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fix(llm-node): handle NoneSegment variables properly (#9978)
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 рік тому
.vscode feat/enhance the multi-modal support (#8818) 1 рік тому
configs Added OceanBase as an option for the vector store in Dify (#10010) 1 рік тому
constants nltk security issue and upgrade unstructured (#9558) 1 рік тому
contexts feat/enhance the multi-modal support (#8818) 1 рік тому
controllers Added OceanBase as an option for the vector store in Dify (#10010) 1 рік тому
core fix(llm-node): handle NoneSegment variables properly (#9978) 1 рік тому
docker fix: use LOG_LEVEL for celery startup (#7628) 1 рік тому
events feat/enhance the multi-modal support (#8818) 1 рік тому
extensions add tidb on qdrant type (#9831) 1 рік тому
factories refactor(file_factory): improve filename and mime type determination (#9784) 1 рік тому
fields feat(api): add video and audio file size limits to upload config (#9703) 1 рік тому
libs refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 рік тому
migrations add tidb on qdrant type (#9831) 1 рік тому
models fix(api): add signature generation for image previews (#9893) 1 рік тому
schedule add tidb on qdrant type (#9831) 1 рік тому
services fix: allow external knowledge api use simple host (#9966) 1 рік тому
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templates Feat/new login (#8120) 1 рік тому
tests Fix content-type header case sensitivity (#9961) 1 рік тому
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 рік тому
.env.example chore: add tidb-on-qdrant configuration in env and docker-compose file (#10015) 1 рік тому
Dockerfile chore(docker): correct package version for expat and perl in Dockerfile (#9801) 1 рік тому
README.md fix: poetry installation in CI jobs (#9336) 1 рік тому
app.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 рік тому
app_factory.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 рік тому
commands.py Added OceanBase as an option for the vector store in Dify (#10010) 1 рік тому
poetry.lock Added OceanBase as an option for the vector store in Dify (#10010) 1 рік тому
poetry.toml build: initial support for poetry build tool (#4513) 1 рік тому
pyproject.toml Added OceanBase as an option for the vector store in Dify (#10010) 1 рік тому
pytest.ini feat: add models for gitee.ai (#9490) 1 рік тому

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