Development Setup¶

Set up a development environment for contributing.

Prerequisites¶

Python 3.10+
Docker
Git
uv (recommended) or pip

Clone Repository¶

git clone https://github.com/NomaDamas/AutoRAG-Research.git
cd AutoRAG-Research

Install Dependencies¶

# Using uv (recommended)
uv sync --all-extras --all-groups

# Using pip
pip install -e ".[dev,test]"

Start PostgreSQL¶

docker-compose up -d

Wait for PostgreSQL to be ready:

make docker-wait

Run Tests¶

# Full test suite
make test

# Quick tests (assumes PostgreSQL running)
make test-only

# Single test
uv run pytest tests/path/to/test_file.py::test_function_name -v

Code Quality¶

# Run all checks
make check

# Individual tools
uv run ruff check .
uv run ruff format .
uv run ty

Common Commands¶

Command	Description
`make install`	Create venv, install deps
`make check`	Run all code quality checks
`make test`	Full test with Docker lifecycle
`make test-only`	Run tests (PostgreSQL assumed running)
`make docs`	Build and serve docs locally
`make docker-up`	Start PostgreSQL container
`make docker-down`	Stop container

Test Markers¶

@pytest.mark.gpu       # Requires GPU
@pytest.mark.api       # Requires LLM/API calls
@pytest.mark.data      # Downloads external data
@pytest.mark.asyncio   # Async test

Directory Structure¶

autorag_research/
├── cli/                 # CLI commands
├── data/
│   └── ingestor/        # Dataset ingestors
├── evaluation/
│   └── metrics/         # Evaluation metrics
├── orm/                 # Database layer
│   ├── models/          # SQLAlchemy models
│   ├── repository/      # Data access
│   ├── service/         # Business logic
│   └── uow/             # Unit of Work
├── pipelines/
│   ├── retrieval/       # Retrieval pipelines
│   └── generation/      # Generation pipelines
├── config.py            # Configuration classes
├── executor.py          # Pipeline orchestration
└── util.py              # Utilities