Jyong ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
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constants b399e8a359 fixed a typo and grammar error in sampled app (#5061) 1 سال پیش
controllers ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
core ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
docker c32c177e15 improvement: introduce Super-Linter actions to check style for shell script, dockerfile and yaml files (#1966) 1 سال پیش
events 0391282b5e fix: initialize site with customized icon and icon_background (#5227) 1 سال پیش
extensions d7fbae286a add aws s3 iam check (#5174) 1 سال پیش
fields 43c19007e0 fix: workspace member's last_active should be last_active_time, but not last_login_time (#4906) 1 سال پیش
libs ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
migrations ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
models ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
schedule 6c4e6bf1d6 Feat/dify rag (#2528) 1 سال پیش
services ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
tasks ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
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.dockerignore 220f7c81e9 build: fix .dockerignore file (#800) 2 سال پیش
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Dockerfile 55fc46c707 improvement: speed up dependency installation in docker image rebuilds by mounting cache layer (#3218) 1 سال پیش
README.md 8da035aac6 Update README.md (#5228) 1 سال پیش
app.py 8bca908f15 refactor: config file (#3852) 1 سال پیش
commands.py 4080f7b8ad feat: support tencent vector db (#3568) 1 سال پیش
config.py 4080f7b8ad feat: support tencent vector db (#3568) 1 سال پیش
poetry.lock 4080f7b8ad feat: support tencent vector db (#3568) 1 سال پیش
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 1 سال پیش
pyproject.toml ba5f8afaa8 Feat/firecrawl data source (#5232) 1 سال پیش
requirements-dev.txt 23498883d4 chore: skip explicit installing jinja2 as testing dependency (#4845) 1 سال پیش
requirements.txt 4080f7b8ad feat: support tencent vector db (#3568) 1 سال پیش

README.md

Dify Backend API

Usage

  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
    
  3. Create environment.

Dify API service uses Poetry to manage dependencies. You can execute poetry shell to activate the environment.

Using pip can be found below.

  1. Install dependencies

    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
    

Usage with pip

[!NOTE]
In the next version, we will deprecate pip as the primary package management tool for dify api service, currently Poetry and pip coexist.

  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
    
  3. Create environment.

If you use Anaconda, create a new environment and activate it

   conda create --name dify python=3.10
   conda activate dify
  1. Install dependencies

    pip install -r requirements.txt
    
  2. Run migrate

Before the first launch, migrate the database to the latest version.

   flask db upgrade
  1. Start backend:

    flask run --host 0.0.0.0 --port=5001 --debug
    
  2. Setup your application by visiting http://localhost:5001/console/api/setup or other apis...

  3. If you need to debug local async processing, please start the worker service.

    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

    pip install -r requirements.txt -r requirements-dev.txt
    
  2. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml

    dev/pytest/pytest_all_tests.sh