Charles Zhou cb09dbef66 feat: correctly delete applications using Celery workers (#5787) пре 1 година
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configs 8fd75e6965 bump to 0.6.12-fix1 (#5743) пре 1 година
constants 2e718b85e9 fix(api): language list (#5649) пре 1 година
controllers 906857b28a fix: couldn't log in or resetup after a failed setup (#5739) пре 1 година
core fdfbbde10d [seanguo] modify bedrock Claude3 invoke method to converse API (#5768) пре 1 година
docker cb09dbef66 feat: correctly delete applications using Celery workers (#5787) пре 1 година
events cb09dbef66 feat: correctly delete applications using Celery workers (#5787) пре 1 година
extensions 3cc6093e4b feat: introduce pydantic-settings for config definition and validation (#5202) пре 1 година
fields 4c0a31d38b FR: #4048 - Add color customization to the chatbot (#4885) пре 1 година
libs dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) пре 1 година
migrations 1e045a0187 fix: slow sql of ops tracing (#5749) пре 1 година
models 1e045a0187 fix: slow sql of ops tracing (#5749) пре 1 година
schedule 6c4e6bf1d6 Feat/dify rag (#2528) пре 1 година
services cb09dbef66 feat: correctly delete applications using Celery workers (#5787) пре 1 година
tasks cb09dbef66 feat: correctly delete applications using Celery workers (#5787) пре 1 година
templates 3d92784bd4 fix: email template style (#1914) пре 1 година
tests dcb72e0067 chore: apply flake8-comprehensions Ruff rules to improve collection comprehensions (#5652) пре 1 година
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) пре 1 година
.env.example 964f0e1400 fix: Modify the incorrect configuration name for Google storage (#5595) пре 1 година
Dockerfile 73ce945d40 Feat/add json process tool (#5555) пре 1 година
README.md cb09dbef66 feat: correctly delete applications using Celery workers (#5787) пре 1 година
app.py 017d2c804b fix: do not remove (#5706) пре 1 година
commands.py 8e5569f773 fix: fix-app-site-missing command (#5714) пре 1 година
poetry.lock fdfbbde10d [seanguo] modify bedrock Claude3 invoke method to converse API (#5768) пре 1 година
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) пре 1 година
pyproject.toml fdfbbde10d [seanguo] modify bedrock Claude3 invoke method to converse API (#5768) пре 1 година

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
    
  3. 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
    
  2. Start Dify web service.

  3. Setup your application by visiting http://localhost:3000...

  4. 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
    
  2. 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