awesome-llm-apps

ShubhamsabooApache-2.0活跃维护 有专家点评

收录 100 多个可直接上手的 AI Agent、Agent Skills 和 RAG 应用示例,帮开发者快速找到能跑起来的 LLM 项目参考。

100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.

暂无版本144,370star +303 / 7 天21,238fork同步于 2026-11-10 23:18 UTC

专家点评

上手难度:入门更新于 2026-11-11

一个按目录切分的 Agent/RAG 示例代码库,用来抄结构而不是当依赖装

适用场景

  • 需要快速验证某个 Agent 模式(多 Agent 协作、后台常驻、语音)能不能跑通:挑对应目录 cd 进去装依赖就能看到端到端流程,比从零搭骨架省掉脚手架时间
  • 给团队新人做 LLM 应用入门材料:单文件 Agent 加一个 API key 就能跑,不用先讲清楚框架抽象
  • 选型阶段横向对比同一任务在不同模型上的表现:模板本身模型无关,改 key 和 model 名就能换后端,不用重写调用层
  • 想给 Cursor/Claude Code 这类编码 Agent 加技能:agent_skills 目录走 npx skills add,比手写 prompt 片段更成体系

踩坑

  • 每个模板是独立目录、独立 requirements.txt,没有顶层统一依赖管理;想批量跑多个模板时会撞上依赖版本互相冲突,得一个目录一个 venv
  • 这是示例集合不是库,没有 API 稳定性承诺;issue 里出现的是收录请求、凭据报错这类杂项,说明维护重心在扩目录而非修单个模板,别指望某个模板长期跟进上游 SDK 变更
  • 多数模板要自备对应模型的 API key,且部分示例默认模型和你的可用额度不一定对得上,第一次跑通前要逐个确认配置项

同类对比

要的是可依赖的 RAG 框架而非示例,看 LlamaIndex 或 LangChain;要开箱即用的 Agent 运行时编排,看 Agno、CrewAI 这类有版本语义的项目。这个仓库的定位是参考实现,不是被 import 的依赖。

怎么上手

由 README 提炼,执行前请确认
npx skills add https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/agent_skills/project-graveyard
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git && cd awesome-llm-apps/starter_ai_agents/ai_travel_agent && pip install -r requirements.txt && streamlit run travel_agent.py
硬件要求按 README 说明

README 未说明

下载:源码 zip·GitHub Releases(安装包)本站不镜像安装包

项目说明

由 README 自动翻译提炼

100+ 个开源 AI Agent、Agent Skill 与 RAG 应用合集,克隆即用,可自由商用

收录 100 多个可直接上手的 AI Agent、Agent Skills 和 RAG 应用示例,帮开发者快速找到能跑起来的 LLM 项目参考。

核心能力

  • 收录 100+ 个手写并端到端测试过的 Agent 与 RAG 模板
  • 用 npx skills add 一条命令给编码 Agent 装新技能
  • 提供单文件入门 Agent,只需一个 API 密钥即可运行
  • 覆盖多 Agent 团队、常驻后台 Agent 与语音 Agent 等分类
  • 兼容 Claude、Gemini、GPT、DeepSeek、Llama、Qwen 等模型

容易踩的坑

每个模板是独立目录,需先 cd 进对应目录再安装各自的 requirements.txt;多数应用需要自备所调用模型的 API 密钥;Agent Skill 需配合 Claude Code、Codex、Cursor 等编码 Agent 使用

内容由模型根据 README 生成,可能不完整或不准确,以官方文档为准。看原文 README

最近发版

0 个版本

暂无 release 数据(可能没有发版,或尚未同步)。

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    README 原文

    未翻译

    Awesome LLM Apps

    100+ open-source AI agents, agent skills, and RAG apps. Hand-built, tested end-to-end, Apache-2.0.

    Clone it, ship it, sell it - 100% free and open-source

    Works with Claude, Gemini, GPT, DeepSeek, Llama, Qwen and other open-source models.

    Step-by-step tutorials on Unwind AI · Quick start · Browse all templates

    🚀 Run one now

    Give your coding agent a new skill in 10 seconds:

    npx skills add https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/agent_skills/project-graveyard
    

    Then ask it: "why do I never finish my side projects?"

    Or clone and run any agent in 30 seconds:

    git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
    cd awesome-llm-apps/starter_ai_agents/ai_travel_agent
    pip install -r requirements.txt
    streamlit run travel_agent.py
    

    📬 New templates drop weekly. Get them in your inbox on Unwind AI.

    📂 Browse all templates

    🧩 Agent Skills

    Give your coding agent new abilities. One command to install, plain English to use. Every skill ships real code and passes a security + eval CI gate. Works with Claude Code, Codex, Cursor, and other coding agents. Browse all skills →

    • ⚰️ Project Graveyard - Finds every side project you abandoned, tells you why each one died, and helps you finish the one worth going back to
    • 👁️ First Reader - Simulates real readers going through your draft and reports where they lose interest, where they stop reading, and what they remember afterward, without rewriting a word
    • 🔭 Scope Creep Detector - Checks whether a diff grew beyond its stated intent and recommends what to keep, split, or justify
    • 🏺 Commit Archaeologist - Reconstructs why a file or code region exists from its introducing commit, later edits, co-changes, and intent clues
    • 🩺 Dependency Doctor - Checks a dependency manifest for standard-library pins, obsolete backports, unpinned entries, duplicate constraints, and yanked releases
    • 🧠 Advisor Orchestrator Worker - Meta Loop with Claude Fable 5.1 as advisor, GPT-6 Astra as orchestrator, and Gemini 3.8 Flash as worker
    • 🎙️ Thinking Out Loud - Echoes a voice ramble back as a scannable brief, with the model's guesses quarantined and your reversals flagged
    • ♾️ Self-Improving Agent Skills - Automatically optimize agent skills using Gemini and ADK

    🛠️ Standalone Apps & Tools

    Standalone web apps, creative tools, and browser extensions for everyday workflows.

    🌱 Starter AI Agents

    Single-file agents that run with just an API key - a great place to start.

    🚀 Advanced AI Agents

    Production-style agents with tools, memory, and multi-step reasoning.

    🛰️ Always-on Agents

    Background agents that run on schedules or events, monitor changing context, decide what needs attention, and proactively deliver updates, artifacts, or actions.

    🤝 Multi-agent Teams

    Multiple agents collaborating to accomplish complex, cross-domain tasks.

    🗣️ Voice AI Agents

    Speech-in, speech-out agents using real-time voice APIs.

    🖼️ Generative UI and Agentic Frontends

    Agents that render interactive UI components, not just text: forms, cards, charts, editable plans.

    🎮 Autonomous Game-Playing Agents

    Agents that play games end-to-end: reasoning, strategy, and action.

    ♾️ MCP AI Agents

    Agents that connect to external tools and data via Model Context Protocol.

    📀 RAG (Retrieval Augmented Generation)

    Retrieval pipelines, from simple chains to agentic and multi-source.

    💾 LLM Apps with Memory

    Agents and chatbots that remember conversations and user state across sessions.

    💬 Chat with X

    Turn any data source into a chat interface.

    🎯 LLM Optimization Tools

    Reduce token usage, context size, and API cost without losing quality.

    🔧 LLM Fine-tuning

    End-to-end fine-tuning recipes for open-source models.

    🧑‍🏫 AI Agent Framework Crash Courses

    Deep-dive tutorials on the major agent frameworks.

    • Google ADK Crash Course - Starter agent, structured outputs, tools (built-in, function, third-party, MCP), memory, callbacks, plugins, and multi-agent patterns. Model-agnostic.
    • OpenAI Agents SDK Crash Course - Starter agent, function calling, structured outputs, tools, memory, evaluation, handoffs, swarm orchestration, and routing logic.

    ⭐ Star the repo to get notified when new templates drop.

    Apache-2.0 · See LICENSE · Fork it, ship it, sell it.