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.vscode f62f71a81a build: initial support for poetry build tool (#4513) 10 months ago
configs 6a09409ec9 Add Oracle23ai as a vector datasource (#5342) 10 months ago
constants 6ccde0452a feat: Added hindi translation i18n (#5240) 10 months ago
controllers 6a09409ec9 Add Oracle23ai as a vector datasource (#5342) 10 months ago
core 6a09409ec9 Add Oracle23ai as a vector datasource (#5342) 10 months ago
docker 5f0ce5811a feat: add `flask upgrade-db` command for running db upgrade with redis lock (#5333) 10 months ago
events d160d1ed02 feat: support opensearch approximate k-NN (#5322) 10 months ago
extensions 3cc6093e4b feat: introduce pydantic-settings for config definition and validation (#5202) 10 months ago
fields 92ddb410cd feat: option to hide workflow steps (#5436) 10 months ago
libs 1336b844fd feat(api/auth): switch-to-stateful-authentication (#5438) 10 months ago
migrations 92ddb410cd feat: option to hide workflow steps (#5436) 10 months ago
models 92ddb410cd feat: option to hide workflow steps (#5436) 10 months ago
schedule 6c4e6bf1d6 Feat/dify rag (#2528) 1 year ago
services 1336b844fd feat(api/auth): switch-to-stateful-authentication (#5438) 10 months ago
tasks ba5f8afaa8 Feat/firecrawl data source (#5232) 10 months ago
templates 3d92784bd4 fix: email template style (#1914) 1 year ago
tests 6a09409ec9 Add Oracle23ai as a vector datasource (#5342) 10 months ago
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.env.example 147a39b984 feat: support tencent cos storage (#5297) 10 months ago
Dockerfile 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 10 months ago
README.md 9a5c423d59 chore: remove pip support for api service (#5453) 10 months ago
app.py 1336b844fd feat(api/auth): switch-to-stateful-authentication (#5438) 10 months ago
commands.py d160d1ed02 feat: support opensearch approximate k-NN (#5322) 10 months ago
config.py 65d34ebb96 refactor: extract vdb configs into pydantic-setting based dify configs (#5426) 10 months ago
poetry.lock 6a09409ec9 Add Oracle23ai as a vector datasource (#5342) 10 months ago
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 months ago
pyproject.toml 6a09409ec9 Add Oracle23ai as a vector datasource (#5342) 10 months ago
requirements.txt 9a5c423d59 chore: remove pip support for api service (#5453) 10 months ago

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
    

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