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patchy631/ai-engineering-hub

patchy631 · personal account · GitHub id 38653995
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In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

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40k
Velocity
54.1★/day
Forks
6.5k
Language
Jupyter Notebook
Created
2024-10-21 (2y)
Last push
2026-11-01
Category
agents
GitPump score
96/100
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In short

AI Engineering Hub is a GitHub collection of Jupyter Notebook-based tutorials and sample projects covering large language models, retrieval-augmented generation (RAG), and AI agent applications. The projects are organized into beginner, intermediate, and advanced tiers, with beginner examples including local OCR apps, chat interfaces built on open models such as Llama, Gemma, Qwen, and DeepSeek, and basic RAG pipelines using frameworks like LlamaIndex and Qdrant. Intermediate entries cover multi-agent workflows built with tools such as CrewAI and AutoGen, agentic RAG designs, and agents with external memory

Written by GitPump research from the repo’s public material. The full text follows below.

README · straight from GitHub

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AI Engineering Hub Banner


AI Engineering Hub 🚀

Welcome to the AI Engineering Hub - your comprehensive resource for learning and building with AI!

🌟 Why This Repo?

AI Engineering is advancing rapidly, and staying at the forefront requires both deep understanding and hands-on experience. Here, you will find:

  • 93+ Production-Ready Projects across all skill levels
  • In-depth tutorials on LLMs, RAG, Agents, and more
  • Real-world AI agent applications
  • Examples to implement, adapt, and scale in your projects

Whether you're a beginner, practitioner, or researcher, this repo provides resources for all skill levels to experiment and succeed in AI engineering.


📋 Table of Contents


🎯 Getting Started

New to AI Engineering? Start here:

  1. Complete Beginners: Check out the AI Engineering Roadmap for a comprehensive learning path
  2. Learn the Basics: Start with Beginner Projects like OCR apps and simple RAG implementations
  3. Build Your Skills: Move to Intermediate Projects with agents and complex workflows
  4. Master Advanced Concepts: Tackle Advanced Projects including fine-tuning and production systems

📬 Stay Updated with Our Newsletter!

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🎓 Projects by Difficulty

🟢 Beginner Projects

Perfect for getting started with AI engineering. These projects focus on single components and straightforward implementations.

OCR & Vision

  • LaTeX OCR with Llama - Convert LaTeX equation images to code using Llama 3.2 vision
  • Llama OCR - 100% local OCR app with Llama 3.2 and Streamlit
  • Gemma-3 OCR - Local OCR with structured text extraction using Gemma-3
  • Qwen 2.5 OCR - Text extraction using Qwen 2.5 VL model

Chat Interfaces & UI

Basic RAG

Multimodal & Media

Other Tools


🟡 Intermediate Projects

Multi-component systems, agentic workflows, and advanced features for experienced practitioners.

AI Agents & Workflows

Voice & Audio

Advanced RAG

Multimodal

MCP (Model Context Protocol)

Model Comparison & Evaluation


🔴 Advanced Projects

Complex systems, fine-tuning, production deployments, and cutting-edge implementations.

Fine-tuning & Model Development

Advanced Agent Systems

Advanced MCP & Infrastructure

Production Systems

Learning Resources


📢 Contribute to the AI Engineering Hub!

We welcome contributors! Whether you want to add new tutorials, improve existing code, or report issues, your contributions make this community thrive. Here's how to get involved:

  1. Fork the repository
  2. Create a new branch for your contribution
  3. Submit a Pull Request and describe the improvements

Check out our contributing guidelines for more details.


📜 License

This repository is licensed under the MIT License - see the LICENSE file for details.


💬 Connect

For discussions, suggestions, and more, feel free to create an issue or reach out directly!

Happy Coding! 🎉