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patchy631/ai-engineering-hub

A collection of 90+ hands-on tutorial projects covering LLMs, RAG pipelines, and AI agents, organized by difficulty level.

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What is it?

AI Engineering Hub is a collection of runnable tutorial projects for building with large language models. The projects are grouped into beginner, intermediate, and advanced tiers and cover topics such as local chat interfaces, OCR with vision models, retrieval-augmented generation over documents, audio and video RAG, and multi-agent workflows built with frameworks like CrewAI, LlamaIndex, and AutoGen.

A sizable share of the entries focus on MCP (Model Context Protocol) integrations, agent memory, and model comparisons such as evaluating reasoning models against each other. Many projects run against hosted APIs from providers like DeepSeek, Gemini, and AssemblyAI, while others use local models through Ollama.

Each project lives in its own folder with its own code, so readers can pick a single tutorial that matches their current skill level and run it independently.

Key features

  • 01Covers LLMs, RAG, and AI agents in one repository.
  • 02Projects are grouped into beginner, intermediate, and advanced tiers.
  • 03Includes OCR, voice, and multimodal RAG examples.
  • 04Features several MCP server and client implementations.
  • 05Each tutorial is self-contained in its own folder.

Use cases

  • Learning RAG by building a working document chat application.
  • Exploring how to wire up agent frameworks like CrewAI or AutoGen.
  • Comparing the output quality of different LLMs on the same task.
  • Finding a starting template for an MCP-based tool integration.

Things to know

  • The README gives no single install command; each project in the collection has its own setup.

In collections

Open-source AI agent frameworks & appsMCP servers

Topics

#llm#rag#ai-agents#tutorial#mcp#jupyter-notebook#machine-learning#agents#ai#llms

FAQ

What is ai-engineering-hub?
A collection of 90+ hands-on tutorial projects covering LLMs, RAG pipelines, and AI agents, organized by difficulty level. AI Engineering Hub is a collection of runnable tutorial projects for building with large language models. The projects are grouped into beginner, intermediate, and advanced tiers and cover topics such as local chat interfaces, OCR with vision models, retrieval-augmented generation over documents, audio and video RAG, and multi-agent workflows built with frameworks like CrewAI, LlamaIndex, and AutoGen.
Is ai-engineering-hub free to use? What license does it have?
ai-engineering-hub is open source under the MIT license. Check the license terms before using it in commercial products.
Is ai-engineering-hub still maintained?
Actively maintained. The last commit to ai-engineering-hub was on Nov 1, 2026.
What can I use ai-engineering-hub for?
Learning RAG by building a working document chat application. Exploring how to wire up agent frameworks like CrewAI or AutoGen. Comparing the output quality of different LLMs on the same task. Finding a starting template for an MCP-based tool integration.
Where can I get ai-engineering-hub?
The source code and installation instructions are on GitHub: https://github.com/patchy631/ai-engineering-hub

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