A Python nearest neighbor descent for approximate nearest neighbors
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Updated
Oct 17, 2025 - Python
A Python nearest neighbor descent for approximate nearest neighbors
PECOS - Prediction for Enormous and Correlated Spaces
Pure python implementation of product quantization for nearest neighbor search
⚡ A fast embedded library for approximate nearest neighbor search
(distributed) vector database
A lightweight benchmark for approximate nearest neighbor search
A High-Efficiency System of Large Language Model Based Search Agents
🐍 Python bidding for the Hora Approximate Nearest Neighbor Search Algorithm library
Fast k-NN graph construction for slow metrics
Implementation of vector quantization algorithms, codes for Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search.
A Python package for hubness analysis and high-dimensional data mining
A pure Python-implemented, lightweight, server-optional, multi-end compatible, vector database deployable locally or remotely.
Hi. I am jann. I am text input - text output chatbot model that is JUST approximate nearest neighbour.
Bi-encoder Based Entity Linking Tutorial. You can run experiment only in 5 minutes. Experiments on Co-lab pro GPU are also supported!
Zero-shot Entity Linking with blitz start in 3 minutes. Hard negative mining and encoder for all entities are also included in this implementation.
Vector Index Benchmark for Embeddings (VIBE) is an extensible benchmark for approximate nearest neighbor search methods, or vector indexes, using modern embedding datasets.
🏘️ Hubness reduced nearest neighbor search for entity alignment with knowledge graph embeddings
Serverless, lightweight, and fast vector database on top of DynamoDB
An open source framework for Retrieval-Augmented System (RAG) uses semantic search helps to retrieve the expected results and generate human readable conversational response with the help of LLM (Large Language Model).
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