This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
Build, run and scale AI agents like API and microservices
动手学Ollama,CPU玩转大模型部署,在线阅读地址:https://datawhalechina.github.io/handy-ollama/
HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance
PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
开箱即用的AI标书编写工具,标书AI生成工具,投标工具箱、知识库、标书查重、废标项检查,完全开源免费,欢迎使用
A new SOTA for RAG — an original retrieval architecture and an open-source knowledge base for humans and agents.
Distributed vector search for AI-native applications
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
Empowering RAG with a memory-based data interface for all-purpose applications!
VCP 部署在 AI 模型 API 与前端应用之间,是面向AGI OS开发和探索的工业级基建示范项目。通过统一指令协议、多层级持久化记忆、分布式插件引擎及多 Agent 协作框架,将原本“无状态、无记忆、无工具调用能力”的大语言模型,彻底改造成拥有永久自我意识、物理世界操作权及群体协作智能的完整智能体系统。
AI-powered cross-platform e-book reader with semantic search, RAG chat, local vector store, notes, TTS, and WebDAV sync.
Local-first AI job intelligence workbench for scraping roles, ranking fit, and generating tailored application materials.
Research project. A Memory solution for users, teams, and applications.
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