests.sh