Python toolkit for building production-ready LLM applications. Modular utilities for prompts, RAG, agents, structured outputs, and multi-provider support.
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Product Quantization for Nearest Neighbor Search, Hervé Jégou, Matthijs Douze, Cordelia Schmid, 2011IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33 (IEEE Computer Society)DOI: 10.1109/TPAMI.2010.57 - The foundational research paper that introduced Product Quantization, detailing its core principles, vector decomposition, codebook generation, and approximate distance computation methods.
Billion-scale similarity search with GPUs, Jeff Johnson, Matthijs Douze, Hervé Jégou, 2017arXiv preprint arXiv:1702.08734DOI: 10.48550/arXiv.1702.08734 - Describes the FAISS library, a highly optimized open-source tool that widely implements Product Quantization and its variants for efficient large-scale similarity search, providing practical context and implementation details.
Vector Embeddings, Kian Kulkarni and Kumar Praveen, 2024 (Packt Publishing) - A contemporary textbook providing a comprehensive overview of vector embeddings, approximate nearest neighbor search, and related algorithms like Product Quantization, highly relevant for LLM applications.