Hierarchical Chunking — Parent-Child Chunk Architecture for RAG

I will implement hierarchical chunking (parent-child chunk architecture) for your RAG system — indexing small child chunks for precise retrieval while returning larger parent chunks for comprehensive context generation, combining the retrieval precision of small chunks with the context richness of large chunks in the LLM's synthesis step. Hierarchical chunking addresses the fundamental chunking tradeoff — small chunks enable precise retrieval (the chunk most closely matching the query) but provide insufficient context for the LLM to generate a comprehensive answer; large chunks provide rich context but reduce retrieval precision; parent-child architecture delivers both simultaneously.

The implementation covers child chunk generation for precise indexing, parent chunk storage for context retrieval, retrieval pipeline that finds child chunks and returns parent context, LlamaIndex or custom implementation, and precision and answer quality comparison against flat chunking.