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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