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vector-similarity

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RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

  • Updated Oct 31, 2024
  • Cuda

Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.

  • Updated Nov 11, 2023
  • TypeScript

This code example shows how to make a chatbot for semantic search over documents using Streamlit, LangChain, and various vector databases. The chatbot lets users ask questions and get answers from a document collection. The code is in Python and can be customized for different scenarios and data.

  • Updated Sep 3, 2023
  • Jupyter Notebook

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