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-LAN- de57af46c0
chore: update version to 0.10.2 in packaging and docker configurations (#9924)
1 年之前
..
.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 年之前
.vscode feat/enhance the multi-modal support (#8818) 1 年之前
configs chore: update version to 0.10.2 in packaging and docker configurations (#9924) 1 年之前
constants nltk security issue and upgrade unstructured (#9558) 1 年之前
contexts feat/enhance the multi-modal support (#8818) 1 年之前
controllers fix: enterprise create workspace (#9921) 1 年之前
core feat(http-request-executor): enhance file handling in HTTP requests (#9944) 1 年之前
docker fix: use LOG_LEVEL for celery startup (#7628) 1 年之前
events feat/enhance the multi-modal support (#8818) 1 年之前
extensions add tidb on qdrant type (#9831) 1 年之前
factories refactor(file_factory): improve filename and mime type determination (#9784) 1 年之前
fields feat(api): add video and audio file size limits to upload config (#9703) 1 年之前
libs refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 年之前
migrations add tidb on qdrant type (#9831) 1 年之前
models fix(api): add signature generation for image previews (#9893) 1 年之前
schedule add tidb on qdrant type (#9831) 1 年之前
services Fix/external api update (#9955) 1 年之前
tasks Feat/new login (#8120) 1 年之前
templates Feat/new login (#8120) 1 年之前
tests feat(http-request-executor): enhance file handling in HTTP requests (#9944) 1 年之前
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 年之前
.env.example chore: add default value for redis configuration (#9864) 1 年之前
Dockerfile chore(docker): correct package version for expat and perl in Dockerfile (#9801) 1 年之前
README.md fix: poetry installation in CI jobs (#9336) 1 年之前
app.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 年之前
app_factory.py refactor: use dify_config to replace legacy usage of flask app's config (#9089) 1 年之前
commands.py feat: add upstash as a new vector database provider (#9644) 1 年之前
poetry.lock upgrade nltk, unstructured and starlette (#9860) 1 年之前
poetry.toml build: initial support for poetry build tool (#4513) 1 年之前
pyproject.toml upgrade nltk, unstructured and starlette (#9860) 1 年之前
pytest.ini feat: add models for gitee.ai (#9490) 1 年之前

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