LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
A unified AI model hub for aggregation & distribution. It supports cross-converting various LLMs into OpenAI-compatible, Claude-compatible, or Gemini-compatible formats. A centralized gateway for personal and enterprise model management.
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
State-of-the-Art Embeddings, Retrieval, and Reranking
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.8, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM5.3, Gemma4, Llava, Phi4, ...) (AAAI 2025).
Enhanced LanceDB memory plugin for OpenClaw — Hybrid Retrieval (Vector + BM25), Cross-Encoder Rerank, Multi-Scope Isolation, Management CLI
MTEB: State-of-the-art evaluation of embeddings across languages and modalities
Open-source inference server and production cluster for all the models your agent needs.
Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali
🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
Rust library for generating vector embeddings and reranking locally!
Nornicdb is a distributed low-latency, Graph+Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Using Neo4j Bolt/Cypher and qdrant's gRPC means you can switch with no changes while adding intelligent features like schemas, managed embeddings, reranking+llm, GPU accel, Auto-TLP, Policy-based Memory Decay, and MCP server.
Open-source infrastructure that turns scattered SKILL.md files into curated, retrieval-ready agent-skill corpora—with retrieval and evaluation tooling included.
RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking.
Agentic RAG for local and self-hosted document search: hybrid retrieval, reranking and multimodal RAG on embedded LanceDB, with Docling parsing and an MCP server
中文优先的企业 RAG 知识库:可控解析、治理、切块、混合检索、重排、引用、图谱、评测与 Dify 接入。
Inference engine for Intel devices. Serve LLMs, VLMs, Whisper, Kokoro-TTS, Embedding and Rerank models over OpenAI endpoints.
Deprecated historical repo. Superlinked now develops SIE, a self-hosted inference engine for embeddings, reranking, OCR, extraction, and document processing.
RAG ReAct Agent - A Retrieval-Augmented Generation system with ReAct (Reasoning+Acting) agent loop for intelligent question answering with multi-hop reasoning
OpenContextEngine is a self-hosted, ACE-compatible code retrieval service. It indexes source files with cAST-aware chunking, stores metadata in PostgreSQL or SQLite, performs dense vector retrieval in Milvus 3.0, and reranks results with an LLM before coverage-aware selection.
专为生产环境设计的 RAG 运维助手。核心采用父子块检索策略与稀疏/稠密混合检索机制,集成 BGE-M3 与 Reranker 本地模型,支持多跳故障推理、主动追问及知识溯源。
Local document Q&A in your terminal — powered by on-device LLMs.
Local VS Code search across Claude Code, Codex, and OpenCode chats with Laya reranking
一个开箱即用的完整智能客服服务:基于 FastAPI + LangChain RAG + CrewAI 多 Agent 构建, 提供意图识别路由、知识库问答、多智能体协作、SSE 流式对话等核心客服能力,并内置 检索工程(BM25+RRF+reranker)、稳定性工程(重试/限流/语义缓存)、可观测性(实时监控控制台) 与效果评估体系(RAGAS 评测闭环),可直接部署上线,也可作为独立 AI 服务被现有业务系统(如 Spring Cloud / Node.js 后端)通过 HTTP/SSE 集成调用。
Full-stack multimodal product retrieval and personalized reranking with CLIP, FAISS, Spring Boot, FastAPI, and PostgreSQL.
本地私有化智能文档问答系统:BM25+向量混合检索、本地 Rerank 重排、完全离线、数据零外传(LangChain + Ollama + ChromaDB)
AdalFlow Alternative 2026: Auto-Optimize LLM Apps Without Code
Build & Auto-Optimize LLM Apps in 2026: The Ultimate AdalFlow Guide
Sniff out the right record: Jev-powered search for Rails with index-time labels, query understanding, and streamed reranking on top of your own keyword and embedding search
Typed judgment tools for MCP agents. TypeSafe's Jev model as verify, screen, find, classify, rerank, decide, compare, extract, review, gate, and score: the model judges, policy decides auto, review, or escalate.
Jev-powered relevance filtering and reranking for RAG in Python.
Zero-dependency local-first AI memory engine: graph memory, multimodal ingestion, reranking, temporal reasoning, hash-chained ledger, capsule compression, memory formation + runtime layers. 52 MCP tools (41 native + 11 compatible). MIT.
Small System One decision models (17M–400M) for Yes/No, Choice, Score, and reranking. Training toolkit, Python inference, and ONNX support for Node.js and browsers.
Local AI Personal Knowledge Base Q&A · Full‑Link RAG Practical Implementation (Hybrid Retrieval + Rerank Fine‑Ranking + Citation‑Enabled Generation)
Reproducible benchmark and reference pipeline for reranked long-term memory retrieval