Azure-Samples/multimodal_rag_python
Python notebook for solving overlapping tables problem with Azure document intelligence , semantic chunking, RAG , Azure AI Search
This project helps operations managers, data analysts, or researchers extract and understand complex information from documents containing large tables that span multiple pages and lack clear headers. It takes your PDF documents as input and outputs structured information, making it easier to analyze and retrieve specific data points that might otherwise be missed. This is particularly useful for anyone dealing with detailed reports, financial statements, or technical specifications where data is often presented in challenging, multi-page table formats.
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Use this if you frequently need to accurately extract and query information from PDF documents containing hierarchical tables that are spread across multiple pages without consistent headers.
Not ideal if your documents primarily contain simple text or well-structured, single-page tables with clear headers.
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Last pushed
Sep 04, 2024
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