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A good way to consume large “awesome” directories:

1. Start from your goal (e.g., “RAG eval”, “agent + DB”, “workflow UI”) and shortlist 3 repos.
2. Run at least one repo end-to-end and write down the exact commands + env vars you needed.
3. Extract only the pieces you trust (auth, vector store, tracing) and keep them as internal templates.

README excerpt (verbatim)

This repository is a comprehensive collection of 80+ practical examples, tutorials, and recipes for building powerful LLM-powered applications — including text agents, voice assistants, RAG apps, and MCP-backed tools. These projects serve as a guide for developers working with various AI frameworks and stacks.

📋 Table of Contents

• 🎓 Courses
• 🚀 Featured AI Apps
  • 🧩 Starter Agents
  • 🪶 Simple Agents
  • 🎙️ Voice Agents
  • 🗂️ MCP Agents
  • 🧠 Memory Agents
  • 📚 RAG Applications
  • 🔬 Advanced Agents
• 📺 Tutorials & Videos
• 🚀 Getting Started
• 🤝 Contributing

💎 Sponsors

A huge thank you to our sponsors for their generous support!

Web Data Platform

AI Inference Provider FAQ Q: Is this a single app? A: No—it is a curated directory that links to many runnable repositories. Q: How do I pick a repo to start? A: Pick by your target pattern and prefer active repos with clear setup docs. Q: Should I copy code directly? A: Use it as a reference: run once, then extract the minimal pattern you need.