ai-engineering-hub

AI Engineering Hub is an educational repository that gathers hands-on tutorials and example projects for building with large language models. The README organizes its material by difficulty rather than by framework, which makes it easy to pick an entry point. Beginner projects focus on single components: local OCR applications built on vision models, chat interfaces with visible reasoning, simple retrieval-augmented generation (RAG) pipelines over documents or GitHub repositories, and a few small utilities such as converting a website into an API or generating news summaries. Intermediate projects combine multiple components. They include agentic workflows for research, content planning, brand monitoring and booking; voice and audio applications such as real-time voice bots and meeting-note generators; more advanced RAG setups over spreadsheets, code and complex documents; multimodal RAG over audio and websites; a substantial set of Model Context Protocol (MCP) examples for web search, video, voice and data orchestration; and several side-by-side model comparison and evaluation projects. Advanced projects cover fine-tuning and reasoning-model construction, transformer implementation from scratch, multi-agent research and browser-automation systems, deeper MCP infrastructure integrations, production-oriented document pipelines, and a NotebookLM-style application with citations and generated audio. A roadmap document is provided as a learning path from Python basics to production AI.