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-LAN- 5c7b1358d4
chore(release): bump version to 0.9.2 (#9314)
1 년 전
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.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1 년 전
.vscode chore: remove .idea and .vscode from root path (#7437) 1 년 전
configs chore(release): bump version to 0.9.2 (#9314) 1 년 전
constants feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 1 년 전
contexts chore(api): Introduce Ruff Formatter. (#7291) 1 년 전
controllers Add Volcengine VikingDB as new vector provider (#9287) 1 년 전
core chore: remove the copied zhipu_ai sdk (#9270) 1 년 전
docker fix: use LOG_LEVEL for celery startup (#7628) 1 년 전
events chore: bump ruff to 0.6.8 for fixing violation in SIM910 (#8869) 1 년 전
extensions Fix/s3 iam add region name (#7819) 1 년 전
fields external knowledge api (#8913) 1 년 전
libs Feat/implement-refresh-tokens (#9233) 1 년 전
migrations fix(migrations): correct parent_message_id for service-api records (#9132) 1 년 전
models external knowledge api (#8913) 1 년 전
schedule external knowledge api (#8913) 1 년 전
services refactor: Refactor the service of retrieval the recommend app (#9302) 1 년 전
tasks external knowledge api (#8913) 1 년 전
templates feat: implement forgot password feature (#5534) 1 년 전
tests Add Volcengine VikingDB as new vector provider (#9287) 1 년 전
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1 년 전
.env.example Add Volcengine VikingDB as new vector provider (#9287) 1 년 전
Dockerfile fix: Version '2.6.2-2' for 'expat' was not found (#8182) 1 년 전
README.md Enhance Readme Documentation to Clarify the Importance of Celery Service (#8558) 1 년 전
app.py Feat/implement-refresh-tokens (#9233) 1 년 전
commands.py feat:support baidu vector db (#9185) 1 년 전
poetry.lock fix: Add new Milvus Lite wheel for manylinux2014_aarch64 (#9316) 1 년 전
poetry.toml build: initial support for poetry build tool (#4513) 1 년 전
pyproject.toml chore: remove the copied zhipu_ai sdk (#9270) 1 년 전
pytest.ini chore: move testing env variables from pyproject.toml to pytest.ini (#9019) 1 년 전

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