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jiangbo721 07ad362854
fix: Cannot find declaration to go to CLEAN_DAY_SETTING (#10157)
1 년 전
..
.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 년 전
.vscode feat/enhance the multi-modal support (#8818) 1 년 전
configs fix: avoid unexpected error when create knowledge base with baidu vector database and wenxin embedding model (#10130) 1 년 전
constants nltk security issue and upgrade unstructured (#9558) 1 년 전
contexts feat/enhance the multi-modal support (#8818) 1 년 전
controllers Feat/add-remote-file-upload-api (#9906) 1 년 전
core feat: add gpustack model provider (#10158) 1 년 전
docker fix: use LOG_LEVEL for celery startup (#7628) 1 년 전
events feat/enhance the multi-modal support (#8818) 1 년 전
extensions Revert "chore: improve validation and handler of logging timezone with TimezoneName" (#10077) 1 년 전
factories Feat/add-remote-file-upload-api (#9906) 1 년 전
fields Feat/add-remote-file-upload-api (#9906) 1 년 전
libs refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 년 전
migrations refactor(migration/model): update column types for workflow schema (#10160) 1 년 전
models refactor(migration/model): update column types for workflow schema (#10160) 1 년 전
schedule fix: Cannot find declaration to go to CLEAN_DAY_SETTING (#10157) 1 년 전
services Feat/add-remote-file-upload-api (#9906) 1 년 전
tasks Feat/new login (#8120) 1 년 전
templates Feat/new login (#8120) 1 년 전
tests feat: add gpustack model provider (#10158) 1 년 전
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 년 전
.env.example chore: add tidb-on-qdrant configuration in env and docker-compose file (#10015) 1 년 전
Dockerfile fix(Dockerfile): conditionally install zlib1g based on architecture (#10118) 1 년 전
README.md fix: poetry installation in CI jobs (#9336) 1 년 전
app.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 년 전
app_factory.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 년 전
commands.py Added OceanBase as an option for the vector store in Dify (#10010) 1 년 전
poetry.lock fix: avoid unexpected error when create knowledge base with baidu vector database and wenxin embedding model (#10130) 1 년 전
poetry.toml build: initial support for poetry build tool (#4513) 1 년 전
pyproject.toml Added OceanBase as an option for the vector store in Dify (#10010) 1 년 전
pytest.ini feat: add models for gitee.ai (#9490) 1 년 전

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
  2. Generate a SECRET_KEY in the .env file.
   sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
   secret_key=$(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 3.10
   poetry install

In case of contributors missing to update dependencies for pyproject.toml, you can perform the following shell instead.

   poetry shell                                               # activate current environment
   poetry add $(cat requirements.txt)           # install dependencies of production and update pyproject.toml
   poetry add $(cat requirements-dev.txt) --group dev    # install dependencies of development and update pyproject.toml
  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 --with dev
  1. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml
   cd ../
   poetry run -C api bash dev/pytest/pytest_all_tests.sh