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zhuhao eec63b112f
chore: add default value for redis configuration (#9864)
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 anno fa
.vscode feat/enhance the multi-modal support (#8818) 1 anno fa
configs add tidb on qdrant type (#9831) 1 anno fa
constants nltk security issue and upgrade unstructured (#9558) 1 anno fa
contexts feat/enhance the multi-modal support (#8818) 1 anno fa
controllers add tidb on qdrant type (#9831) 1 anno fa
core fix: moonshot response_format raise error (#9847) 1 anno fa
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factories refactor(file_factory): improve filename and mime type determination (#9784) 1 anno fa
fields feat(api): add video and audio file size limits to upload config (#9703) 1 anno fa
libs refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 anno fa
migrations add tidb on qdrant type (#9831) 1 anno fa
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services Marking the last piece of data on each page is a duplicate issue, which can be solved by adding the id field to the order by rig and using a unique field (#9799) 1 anno fa
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tests chore: add local storage test (#9827) 1 anno fa
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 anno fa
.env.example chore: add default value for redis configuration (#9864) 1 anno fa
Dockerfile chore(docker): correct package version for expat and perl in Dockerfile (#9801) 1 anno fa
README.md fix: poetry installation in CI jobs (#9336) 1 anno fa
app.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 anno fa
app_factory.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 anno fa
commands.py feat: add upstash as a new vector database provider (#9644) 1 anno fa
poetry.lock upgrade nltk, unstructured and starlette (#9860) 1 anno fa
poetry.toml build: initial support for poetry build tool (#4513) 1 anno fa
pyproject.toml upgrade nltk, unstructured and starlette (#9860) 1 anno fa
pytest.ini chore: move testing env variables from pyproject.toml to pytest.ini (#9019) 1 anno 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
  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