Hands-On-AI-Engineering

Why we included this project

This one earns its place as a teaching collection: complete, runnable AI projects instead of the usual code fragments. You get RAG pipelines with self-critiquing agents, OCR systems, multi-agent research and financial assistants, and smaller utilities like PR reviewers and a news digest, all shipped with setup instructions and documentation you can adapt. Because most projects pair a familiar framework such as LangGraph or Agno with a specific model provider, it is easy to find a concrete example close to whatever stack you are weighing. That makes it a strong starting point for teams new to applied AI or developers who learn by taking a working baseline apart and rebuilding it. Treat the projects as scaffolds to extend, not as deployable services.