[HN Gopher] RAG Without Vectors - Reasoning-Based RAG using Page...
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       RAG Without Vectors - Reasoning-Based RAG using PageIndex
        
       Traditional vector-based RAG often struggles with retrieval
       accuracy because it optimizes for similarity, not relevance. But
       what we truly need in retrieval is relevance, which requires
       reasoning. When working with professional documents that require
       domain expertise and multi-step reasoning, vector-based RAG and
       similarity search often fall short.  So we started exploring a more
       reasoning-driven approach to RAG. Reasoning-based RAG enables LLMs
       to think and reason their way to the most relevant document
       sections. Inspired by AlphaGo, we propose to use tree search to
       perform structured document retrieval.  We open-sourced one of the
       key components: PageIndex. PageIndex is a hierarchical Document
       Indexing system that builds search trees from long documents (like
       financial reports, regulatory documents, or textbooks), making them
       ready for reasoning-based RAG.  Some highlights:  - Hierarchical
       Structure: Organizes lengthy PDFs into LLM-friendly trees -- like a
       smart table of contents.  - Precise Referencing: Each node includes
       a summary and exact physical page numbers.  - Natural Segmentation:
       Nodes align with document sections, preserving context -- no
       arbitrary chunking.  We've used PageIndex for financial document
       analysis with reasoning-based RAG and saw significant improvements
       in retrieval accuracy compared to vector-based systems.  Would love
       any feedback -- especially thoughts on reasoning-based RAG, or
       ideas for where PageIndex could be applied!
        
       Author : vectify_AI
       Score  : 19 points
       Date   : 2025-04-10 18:37 UTC (4 hours ago)
        
       | casenmgreen wrote:
       | Can this system explain its reasoning, and so explain its answer?
        
         | vectify_AI wrote:
         | Yes, the explanation and reasons for relevance can be included
         | in the search and reflected in the answer.
        
           | casenmgreen wrote:
           | Looking through the repo, reading the doc, an LLM looks to be
           | part of the implementation. LLMs cannot explain their
           | reasoning, so if there is an LLM, then the system as a whole
           | cannot explain its reasoning, because part of the system is a
           | black box? reasoning can be explained up to the point the LLM
           | comes into play, and also then afterwards, with whatever is
           | done with LLM output?
        
             | curl-up wrote:
             | Can you explain your reasoning?
        
       | BizarroLand wrote:
       | Is there a plan to allow localhosting with ollama or pinokio or
       | llmstudio?
        
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       (page generated 2025-04-10 23:01 UTC)