Rust library for generating vector embeddings, reranking locally!
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Updated
May 4, 2026 - Rust
Rust library for generating vector embeddings, reranking locally!
Suite of tools containing an in-memory vector datastore and AI proxy
Drop docs, search instantly from Claude Code — 12 MCP tools, 20 format parsers, hybrid search + reranking. Zero servers, zero API keys, 100% local.
SQL-like query language and CLI for Qdrant vector search engine
The highest-scoring AI memory system ever benchmarked that isn't reliant on LLM reranking. And it's free & burns less tokens.
Give your AI Agent understanding of your codebase. A Rust CLI that turns your entire project into a single, optimized context file for Cursor, Antigravity, and Claude.
Chat with Lex! A RAG app, using HyDE with milvus DB for vector store, VLLM for LLM inference, and FastEmbed for Embeddings!
FastAPI backend for archive.ire.org
Generating embedding for 1000s of PDF Documents, in Qdrant using FastEmbed with distributed Computing in Ray
MedSage is a multimodal healthcare assistant that combines LLMs, vector search, and real-time reasoning to deliver fast, reliable medical insights. It supports symptom analysis, medical document Q&A, universal file RAG, multilingual interactions, and emergency SOS with live location.
A polars plugin for embedding DataFrames
A fast and simple local API for generating text embeddings.
⚡ Instantly index, deduplicate, and search your code, docs, and web content in a blazing-fast Qdrant vector DB for AI & RAG.
This project showcases how to use AWS Lambda Managed Instances with AI/ML capabilities for real-time customer analytics
🧠 Universal long-term memory for AI agents. GraphRAG-powered knowledge base with vector search + graph traversal. Privacy-first, local-only, MCP-compatible. Connect Claude, Copilot, or any AI assistant.
Hub repo for Claude Code related tools (Japanese distributions)
Using Qdrant, Fastembed, Google Cloud, OpenAI to build a Question Answer Cloud Based RAG System
A library to gather structured statistics on the source code files in a software repository, generate embeddings and store in a vector database.
In-memory vector store with FastEmbed integration for Python applications.
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