Shubhamsaboo/awesome-llm-apps

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

What it solves

AI 에이전트 및 RAG (Retrieval Augmented Generation) 애플리케이션을 위한 즉시 실행 가능한 템플릿 " cookbook "을 제공하여, 개발자가 일반적인 파이프라인, 에이전트 루프 또는 통합을 처음부터 다시 구축할 필요가 없도록 합니다.

How it works

이 저장소는 다양한 프로바이더에 종속되지 않는 독창적이고 독립적인 스타터 코드 템플릿 컬렉션을 포함하고 있습니다. 설정을 통해 다양한 LLM (Claude, Gemini, GPT, Llama, Qwen, 및 xAI) 간을 전환할 수 있습니다. 이 템플릿들은 멀티 에이전트 팀, 음성 AI, 그리고 Model Context Protocol (MCP) 통합을 포함한 다양한 모달리티와 아키텍처를 다룹니다.

Who it's for

빈 페이지에서 시작하지 않고, 빠르게 프로토타입을 만들고, 커스텀하고, 프로덕션급 LLM 애플리케이션을을 출시할 수 있는 개발자.

Highlights

  • Diverse Templates: Over 100 apps covering starter agents, advanced agents, always-on agents, multi-agent teams, and voice AI.
  • Broad LLM Support: Compatible with major providers like OpenAI, Google, Anthropic, and Meta.
  • Hassle-Free Setup: Designed to run in a few commands with

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SUMMARY:

A comprehensive cookbook of - 100+ ready-to-run AI agent and RAG templates that developers can clone and customize to ship production LLM apps.

BODY:

What it solves

It provides a " cookbook " of ready-to-run templates for AI agents and RAG (Retrieval Augmented Generation) applications, eliminating the need for developers to rebuild common pipelines, agent loops, or integrations from scratch.

How it works

The repository contains a collection of provider-agnostic, self-contained starter code templates that allowing users to switch between different LLMs (such as Claude, Gemini, GPT, Llama, Qwen, and xAI) via configuration.

Who it's for

Developers who want to quickly prototype, customize, and ship production-ready LLM applications without starting from a blank page.

Highlights

  • Diverse Templates: Over 100 apps covering starter agents, advanced agents, always-on agents, multi-agent teams, and voice AI.

  • Broad LLM Support: Compatible with major providers like OpenAI, Google, Anthropic, and Meta.

  • Hassle-Free Setup: Designed to a few commands with provided requirements files.

  • Specialized Categories: Includes dedicated sections for RAG pipelines, generative UI, autonomous game-playing agents, and LLM optimization tools.

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zh-TW Summary: 包含 100 多個即插即用的 AI Agent 與 RAG 範本的全面指南，開發者可以複製並自定義，以快速交付生產級的 LLM 應用程式。

zh-TW Body:

What it solves

它提供了一個針對 AI Agent 與 RAG (Retrieval Augmented Generation) 應用程式的即插即用範本「指南」，消除了開發者從頭開始重建常見的流水線、Agent 迴圈或整合的需要。

How it works

該儲存庫包含一系列原創、獨立的入門代碼範本，這些範本與供應商無關，允許用戶透過配置來切換不同的 LLM (例如 Claude, Gemini, GPT, Llama, Qwen, 和 xAI) 。這類範本涵蓋了各種模態與架構，包括多 Agent 團隊、語音 AI 以及 Model Context Protocol (MCP) 整合。

Who it's for

想要在不從空白頁面開始的情況下，快速原型化、自定義並交付生產級 LLM 應用程式的開發者。

Highlights

  • Diverse Templates: Over 100 apps covering starter agents, advanced agents, always-on agents, multi-agent teams, and voice AI.
  • Broad LLM Support: Compatible with major providers like OpenAI, Google, Anthropic, and Meta.
  • Hassle-Free Setup: Designed to run in a few commands with provided requirements files.
  • Specialized Categories: Includes dedicated sections for RAG pipelines, generative UI, autonomous game-playing agents, and LLM optimization tools.

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