Built a page RAG field manual while studying for Azure AI-103 if Any one preparing for AI-103 (.NET-flavored)
I was studying RAG for Microsoft's AI-103 cert and kept losing track of how all the pieces actually connect ingestion, chunking, embeddings, vector DB, retrieval, augmentation, generation, the agent , eval. Most of the reference material out there is written from a Python/LangChain angle, and I'm coming at this from the .NET/Azure world, and I like visuals/structured learning.
It's a static HTML page covering the whole pipeline end to end, with a free/open-source alternative called out at each step not just the usual Pinecone/OpenAI defaults.
Mainly built it to learn figured it might be useful to anyone else piecing RAG together, especially if you're coming from a non-Python background. Feedback welcome, especially if I got a tradeoff wrong somewhere.