Rust library for generating vector embeddings, reranking locally!
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Updated
May 30, 2026 - Rust
Rust library for generating vector embeddings, reranking locally!
Local code search combining BM25, vector similarity, and cross-encoder reranking. Parses 60+ languages with tree-sitter, runs entirely offline, and returns structured results with file paths, line ranges, and symbol metadata. Built in Rust.
Context retrieval engine for AI agents — semantic + lexical search over codebases
Embedded retrieval artifacts for Node, browsers, and Workers.
A Rust library for sparse vector indexing and retrieval, supporting optimized search, multi-threading, and C++ integration via FFI.
High-performance vector database & RAG memory layer - hybrid search, embeddings, RAPTOR trees, BM25 fusion for AI systems.
RedHop — a reasoning-aware retrieval & context runtime for RAG (in-process, no vector DB). Light weight alternative to langchain and llamaindex for retrieval alone.
Inference-aware runtime for AI coding agents that reuses execution state to reduce repeated reasoning, repo rereads, tool calls, and failure loops.
Local-first cross-corpus retrieval MCP server — model2vec embeddings + LanceDB (Tantivy BM25) + SQLite. One binary; hybrid (dense + BM25) search across markdown, code, and Claude Code sessions.
🚀 Build memory and retrieval infrastructure for ReasonKit, enhancing data management and access for your applications with ease and efficiency.
🚀 Optimize AI context retrieval with OrionGraphDB, a powerful engine that respects token budgets and delivers diverse, relevant information seamlessly.
APEX-MEM: The strongest multi-dimensional memory system for AI agents. 5D memory, hybrid retrieval (BM25 + vector + graph), dreaming consolidation, APEX self-healing, MCP-native. Drop-in replacement and superset of OpenClaw's memory subsystem with 100% compatibility adapters for mem0 (49.9K stars), Letta (17K stars) and LangMem.
Fast local RAG in Rust. Index, query, verify.
A local-first retrieval engine that turns notes, docs, and code into a searchable knowledge base for humans and AI agents.
Experimental MCP memory server pairing a delta-encoded recognition trie with a concept store that binds surface forms across languages via temporal co-occurrence — "bush", "křoví", "茂み" collapse into one concept without a dictionary. Append-only commit layers record what was learned and when.
Local first semantic and hybrid BM25 grep / search tool for use by AI and humans!
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