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Cling_o3 ab127ba92e
[fix] fix the bug that modify document name not effective (#10154)
1年前
..
.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1年前
.vscode feat/enhance the multi-modal support (#8818) 1年前
configs fix: avoid unexpected error when create knowledge base with baidu vector database and wenxin embedding model (#10130) 1年前
constants nltk security issue and upgrade unstructured (#9558) 1年前
contexts feat/enhance the multi-modal support (#8818) 1年前
controllers Feat/add-remote-file-upload-api (#9906) 1年前
core feat: add gpustack model provider (#10158) 1年前
docker fix: use LOG_LEVEL for celery startup (#7628) 1年前
events feat/enhance the multi-modal support (#8818) 1年前
extensions Revert "chore: improve validation and handler of logging timezone with TimezoneName" (#10077) 1年前
factories Feat/add-remote-file-upload-api (#9906) 1年前
fields Feat/add-remote-file-upload-api (#9906) 1年前
libs refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1年前
migrations refactor(migration/model): update column types for workflow schema (#10160) 1年前
models fix(workflow model): ensure consistent timestamp updating (#10172) 1年前
schedule fix: Cannot find declaration to go to CLEAN_DAY_SETTING (#10157) 1年前
services [fix] fix the bug that modify document name not effective (#10154) 1年前
tasks Feat/new login (#8120) 1年前
templates Feat/new login (#8120) 1年前
tests feat: add gpustack model provider (#10158) 1年前
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1年前
.env.example chore: add tidb-on-qdrant configuration in env and docker-compose file (#10015) 1年前
Dockerfile fix(Dockerfile): conditionally install zlib1g based on architecture (#10118) 1年前
README.md fix: poetry installation in CI jobs (#9336) 1年前
app.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1年前
app_factory.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1年前
commands.py Added OceanBase as an option for the vector store in Dify (#10010) 1年前
poetry.lock fix: avoid unexpected error when create knowledge base with baidu vector database and wenxin embedding model (#10130) 1年前
poetry.toml build: initial support for poetry build tool (#4513) 1年前
pyproject.toml Added OceanBase as an option for the vector store in Dify (#10010) 1年前
pytest.ini feat: add models for gitee.ai (#9490) 1年前

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