Hands-On-Large-Language-Models vs awesome-llm-apps
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| Hands-On-Large-Language-Models | awesome-llm-apps | |
|---|---|---|
| Tagline | Code repository for Hands-On Large Language Models | 100+ AI Agent & RAG apps you can actually run — clone, customize, ship. |
| Stars | 27k | 117k |
| Forks | 6.4k | 17k |
| Open issues | 37 | 6 |
| Language | Jupyter Notebook | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last pushed | Apr 24, 2026 | Jun 15, 2026 |
| Categories | Developer Tools, LLM Frameworks | AI Agents, LLM Frameworks |
Hands-On-Large-Language-Models
This repository contains the code and Jupyter Notebook examples from Jay Alammar and Maarten Grootendorst’s O'Reilly publication 'Hands-On Large Language Models', providing practical insights into using Large Language Models.
Jupyter Notebook
awesome-llm-apps
A repository containing a collection of AI agent and Retrieval-Augmented Generation (RAG) applications that are ready to be cloned, customized, and deployed. The projects cover various aspects such as AI agents, always-on agents, multi-agent teams, RAG techniques, voice agents, fine-tuning for specific use cases, and more.
Python