generative-ai

This repository is a learning hub rather than a tool. It has two parts. The documentation side lists a GenAI roadmap, an AI/ML roadmap, guides on LLM fundamentals, vector embeddings, prompt engineering, 25 AI design patterns, tech stacks, LLM provider comparisons, an advanced RAG decision flow chart, a project lifecycle guide and an enterprise production checklist, plus cloud guides for AWS, Azure and Vertex AI and interview question sets, including 90+ multi-agent questions.

The projects side holds runnable use cases. For RAG there is Advanced RAG with agentic, graph and multimodal variants and nine advanced patterns such as corrective RAG and hybrid search, and Cache-Augmented Generation. For agents there are CrewAI and LangGraph examples, 25 reasoning patterns (Chain-of-Thought, ReAct, Tree-of-Thought), an MCP example with web search, and a multi-agent content moderation system with a React frontend.

Other projects cover a PDF chatbot with memory using local models, a conversational analytics app (React, FastAPI, PostgreSQL), LLM provider and embedding comparisons, text-to-SQL, Neo4j graph Q&A, sentiment analysis, 16+ prompt engineering techniques, Prompt Guard using Meta's Llama Guard to detect injections, Gemini image generation, a Llama 4 multi-function app and an n8n guide. No licence is stated in the README text we have, so check the repository before reusing code. Last push was 2026-10-08. This review is based on the README and repository data; we have not run it ourselves.