🚨 The Problem: Context Fragmentation Imagine a 50-page legal contract. If you chunk it into tiny 200-character pieces, one chunk might say: "The liability is capped at $1M." Another chunk might say: "However, this cap does not apply to gross negligence." If your retriever only finds the first chunk, your AI will give a dangerously wrong answer because it lacks the Parent Context . 🧩 The Solution: Hierarchical Parenting Auto-merging retrieval organizes data into a tree structure. You store small Child Chunks (for high-precision searching) that are linked to larger Parent Chunks (for broad context). How it works: You index the document at multiple levels (e.g., small, medium, and large chunks). During retrieval, if the system finds that multiple child chunks belonging to the same parent have been retrieved, it "merges" them. Instead of sending the fragmented children to the LLM, it sends the entire Parent Chunk .…