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High-performance retrieval augmented generation components for the AccuralAI ecosystem.

Project description

accuralai-rag

High-performance Retrieval Augmented Generation (RAG) utilities built for the AccuralAI orchestration ecosystem. The package provides:

  • Multi-vector embedding utilities with optional GPU + hybrid sparse support.
  • Intelligent chunking and metadata extraction helpers tuned for large documents.
  • Hybrid dense/sparse retrieval with reciprocal rank fusion and reranking hooks.
  • Query optimizers (HyDE, decomposition, semantic augmentation) plus advanced context builders.
  • UltraFastRAG pipeline that combines the components with aggressive caching and streaming-friendly hooks.

All heavy dependencies are optional. Install extras such as torch, transformers, faiss, or redis based on your production topology:

pip install -e packages/accuralai-rag[torch,transformers,faiss,redis]

See accuralai_rag/pipeline.py for the orchestrated entry point and tests/ for lightweight examples.

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