Mastering Graph-Rag Foundations: Unlocking Retrieval-Augmented Generation with Knowledge Graphs, Vector Search & Llms

By finn cordex

Unlock the full power of Retrieval-Augmented Generation (RAG) with knowledge graphs, vector search, and large language models (LLMs) in this definitive guide for AI engineers, developers, and data scientists.

Mastering Graph-RAG Foundations takes you from conceptual understanding to practical mastery, offering a structured, hands-on approach to designing AI systems that can intelligently retrieve, reason, and generate knowledge. Whether you're building advanced chatbots, knowledge-intensive agents, or production-grade AI workflows, this book equips you with the tools and frameworks you need to succeed.

Inside, you'll discover:

How knowledge graphs enhance RAG workflows for accurate and context-aware AI outputs.

Step-by-step guidance on vector search, embeddings, and LLM integration.

Hands-on Python and LangGraph examples to implement real-world RAG systems.

Practical insights into designing scalable, maintainable AI architectures.

Expert commentary, best practices, and caveats from a senior AI engineer's perspective.

Designed for advanced learners and technical professionals, this book bridges the gap between theory and practice. Start your journey to mastering Graph-RAG today and unlock new levels of AI system intelligence and reliability.

• Format: Paperback
• Language: English
• ISBN: B0G3QDZY5J
• ISBN13: 9798275850673
• Release Date: November 2025
• Publisher: Independently Published
• Length: 176 Pages
• Weight: 0.46 lbs.
• Dimensions: 0.4" x 5.5" x 8.5"