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generative-ai

Notebook-based GenAI tutorials and example apps on RAG, agents and prompting

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Stars
2.6k
License
MIT
Last commit
Oct 2026
Language
Jupyter Notebook

Missed the latest GitHub check; these facts may be older.

Overview

A learning repository of Jupyter notebooks, PDF guides and small example projects on generative AI. Use cases include advanced RAG patterns, multi-agent systems with CrewAI and LangGraph, text-to-SQL, Neo4j graph Q&A, prompt engineering, and a React + FastAPI + PostgreSQL analytics app. It also links to the author's interactive learning site, AI-ML Companion.

Who it is for: Developers learning to build RAG, agent and prompting apps from examples

Strengths

  • Separate use-case folders for RAG, agents, MCP, text-to-SQL and prompting
  • Compares OpenAI, Gemini, Claude, Groq and local Ollama/HuggingFace models
  • PDF references for AI patterns, RAG decision flow, and AWS/Azure/Vertex AI
  • MIT license

Weaknesses

  • No single install path; each use-case folder has its own setup
  • Full interactive guides live on a separate site; some interview sets need Pro
  • README mixes in links to unrelated third-party coding-agent projects
  • No tagged releases, so examples are not pinned to a version

What it needs

  • Needs Jupyter, CrewAI, LangGraph, Neo4j, PostgreSQL, Ollama
  • Models: OpenAI, Gemini, Claude, Groq, Ollama

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