Show HN: RAG Architecture for optimizing retrieval volume/relevancy tradeoff
Gregoryy Wednesday, January 14, 2026
We propose a RAG architecture that uses hierarchical semantic chunking and graph-based context exclusion to maximize relevant information while minimizing the total volume of retrieved context.
The system recursively splits documents into a hierarchical tree structure and dynamically selects the most optimally-sized chunk from each branch by identifying and excluding redundant ancestors and descendants during the search process.
This approach ensures a higher relevant-to-total information ratio by retrieving diverse segments from across the document without including overlapping or nested chunks
Summary
NestedRAG is a Python library that provides a simple and intuitive interface for creating nested Directed Acyclic Graphs (DAGs) with Resource Allocation Groups (RAGs). The library aims to simplify the management of complex data processing workflows by allowing users to define and execute multi-level task dependencies within a nested structure.
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