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
191 results
📚 从零开始的向量数据库原理与实践教程，在线阅读地址：https://easy-vecdb.datawhale.cc/
An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.
Embedding Studio is a framework which allows you transform your Vector Database into a feature-rich Search Engine.
Super performant RAG pipelines for AI apps. Summarization, Retrieve/Rerank and Code Interpreters in one simple API.
Mercury - Train your own custom GPT. Chat with any file, or website.
Semantic Search on Wikipedia with Upstash Vector
Your Local Artificial Memory on your Device.
A dead-simple API to build LLM-powered apps
The Supabase of AI era. A modular, open-source backend for building AI-native software — designed for knowledge, not static data.
ChatWeb can crawl web pages, read PDF, DOCX, TXT, and extract the main content, then answer your questions based on the content, or summarize the key points.
Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.
Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database.
Postgres with GPUs for ML/AI apps.
A no-code RAG server that keeps answers in sync with your documents. Works with 8 vector databases. Built on Pathway.
The definitive guide to using Vector Search to solve your semantic search production workload needs.
Mimir - Fully open and customizable memory bank with semantic vector search capabilities for locally indexed files (Code Intelligence) and stored memories that are shared across sessions and chat contexts allowing worker agent to learn from errors in past runs. Includes Drag and Drop multi-agent orchestration
Neural Search
Weaviate vector database – examples
Powerful unsupervised domain adaptation method for dense retrieval. Requires only unlabeled corpus and yields massive improvement: "GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval" https://arxiv.org/abs/2112.07577
A curated list of awesome works related to high dimensional structure/vector search & database
In-memory vector store with efficient read and write performance for semantic caching and retrieval system. Redis for Semantic Caching.
The codebase for the book "AI-Powered Search" (Manning Publications, 2025) and associated "AI-Powered Search: Modern Retrieval for Humans & Agents" Maven course
A tiny embedding database in pure Rust.
24,543 repositories in the index in total.
