您最多选择25个主题 主题必须以字母或数字开头,可以包含连字符 (-),并且长度不得超过35个字符
Nam Vu 6e37750fbd
fix: commands.py (#8483)
1年前
..
.idea fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 1年前
.vscode chore: remove .idea and .vscode from root path (#7437) 1年前
configs chore: enhance configuration descriptions (#8624) 1年前
constants feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 1年前
contexts chore(api): Introduce Ruff Formatter. (#7291) 1年前
controllers feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 1年前
core fix: redundant check for available_document_count (#8491) 1年前
docker fix: use LOG_LEVEL for celery startup (#7628) 1年前
events chore: refurbish Python code by applying refurb linter rules (#8296) 1年前
extensions add storage error log (#8556) 1年前
fields feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 1年前
libs chore: refurish python code by applying Pylint linter rules (#8322) 1年前
migrations feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 1年前
models feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 1年前
schedule chore(api): Introduce Ruff Formatter. (#7291) 1年前
services feat: regenerate in `Chat`, `agent` and `Chatflow` app (#7661) 1年前
tasks chore: refurish python code by applying Pylint linter rules (#8322) 1年前
templates feat: implement forgot password feature (#5534) 1年前
tests Add Fireworks AI as new model provider (#8428) 1年前
.dockerignore build: support Poetry for depencencies tool in api's Dockerfile (#5105) 1年前
.env.example add volcengine tos storage (#8164) 1年前
Dockerfile fix: Version '2.6.2-2' for 'expat' was not found (#8182) 1年前
README.md Enhance Readme Documentation to Clarify the Importance of Celery Service (#8558) 1年前
app.py chore: refurish python code by applying Pylint linter rules (#8322) 1年前
commands.py fix: commands.py (#8483) 1年前
poetry.lock chore: add Gemini newest experimental models (close #7121) (#8621) 1年前
poetry.toml build: initial support for poetry build tool (#4513) 1年前
pyproject.toml chore: add Gemini newest experimental models (close #7121) (#8621) 1年前

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