非法操作 5660878f7b chore: update the tool's doc (#6167) 2 gadi atpakaļ
..
configs 9622fbb62f feat: app rate limit (#5844) 2 gadi atpakaļ
constants 6ef401a9f0 feat:add tts-streaming config and future (#5492) 2 gadi atpakaļ
controllers 9622fbb62f feat: app rate limit (#5844) 2 gadi atpakaļ
core 5660878f7b chore: update the tool's doc (#6167) 2 gadi atpakaļ
docker cb09dbef66 feat: correctly delete applications using Celery workers (#5787) 2 gadi atpakaļ
events cb09dbef66 feat: correctly delete applications using Celery workers (#5787) 2 gadi atpakaļ
extensions cbbe28f40d fix azure stream download (#6063) 2 gadi atpakaļ
fields 9622fbb62f feat: app rate limit (#5844) 2 gadi atpakaļ
libs 9622fbb62f feat: app rate limit (#5844) 2 gadi atpakaļ
migrations 9622fbb62f feat: app rate limit (#5844) 2 gadi atpakaļ
models 9622fbb62f feat: app rate limit (#5844) 2 gadi atpakaļ
schedule 6c4e6bf1d6 Feat/dify rag (#2528) 2 gadi atpakaļ
services 9622fbb62f feat: app rate limit (#5844) 2 gadi atpakaļ
tasks 00b4cc3cd4 feat: implement forgot password feature (#5534) 2 gadi atpakaļ
templates 00b4cc3cd4 feat: implement forgot password feature (#5534) 2 gadi atpakaļ
tests 7c70eb87bc feat: support AnalyticDB vector store (#5586) 2 gadi atpakaļ
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 2 gadi atpakaļ
.env.example 9622fbb62f feat: app rate limit (#5844) 2 gadi atpakaļ
Dockerfile 9b7c74a5d9 chore: skip pip upgrade preparation in api dockerfile (#5999) 2 gadi atpakaļ
README.md 2d6624cf9e typo: Update README.md (#5987) 2 gadi atpakaļ
app.py d7f75d17cc Chore/remove-unused-code (#5917) 2 gadi atpakaļ
commands.py 7c70eb87bc feat: support AnalyticDB vector store (#5586) 2 gadi atpakaļ
poetry.lock f9d00e0498 chore: use poetry for linter tools installation and bump Ruff from 0.4 to 0.5 (#6081) 2 gadi atpakaļ
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 2 gadi atpakaļ
pyproject.toml f9d00e0498 chore: use poetry for linter tools installation and bump Ruff from 0.4 to 0.5 (#6081) 2 gadi atpakaļ

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
   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,app_deletion

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