How to Build RAG WITHOUT Vector Databases (Page Index Python Tutorial)

Описание: Vector databases, embeddings, chunking — what if you don't need ANY of it?

In this video, I build a RAG system from scratch using pure LLM reasoning and a semantic tree structure. No vector database. No embeddings. No LangChain.

🔥 What you'll learn:
→ Why traditional RAG pipelines are overengineered for most use cases
→ How to convert documents into semantic trees (page → paragraph → line)
→ Recursive reasoning: let the LLM focus on what matters
→ Full Python implementation with OpenAI + Llama 3.1
→ Side-by-side comparison with traditional RAG


💻 Code: https://github.com/3SigmaCode/PageInd...
PageIndex: https://docs.pageindex.ai/
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#RAG #VectorDatabase #LLM #Python #AIEngineering #DeepLearning #MachineLearning #RetrievalAugmentedGeneration