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Bowen Liang 9b46b02717
refactor: assembling the app features in modular way (#9129)
11 meses atrás
..
.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 ano atrás
.vscode feat/enhance the multi-modal support (#8818) 1 ano atrás
configs refactor: assembling the app features in modular way (#9129) 11 meses atrás
constants chore: add Thai GUI (#11201) 11 meses atrás
contexts feat/enhance the multi-modal support (#8818) 1 ano atrás
controllers chore(*): Removes debugging print statements (#11145) 11 meses atrás
core fix: use Gemini response metadata for token counting (#11226) 11 meses atrás
docker fix: remove unused queue `generation` (#10532) 11 meses atrás
events chore: bump minimum supported Python version to 3.11 (#10386) 11 meses atrás
extensions refactor: assembling the app features in modular way (#9129) 11 meses atrás
factories fix(file_factory): Remove transfer_method validation (#11207) 11 meses atrás
fields feat: Check and compare the DSL version before import an app (#10969) 11 meses atrás
libs refactor: assembling the app features in modular way (#9129) 11 meses atrás
migrations Feat/clean message records (#10588) 11 meses atrás
models fix: Cannot use files in the user inputs. (#11112) 11 meses atrás
schedule update the scheduler of update_tidb_serverless_status_task to 1/10min (#11135) 11 meses atrás
services fix: code linting (#11143) 11 meses atrás
tasks fix: wrong param name (#11039) 11 meses atrás
templates Feat/new login (#8120) 1 ano atrás
tests refactor: assembling the app features in modular way (#9129) 11 meses atrás
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 ano atrás
.env.example feat: add retireval_top_n to config in env (#11132) 11 meses atrás
Dockerfile chore: update base image to Python 3.12 in Dockerfile (#10358) 11 meses atrás
README.md chore: update base image to Python 3.12 in Dockerfile (#10358) 11 meses atrás
app.py refactor: assembling the app features in modular way (#9129) 11 meses atrás
app_factory.py refactor: assembling the app features in modular way (#9129) 11 meses atrás
commands.py refactor: assembling the app features in modular way (#9129) 11 meses atrás
dify_app.py refactor: assembling the app features in modular way (#9129) 11 meses atrás
poetry.lock chore(dep): bump flask from 3.0.1 to 3.1.0 and flask-compress to 1.17 (#11195) 11 meses atrás
poetry.toml build: initial support for poetry build tool (#4513) 1 ano atrás
pyproject.toml chore(dep): bump flask from 3.0.1 to 3.1.0 and flask-compress to 1.17 (#11195) 11 meses atrás
pytest.ini feat: Add support for TEI API key authentication (#11006) 11 meses atrás

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