呆萌闷油瓶 68ac433218 feat: add support Spark4.0 (#5688) 10 miesięcy temu
..
configs 17d2f0bb0d fix(api/configs): Ignore empty environment variables when loading config. (#5647) 10 miesięcy temu
constants 2e718b85e9 fix(api): language list (#5649) 10 miesięcy temu
controllers 4c0a31d38b FR: #4048 - Add color customization to the chatbot (#4885) 10 miesięcy temu
core 68ac433218 feat: add support Spark4.0 (#5688) 10 miesięcy temu
docker e8b8f6c6dd Feat/fix ops trace (#5672) 10 miesięcy temu
events d160d1ed02 feat: support opensearch approximate k-NN (#5322) 10 miesięcy temu
extensions 3cc6093e4b feat: introduce pydantic-settings for config definition and validation (#5202) 10 miesięcy temu
fields 4c0a31d38b FR: #4048 - Add color customization to the chatbot (#4885) 10 miesięcy temu
libs dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) 10 miesięcy temu
migrations e8b8f6c6dd Feat/fix ops trace (#5672) 10 miesięcy temu
models e8b8f6c6dd Feat/fix ops trace (#5672) 10 miesięcy temu
schedule 6c4e6bf1d6 Feat/dify rag (#2528) 1 rok temu
services dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) 10 miesięcy temu
tasks e8b8f6c6dd Feat/fix ops trace (#5672) 10 miesięcy temu
templates 3d92784bd4 fix: email template style (#1914) 1 rok temu
tests dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) 10 miesięcy temu
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 10 miesięcy temu
.env.example 964f0e1400 fix: Modify the incorrect configuration name for Google storage (#5595) 10 miesięcy temu
Dockerfile 73ce945d40 Feat/add json process tool (#5555) 10 miesięcy temu
README.md f9e4b4e74c Fix docker command (#5681) 10 miesięcy temu
app.py dd5f3873da feat: change TRACE_QUEUE_MANAGER_INTERVAL default value (#5698) 10 miesięcy temu
commands.py d160d1ed02 feat: support opensearch approximate k-NN (#5322) 10 miesięcy temu
poetry.lock 73ce945d40 Feat/add json process tool (#5555) 10 miesięcy temu
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 miesięcy temu
pyproject.toml 73ce945d40 Feat/add json process tool (#5555) 10 miesięcy temu

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
   docker compose -f docker-compose.middleware.yaml -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 debug local async processing, 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

The started celery app handles the async tasks, e.g. dataset importing and documents indexing.

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