Semantic Chunking for RAG | How I Chunk Markdown for Better Retrieval

I walk through my markdown-aware chunking pipeline for RAG: UUID-based provenance, heading-stack parsing, paragraph-level chunks, code-fence handling, metadata separation, and stable chunk IDs for efficient re-embedding.

RAG, semantic chunking, markdown chunking, provenance, vector database, document ingest, Obsidian, local LLM, retrieval, embedding pipeline, hybrid retrieval

personal AI system, node graph, knowledge system, AI architecture, RAG system, Obsidian vault, semantic chunking, vector database, provenance, retrieval, runtime state, tool execution, local LLM, workflow architecture, system design

#RAG #SemanticChunking #AIBuildInPublic

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