GenAI Essentials

A collection of Jupyter notebooks covering essential concepts in Generative AI and Large Language Models.

Getting Started

1. Install dependencies:

   python -m venv .venv
   source .venv/bin/activate  
   pip install -r requirements.txt
   

2. Work through the notebooks in this order:

   1. llm_security.ipynb - Security considerations and best practices for LLMs
   2. llm_tutorial.ipynb - Core LLM concepts and basic agent introduction
   3. local_rag.ipynb - Retrieval-Augmented Generation with local data
   4. multimodal_llms.ipynb - Vision-language models and document understanding
   5. agent_frameworks.ipynb - Deep dive into agent patterns and architectures
   6. mcp_integration/ - Model Context Protocol for AI tool integration

Learning Progression

The notebooks build on each other:

• Tutorial introduces agents with simple examples (taste/intro)
• RAG shows document-based retrieval and vector databases
• Agent Frameworks explores advanced patterns in depth (ReAct, Plan-Execute, Multi-agent) and includes RAG-enabled agents
• Multimodal demonstrates vision-enabled agents
• MCP Integration shows how to extend AI assistants with custom tools and security capabilities

Directory Structure

• ./data/ - Sample documents used for RAG demonstrations
  • ./data/markdowns/ - Content from https://github.com/notaspork/linuxexamples/tree/main/basic
• ./temp/ - Working directory for temporary files (created at runtime)
• ./chroma_llm_training/ - Vector database created by llm_tutorial.ipynb (generated at runtime)
• ./chromadb_store/ - Vector database created by local_rag.ipynb (generated at runtime)
• ./chroma_agents/ - Vector database created by agent_frameworks.ipynb (generated at runtime)
• ./mcp_integration/ - Model Context Protocol servers and configurations

Prerequisites

• Python 3.8+
• Jupyter Notebook or JupyterLab

Additional Resources

• Prompt Engineering Guide - Comprehensive guide to effective prompting techniques
• Ollama Models - Local model library for privacy-focused development
• code-review.md - Practical prompts for AI-assisted code review (PR reviews, file reviews, and repository audits)

License

See LICENSE file for details.