#Vector-search
Showing 60 of 213 repositories tagged #vector-search, ranked by stars
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Open Source AI Platform - AI Chat with advanced features that works with every LLM
The #1 AI Harness for Building Resumes, PDFs, Cover Letters & more, locally with 100+ LLMs support.
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
A vector index built on TurboQuant, written in Rust with Python bindings
Refine high-quality datasets and visual AI models
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
The Fastest Distributed Database for Transactional, Analytical, and AI Workloads.
Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from scratch. Unified architecture on your S3.
Semantic cache for LLMs. Fully integrated with LangChain and llama_index.
TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies.
The AI search platform
Superduper: End-to-end framework for building custom AI applications and agents.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.
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.
Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-flow, interactive HTML viewer, cross-project & branch-aware search, DB/API/infra knowledge. 61% less tokens, 84% fewer calls, 37x faster. Cloud in beta.
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
AI agent microservice
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).
🧠 AI-powered enterprise search engine 🔎
All-in-one platform for search, recommendations, RAG, and analytics offered via API
🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
Distributed vector search for AI-native applications
Open-source inference server and production cluster for all the models your agent needs.
Build LLM-powered applications in Ruby
An document retrieval project built on SAG
SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.
SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go 📐
Semantic Search & Call Graphs for AI Agents (100% Local)
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
JVector: the most advanced embedded vector search engine
Template for building your own custom ChatGPT style doc search powered by Next.js, OpenAI, and Supabase.
Collections of vector search related libraries, service and research papers
Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️
🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
A @ClickHouse fork that supports high-performance vector search and full-text search.
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
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.
ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.
Rust library for generating vector embeddings, reranking locally!
RAG-Fusion: multi-query generation + Reciprocal Rank Fusion for better retrieval-augmented generation. Includes evaluation harness with NFCorpus/BEIR.
This repository shares end-to-end notebooks on how to use various Weaviate features and integrations!
RAG Time: A 5-week Learning Journey to Mastering RAG
Epsilla is a high performance Vector Database Management System
Nornicdb is a distributed low-latency, Graph+Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Using Neo4j Bolt/Cypher and qdrant's gRPC means you can switch with no changes while adding intelligent features like schemas, managed embeddings, reranking+llm, GPU accel, Auto-TLP, Policy-based Memory Decay, and MCP server.
cuVS - a library for vector search and clustering on the GPU
Embeddable, in-memory, document-oriented database with a high-level Query builder interface.
Single-file memory layer for AI agents, sub mili-second RAG on Apple Silicon. Metal Optimized On-Device. No Server. No API. One File. Pure Swift
NucliaDB, The AI Search database for RAG
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 🗄️
TypeScript AI agent framework: cognitive memory, runtime tool forging, multi-agent orchestration, 11 LLM providers.
Use ArXiv ChatGuru to talk to research papers. This app uses LangChain, OpenAI, Streamlit, and Redis as a vector database/semantic cache.
Deprecated historical repo. Superlinked now develops SIE, a self-hosted inference engine for embeddings, reranking, OCR, extraction, and document processing.