仓库/Skill 库

一个用于构建 AI Agent 的 Python 库，可充分发挥 Google Antigravity 的全部能力。A Python library for building AI agents that leverage the full power of Google Antigravity.

Neo.mjs 是一个自演化的软件生命体：一支端到端的 AI 工程团队，其跨模型集群通过 Neural Link、Active Hybrid GraphRAG、DreamService 与自愈回路栖身于实时应用中。Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.

快速、准确、轻量的 Python 库，用于构建 SOTA embeddingFast, Accurate, Lightweight Python library to make State of the Art Embedding

AI Agent 的通用记忆层。提供可扩展、可互操作的记忆存储与检索，为下一代自主系统简化 AI agent 状态管理。Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.

一个精简且可定制的高效大模型（LLM、VLM、AIGC）评估与性能基准测试框架。A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.

学习使用 LLM、agent、RAG、微调、LLMOps 和 AI 系统技术构建你的 Second Brain AI 助手。Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.

开源推理服务器与生产级集群，支持 Agent 所需的全部模型Open-source inference server and production cluster for all the models your agent needs.

深度对接你的 Zotero 库的研究 Agent 系统。An open-sourced research agent system deeply rooted in your Zotero library.

生成式AI综合资源，包含详细路线图、项目、用例、面试准备与编码练习Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.

Apache Hamilton 帮助数据科学家和工程师定义可测试、模块化、自文档化的数据流，内置 lineage/tracing 与 metadata，可在任何支持 Python 的环境中运行和扩展。Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

AI 工程面试速查表——问题与答案Your Cheat Sheet for AI Engineering Interview – Questions and Answers.

代码探索场景下削减AI token成本95%以上。基于tree-sitter AST实现精准符号级GitHub代码检索的主流MCP服务器，兼容Claude Code、Cursor及任何MCP客户端，已节省313B+ tokensCut AI token costs 95%+ on code exploration. The leading MCP server for precise, symbol-level GitHub code retrieval via tree-sitter AST. Works with Claude Code, Cursor & any MCP client. 313B+ tokens saved.

像构建 API 和微服务一样构建、运行和扩展 AI Agent。Build, run and scale AI agents like API and microservices

RAG 领域新 SOTA —— 一种全新的原创检索架构，以及面向人类与 Agent 的开源知识库。A new SOTA for RAG — an original retrieval architecture and an open-source knowledge base for humans and agents.

国家法令信息MCP v4.4 | 法制处42个API → 9个MCP工具。法令·判例·条例·条约 + 多阶段研究(legal_research) + 精准分析(legal_analysis: 引文验证·判例存废·行为时法·影响图谱) | 42个韩国法律API → 9个MCP工具법제처 국가법령정보를 LLM에서 바로 조회하는 MCP 서버. 법령·판례·조례 검색과 인용 검증 | MCP server for Korean law — search statutes, precedents, and ordinances, and verify citations

MCP服务器，使AI助手能够与Google Gemini CLI交互，借助Gemini的大token窗口进行大文件分析与代码库理解MCP server that enables AI assistants to interact with Google Gemini CLI, leveraging Gemini's massive token window for large file analysis and codebase understanding

全球首个开源的企业级世界模型。World's first open-source enterprise world model.

NVIDIA AI Blueprint for video search and summarization（VSS）是一个 GPU 加速参考架构，用于构建具备实时验证告警、视觉问答与自动报告能力的视频分析 Agent。VSS Blueprint 采用 NVIDIA Cosmos 等视觉语言模型（VLM）、NVIDIA Nemotron 等 LLM，并结合 RAG 与 NVIDIA NIM。NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs.

由 GPT-5、GPT-4、o1、o3、Gemini、Claude、Ollama、DeepSeek、Perplexity、Grok、Bielik 驱动的桌面 AI Assistant，支持 chat、vision、voice、RAG、图像与视频生成、agents、tools、MCP、plugins、语音合成与识别、网页搜索、记忆、预设、assistants 等。Linux、Windows、Mac。Desktop AI Assistant powered by GPT-5, GPT-4, o1, o3, Gemini, Claude, Ollama, DeepSeek, Perplexity, Grok, Bielik, chat, vision, voice, RAG, image and video generation, agents, tools, MCP, plugins, speech synthesis and recognition, web search, memory, presets, assistants,and more. Linux, Windows, Mac

AI Agents 喜爱的 Memory 方案！Memory that AI Agents Love!

收录 AIGC 领域 RAG 的优秀论文。我们在论文 "Retrieval-Augmented Generation for AI-Generated Content: A Survey" 中提出了 RAG 基础、增强与应用分类法。Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".

WFGY 正迈向 WFGY 5.0 Polaris Protocol，面向 AI reasoning、RAG、agents 与真实工作流的重要开源版本，包含 Problem Map、Global Debug Card、WFGY 4.0 与 CFV Easter EggWFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.

2026 年 AI Agent 研究论文精选合集，涵盖 agent 工程、记忆、评测、workflow 与自主系统。A curated collection of AI agent research papers released in 2026, covering agent engineering, memory, evaluation, workflows, and autonomous systems.

用于构建生产级Agent系统的Go框架，涵盖图工作流、工具、记忆、A2A、AG-UI、MCP、评估与可观测性A Go framework for building production agent systems with graph workflows, tools, memory, A2A, AG-UI, MCP, evaluation, and observability.

开源、端到端的 LLM 与 AI agent 应用评估、观测与改进平台。Tracing · Evals · Simulations · Datasets · Gateway · Guardrails。可自托管，Apache 2.0 许可。Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.

后端 Agent 构建工具 —— 多模态数据库、编排与服务，一个文件搞定The backend agents build with - Multimodal database, orchestration, and serving in one file

Daily updated LLM papers. 每日更新 LLM 相关的论文，欢迎订阅 👏 喜欢的话动动你的小手 🌟 一个

基于 Rust 🦀 构建的高性能、模块化、内存安全、生产可用的推理、数据接入与索引系统Highly Performant, Modular, Memory Safe and Production-ready Inference, Ingestion and Indexing built in Rust 🦀

基于 OpenSearch 构建的开源、自托管企业及站内搜索服务器，爬取网页、文件、数据库与云端数据源，支持 20+ 语言、REST API，以及 AI/RAG 与语义搜索。Apache-2.0。Open-source, self-hosted enterprise & site search server built on OpenSearch. Crawls web / file / DB / cloud sources, 20+ languages, REST API, and AI/RAG & semantic search. Apache-2.0.

Rust 库，用于本地生成向量 embedding 和重排序！Rust library for generating vector embeddings and reranking locally!

为你的 AI agent 装上看 PDF 的眼睛——通过 MCP 提供结构化文本、表格、OCR、视觉证据和页级引用。原生 Rust，本地优先。Give your AI agent eyes for PDFs — structured text, tables, OCR, visual evidence, and page-level citations via MCP. Native Rust, local-first.

开源、本地优先的写作工作空间，可使用 Claude Code 和 Codex 进行写作，并参考你自己的资料与过往工作。An open-source, local-first writing workspace where you can write with Claude Code and Codex, drawing on your own sources and past work.

🧩 FrontierAgent，我们的 agent 框架，与之同步开源——原生命令行 TUI，支持 ReAct 与 Agent Team 模式，macOS 与 Linux 上一条命令即可运行，无需预装，无强 Docker 依赖。🧩 FrontierAgent, our agent framework, open-sourced alongside it — native command-line TUI, ReAct and Agent Team modes, one command on macOS and Linux, no preinstall, no hard Docker dependency.

基于 Next.js、LangChain、PostgreSQL + pgvector 构建的 AI 驱动的初创企业加速引擎。可上传、组织并与文档对话。包含预测性缺失文档检测、基于角色的工作流以及页面级洞察提取。AI-powered StartUp Accelerator Engine built with Next.js, LangChain, PostgreSQL + pgvector. Upload, organize, and chat with documents. Includes predictive missing-document detection, role-based workflows, and page-level insight extraction.

高性能且兼容 CommonMark 的 HTML 转 Markdown 转换器。由 Kreuzberg 团队维护。Kreuzberg 是一个以 Rust 为核心的快速多语言文档智能引擎，基于流式解析器与内置 OCR，支持从 98+ 文档格式中抽取结构化数据。High performance and CommonMark compliant HTML to Markdown converter. Maintained by the Kreuzberg team. Kreuzberg is a fast, polyglot document intelligence engine with a Rust core. It extracts structured data from 98+ document formats using streaming parsers and built-in OCR.

♾️ 基于 Spec Coding 的私有 Agent 集群。每个 Agent 拥有独立 GPU 加速桌面，可在完整私有 AI Stack 上运行 Claude、Codex、Gemini 及开源模型 ♾️♾️ Private Agent Fleet with Spec Coding. Each agent gets their own GPU-accelerated desktop. Run Claude, Codex, Gemini and open models on a full private AI Stack ♾️