呆萌闷油瓶 cd4310df25 chore:update azure api version (#11711) 4 mesi fa
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.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 8 mesi fa
.vscode e61752bd3a feat/enhance the multi-modal support (#8818) 6 mesi fa
configs e20161b3de make login lockout duration configurable (#11699) 4 mesi fa
constants 36cb25b341 fix: support mdx files close #11557 (#11565) 4 mesi fa
contexts e61752bd3a feat/enhance the multi-modal support (#8818) 6 mesi fa
controllers 259cff9f22 fix(api/ops_trace): avoid raise exception directly (#11732) 4 mesi fa
core cd4310df25 chore:update azure api version (#11711) 4 mesi fa
docker 8d4bb9b40d feat: integrate opendal storage (#11508) 4 mesi fa
events 6c8e208ef3 chore: bump minimum supported Python version to 3.11 (#10386) 5 mesi fa
extensions 38e155d819 feat: log add trace id (#11599) 4 mesi fa
factories e135ffc2c1 Feat: upgrade variable assigner (#11285) 4 mesi fa
fields 79a710ce98 Feat: continue on error (#11458) 4 mesi fa
libs 8e3d60c359 fix: account.id should account_id (#11628) 4 mesi fa
migrations 79a710ce98 Feat: continue on error (#11458) 4 mesi fa
models 4b402c4041 fix: enhance workflow.tool_published performance (#11640) 4 mesi fa
schedule 00ac7edeb3 improve message clean logic (#11487) 4 mesi fa
services e20161b3de make login lockout duration configurable (#11699) 4 mesi fa
tasks 1a7c213405 fix: ExternalDatasetService.process_external_api wrong args (#11586) 4 mesi fa
templates 4fd2743efa Feat/new login (#8120) 6 mesi fa
tests 74fdc16bd1 feat: enhance gemini models (#11497) 4 mesi fa
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 10 mesi fa
.env.example e20161b3de make login lockout duration configurable (#11699) 4 mesi fa
.ruff.toml e79eac688a chore(lint): sort __all__ definitions (#11243) 4 mesi fa
Dockerfile ef204817ae chore(api/Dockerfile): Bump perl to 0.40.0-8 (#11234) 4 mesi fa
README.md da601f0bef chore: update base image to Python 3.12 in Dockerfile (#10358) 5 mesi fa
app.py 9b46b02717 refactor: assembling the app features in modular way (#9129) 4 mesi fa
app_factory.py 9b46b02717 refactor: assembling the app features in modular way (#9129) 4 mesi fa
commands.py 5669cac16d fix: some typos using typos (#11374) 4 mesi fa
dify_app.py 9b46b02717 refactor: assembling the app features in modular way (#9129) 4 mesi fa
poetry.lock efa8eb379f fix: memory leak by pypdfium2 close(maybe) #11510 (#11700) 4 mesi fa
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 mesi fa
pyproject.toml efa8eb379f fix: memory leak by pypdfium2 close(maybe) #11510 (#11700) 4 mesi fa
pytest.ini 096c0ad564 feat: Add support for TEI API key authentication (#11006) 5 mesi fa

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