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feat/enhance the multi-modal support (#8818)
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 ano atrás
.vscode feat/enhance the multi-modal support (#8818) 1 ano atrás
configs feat/enhance the multi-modal support (#8818) 1 ano atrás
constants feat/enhance the multi-modal support (#8818) 1 ano atrás
contexts feat/enhance the multi-modal support (#8818) 1 ano atrás
controllers feat/enhance the multi-modal support (#8818) 1 ano atrás
core feat/enhance the multi-modal support (#8818) 1 ano atrás
docker fix: use LOG_LEVEL for celery startup (#7628) 1 ano atrás
events feat/enhance the multi-modal support (#8818) 1 ano atrás
extensions feat/enhance the multi-modal support (#8818) 1 ano atrás
factories feat/enhance the multi-modal support (#8818) 1 ano atrás
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migrations feat/enhance the multi-modal support (#8818) 1 ano atrás
models feat/enhance the multi-modal support (#8818) 1 ano atrás
schedule update dataset clean rule (#9426) 1 ano atrás
services feat/enhance the multi-modal support (#8818) 1 ano atrás
tasks Feat/new login (#8120) 1 ano atrás
templates Feat/new login (#8120) 1 ano atrás
tests feat/enhance the multi-modal support (#8818) 1 ano atrás
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 ano atrás
.env.example feat/enhance the multi-modal support (#8818) 1 ano atrás
Dockerfile fix: Version '2.6.2-2' for 'expat' was not found (#8182) 1 ano atrás
README.md fix: poetry installation in CI jobs (#9336) 1 ano atrás
app.py fix: resolve the error with the db-pool-stat endpoint (#9478) 1 ano atrás
app_factory.py controller test (#9469) 1 ano atrás
commands.py feat/enhance the multi-modal support (#8818) 1 ano atrás
poetry.lock feat/enhance the multi-modal support (#8818) 1 ano atrás
poetry.toml build: initial support for poetry build tool (#4513) 1 ano atrás
pyproject.toml feat/enhance the multi-modal support (#8818) 1 ano atrás
pytest.ini chore: move testing env variables from pyproject.toml to pytest.ini (#9019) 1 ano atrás

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