🌟 Awesome LLM Apps

🌟 优秀的LLM应用

A curated collection of Awesome LLM apps built with RAG, AI Agents, Multi-agent Teams, MCP, Voice Agents, and more. This repository features LLM apps that use models from openai logoOpenAI , anthropic logoAnthropic, google logoGoogle, X logoxAI and open-source models like alibaba logoQwen or meta logoLlama that you can run locally on your computer.

一个精选的优秀LLM应用集合,这些应用构建于RAG(Retrieval Augmented Generation,检索增强生成)、AI Agents(人工智能代理)、Multi-agent Teams(多智能体团队)、MCP(Multi-Chain Pipeline,多链管道)、Voice Agents(语音代理)等技术之上。这个仓库收录了使用来自OpenAI、Anthropic、Google、xAI等公司的模型,以及Qwen或Llama等开源模型构建的LLM应用,您可以在本地计算机上运行它们。

🤔 Why Awesome LLM Apps?

🤔 为什么选择优秀的LLM应用?
  • 💡 Discover practical and creative ways LLMs can be applied across different domains, from code repositories to email inboxes and more.
  • 💡 探索LLM在不同领域(从代码仓库到电子邮件收件箱等)应用的实用且富有创造性的方式。
  • 🔥 Explore apps that combine LLMs from OpenAI, Anthropic, Gemini, and open-source alternatives with AI Agents, Agent Teams, MCP & RAG.
  • 🔥 探索结合了来自OpenAI、Anthropic、Gemini以及开源替代方案的LLM与AI Agents(人工智能代理)、Agent Teams(代理团队)、MCP(Multi-Chain Pipeline,多链管道)和RAG(Retrieval Augmented Generation,检索增强生成)的应用。
  • 🎓 Learn from well-documented projects and contribute to the growing open-source ecosystem of LLM-powered applications.
  • 🎓 从有良好文档记录的项目中学习,并为不断增长的LLM驱动应用程序的开源生态系统做出贡献。

📂 Featured AI Projects

📂 精选AI项目

AI Agents

AI Agents(人工智能代理)

🌱 Starter AI Agents

🌱 初级AI Agents(人工智能代理)

🚀 Advanced AI Agents

🚀 高级AI Agents(人工智能代理)

🎮 Autonomous Game Playing Agents

🎮 自主游戏代理 (Autonomous Game Playing Agents)

🤝 Multi-agent Teams

🤝 多代理团队 (Multi-agent Teams)

🗣️ Voice AI Agents

🗣️ 语音 AI 代理 (Voice AI Agents)

mcp logo MCP AI Agents

MCP AI 代理 (MCP AI Agents)

📀 RAG (Retrieval Augmented Generation)

📀 RAG (检索增强生成) (Retrieval Augmented Generation)

💾 LLM Apps with Memory Tutorials

💾 带有记忆的 LLM 应用教程 (LLM Apps with Memory Tutorials)

💬 Chat with X Tutorials

💬 与 X 聊天教程 (Chat with X Tutorials)

🎯 LLM Optimization Tools

🎯 LLM 优化工具 (LLM Optimization Tools)
  • 🎯 Toonify Token Optimization - Reduce LLM API costs by 30-60% using TOON format
  • 🎯 Toonify Token 优化 - 使用 TOON 格式减少 LLM API 成本 30-60% (Toonify Token Optimization - Reduce LLM API costs by 30-60% using TOON format)
  • 🧠 Headroom Context Optimization - Reduce LLM API costs by 50-90% through intelligent context compression for AI agents (includes persistent memory & MCP support)
  • 🧠 Headroom 上下文优化 - 通过智能上下文压缩 AI 代理减少 LLM API 成本 50-90% (包括持久内存和 MCP 支持) (Headroom Context Optimization - Reduce LLM API costs by 50-90% through intelligent context compression for AI agents (includes persistent memory & MCP support))

🔧 LLM Fine-tuning Tutorials

🔧 LLM 微调教程 (LLM Fine-tuning Tutorials)

🧑‍🏫 AI Agent Framework Crash Course

🧑‍🏫 AI 代理框架速成课程 (AI Agent Framework Crash Course)

google logo Google ADK Crash Course

Google ADK 速成课程 (Google ADK Crash Course)
  • Starter agent; model‑agnostic (OpenAI, Claude)
  • 启动代理;模型无关 (OpenAI, Claude) (Starter agent; model‑agnostic (OpenAI, Claude))
  • Structured outputs (Pydantic)
  • 结构化输出 (Pydantic) (Structured outputs (Pydantic))
  • Tools: built‑in, function, third‑party, MCP tools
  • 工具:内置、函数、第三方、MCP 工具 (Tools: built‑in, function, third‑party, MCP tools)
  • Memory; callbacks; Plugins
  • 记忆;回调;插件 (Memory; callbacks; Plugins)
  • Simple multi‑agent; Multi‑agent patterns
  • 简单多代理;多代理模式 (Simple multi‑agent; Multi‑agent patterns)

openai logo OpenAI Agents SDK Crash Course

OpenAI 代理 SDK 速成课程 (OpenAI Agents SDK Crash Course)
  • Starter agent; function calling; structured outputs
  • 启动代理;函数调用;结构化输出 (Starter agent; function calling; structured outputs)
  • Tools: built‑in, function, third‑party integrations
  • 工具:内置、函数、第三方集成 (Tools: built‑in, function, third‑party integrations)
  • Memory; callbacks; evaluation
  • 记忆;回调;评估 (Memory; callbacks; evaluation)
  • Multi‑agent patterns; agent handoffs
  • 多智能体模式;智能体切换 (agent handoffs)
  • Swarm orchestration; routing logic
  • 集群编排 (swarm orchestration);路由逻辑 (routing logic)