Rust library for generating vector embeddings and reranking locally!
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Updated
Sep 22, 2026 - Rust
Rust library for generating vector embeddings and 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.
High-quality search for AI-native applications.
Embedded retrieval library built on Parquet. Fast, efficient, and scalable.
🚀 100% local RAG system with one-command setup. Your data never leaves your server.
Context retrieval engine for AI agents — semantic + lexical search over codebases
Bounded, inspectable LLM inference pipelines from declared YAML — runs offline against Ollama or any OpenAI-compatible local server, emitting JSONL traces, inspect reports, and stable exit codes.
Run, quantize, and fine-tune LLMs on Apple Silicon. Pure Rust, no Python, no CUDA, no ONNX
Embedded retrieval artifacts for Node, browsers, and Workers.
Zero-token memory for LLM agents. Rust implementation of Zero-Mem (arXiv:2607.29377) with a Hermes Agent memory provider.
chew through any source into clean datasets! a fast ingestion, RAG & fine-tuning toolkit
A Rust library for sparse vector indexing and retrieval, supporting optimized search, multi-threading, and C++ integration via FFI.
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.
High-performance vector database & RAG memory layer - hybrid search, embeddings, RAPTOR trees, BM25 fusion for AI systems.
Late-interaction retrieval (ColBERT + PLAID) in one numpy file — nanoGPT-style, with a Rust SIMD kernel ladder
A local-first retrieval engine that turns notes, docs, and code into a searchable knowledge base for humans and AI agents.
Inference-aware runtime for AI coding agents that reuses execution state to reduce repeated reasoning, repo rereads, tool calls, and failure loops.
Local code retrieval for AI coding agents. Rust CLI and MCP server with indexing, compact context, and reproducible evaluation tools.
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