#Reranking
Showing 26 of 26 repositories tagged #reranking, ranked by stars
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
Open-source inference server and production cluster for all the models your agent needs.
๐ฅค RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
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!
Use late-interaction multi-modal models such as ColPali in just a few lines of code.
๐ฅ Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation ๐ฅ. Our toolkit integrates 40 pre-retrieved benchmark datasets and supports 7+ retrieval techniques, 24+ state-of-the-art Reranking models, and multiple RAG methods.
Is ChatGPT Good at Search? LLMs as Re-Ranking Agent [EMNLP 2023 Outstanding Paper Award]
Querying local documents, powered by LLM
YT Navigator: AI-powered YouTube content explorer that lets you search and chat with channel videos using AI agents. Extract insights from hours of content in seconds with semantic search and precise timestamps.
Java AI application development framework (supports LLM-tool,skill; RAG; MCP; Agent-ReAct,Team-Agent). Compatible with java8 ~ java25. It can also be embedded in SpringBoot, jFinal, Vert.x, Quarkus, and other frameworks.
A LLM RAG system runs on your laptop. ๅคงๆจกๅๆฃ็ดขๅขๅผบ็ๆ็ณป็ป๏ผๅฏไปฅ่ฝปๆพ้จ็ฝฒๅจ็ฌ่ฎฐๆฌ็ต่ไธ๏ผๅฎ็ฐๆฌๅฐ็ฅ่ฏๅบๆบ่ฝ้ฎ็ญใ
Hybrid RAG system combining vector search, knowledge graph (LightRAG), and cross-encoder reranking โ with Docling document parsing, visual intelligence (image/table captioning), agentic streaming chat, and inline citations. Powered by Gemini or local Ollama models.
llama.cpp (GGUF LLMs) and llava.cpp (GGUF VLMs) for ROS 2
Local RAG MCP server for Claude Code โ hybrid search (semantic + BM25), cross-encoder reranking, 13 MCP tools, 20 format parsers. Zero external servers, zero API keys.
See how to augment LLMs with real-time data for dynamic, context-aware apps - Rag + Agents + GraphRAG.
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.
This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.
RAG boilerplate with semantic/propositional chunking, hybrid search (BM25 + dense), LLM reranking, query enhancement agents, CrewAI orchestration, Qdrant vector search, Redis/Mongo sessioning, Celery ingestion pipeline, Gradio UI, and an evaluation suite (Hit-Rate, MRR, hybrid configs).
Official repository of ICCV21 paper "Viewpoint Invariant Dense Matching for Visual Geolocalization"
Codebase Context gives AI agents understanding of your codebase through semantic code search, team conventions, patterns, and memory, so they use fewer tokens, spend less time, and produce better, more familiar output.
A post-retrieval temporal layer for RAG systems โ validity filtering, time decay, document kind classification, and hybrid reranking in one pipeline.
The ultimate memory backend for OpenClaw and Claude Code. Persistent conversation memory with LLM fact extraction, foundation-model reranking, and 77.7% LoCoMo accuracy. MCP native, REST API, self-hosted.
LightweightEmbeddings is a fast, free, and unlimited API service for multilingual embeddings and reranking, with support for both text and images and guaranteed uptime.
Boilerplate RAG System with LangGraph Architecture
Hybrid RAG (DuckDB vector + BM25 + RRF + recency/keyword priors + optional cross-encoder rerank) as an installable library + CLI.