Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Storage and retrieval for embeddings: vector indexes, hybrid search and ANN libraries.
Signals: vector-database, vector-search, vector-store, similarity-search, approximate-nearest-neighbor, ann-search, faiss, hnsw
195 results
Deprecated historical repo. Superlinked now develops SIE, a self-hosted inference engine for embeddings, reranking, OCR, extraction, and document processing.
Go library for embedded vector search and semantic embeddings using llama.cpp
Multi-Modal Database replacing MongoDB, Neo4J, and Elastic with 1 faster ACID solution, with NetworkX and Pandas interfaces, and bindings for C 99, C++ 17, Python 3, Java, GoLang 🗄️
A Python vector database you just need - no more, no less.
Epsilla is a high performance Vector Database Management System
A repository of code samples for Vector search capabilities in Azure AI Search.
This repository shares end-to-end notebooks on how to use various Weaviate features and integrations!
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
A @ClickHouse fork that supports high-performance vector search and full-text search.
🕸️🦀 A WASM vector similarity search written in Rust
MemFree - Hybrid AI Search Engine & AI Page Generator
Collections of vector search related libraries, service and research papers
Template for building your own custom ChatGPT style doc search powered by Next.js, OpenAI, and Supabase.
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
Semantic Search & Call Graphs for AI Agents (100% Local)
A SQLite extension for efficient vector search, based on Faiss!
Distributed vector search for AI-native applications
🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
🧠 AI-powered enterprise search engine 🔎
Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).
LakeSoul is an end-to-end, realtime cloud-native Lakehouse framework for fast data ingestion, concurrent updates, incremental analytics, multimodal data processing and vector search — powering next-generation BI and AI workloads.
A distributed approximate nearest neighborhood search (ANN) library which provides a high quality vector index build, search and distributed online serving toolkits for large scale vector search scenario.
Semantic cache for LLMs. Fully integrated with LangChain and llama_index.
A vector index built on TurboQuant, written in Rust with Python bindings
24,523 repositories in the index in total.
