While everyone’s talking about building with LLMs, most developers are still staring at blank files wondering where to start. This collection cuts through the noise with actual working code - not just tutorials, but complete applications you can run, modify, and learn from. With nearly 100k stars, it’s become the go-to resource for developers who want to see LLMs in action across real use cases.
What sets this apart is the breadth and practicality. You’ll find everything from document chat systems using RAG to multi-agent workflows, voice interfaces, and apps that work with both cloud APIs (OpenAI, Anthropic, Gemini) and local open-source models like Llama and Qwen. Each example comes with clear documentation and covers different architectural patterns - perfect for understanding how to structure your own LLM applications.
Whether you’re a Python developer curious about AI or an ML engineer looking for production patterns, this repo saves you weeks of research. The code quality is solid, the examples are diverse, and the active community means you’ll find answers to implementation questions. Clone it, pick an app that matches your use case, and you’ll have a working prototype faster than you can say ‘artificial intelligence.’
⭐ Stars: 94884
💻 Language: Python
🔗 Repository: Shubhamsaboo/awesome-llm-apps