Jyong 71bcf75d9a Feat/add delete knowledge confirm (#5810) 9 месяцев назад
..
configs 8fd75e6965 bump to 0.6.12-fix1 (#5743) 9 месяцев назад
constants 2e718b85e9 fix(api): language list (#5649) 10 месяцев назад
controllers 71bcf75d9a Feat/add delete knowledge confirm (#5810) 9 месяцев назад
core 850c2273ee feat: Nominatim OpenStreetMap search tool (#5789) 9 месяцев назад
docker cb09dbef66 feat: correctly delete applications using Celery workers (#5787) 9 месяцев назад
events cb09dbef66 feat: correctly delete applications using Celery workers (#5787) 9 месяцев назад
extensions 3cc6093e4b feat: introduce pydantic-settings for config definition and validation (#5202) 10 месяцев назад
fields 4c0a31d38b FR: #4048 - Add color customization to the chatbot (#4885) 10 месяцев назад
libs dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) 10 месяцев назад
migrations 1e045a0187 fix: slow sql of ops tracing (#5749) 9 месяцев назад
models 1e045a0187 fix: slow sql of ops tracing (#5749) 9 месяцев назад
schedule 6c4e6bf1d6 Feat/dify rag (#2528) 1 год назад
services 71bcf75d9a Feat/add delete knowledge confirm (#5810) 9 месяцев назад
tasks cb09dbef66 feat: correctly delete applications using Celery workers (#5787) 9 месяцев назад
templates 3d92784bd4 fix: email template style (#1914) 1 год назад
tests dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) 10 месяцев назад
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 10 месяцев назад
.env.example 964f0e1400 fix: Modify the incorrect configuration name for Google storage (#5595) 10 месяцев назад
Dockerfile 73ce945d40 Feat/add json process tool (#5555) 10 месяцев назад
README.md cb09dbef66 feat: correctly delete applications using Celery workers (#5787) 9 месяцев назад
app.py 017d2c804b fix: do not remove (#5706) 10 месяцев назад
commands.py 8e5569f773 fix: fix-app-site-missing command (#5714) 10 месяцев назад
poetry.lock fdfbbde10d [seanguo] modify bedrock Claude3 invoke method to converse API (#5768) 9 месяцев назад
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 месяцев назад
pyproject.toml fdfbbde10d [seanguo] modify bedrock Claude3 invoke method to converse API (#5768) 9 месяцев назад

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
   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