A factory for building advanced RAG (Retrieval-Augmented Generation) pipelines, including:
- Standard RAG implementations
- GraphRAG architectures
- Multi-modal RAG systems
- Modular design for easy customization
- Support for various knowledge graph backends
- Integration with multiple LLM providers
- Configurable pipeline components
pip install -e .
python main.py --config examples/graphrag/config.yaml
See the examples/
directory for sample configurations and usage.
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