Enterprise RAG pipeline uses spatial OCR and layout parsing for complex documents

This article details an enterprise-grade retrieval-augmented generation (RAG) ingestion pipeline designed to handle complex documents. It emphasizes overcoming common failures in RAG deployments by employing a multi-stage process that combines spatial computer vision, layout-aware parsing, and vision-language model chart indexing. The pipeline includes stages for spatial OCR using MuPDF and YOLOv8 for document geometry resolution, followed by layout-aware table extraction and Markdown serialization using libraries like BeautifulSoup and pandas. AI

IMPACT Enhances RAG system capabilities for handling complex document structures, improving data extraction accuracy.

RANK_REASON Article details a specific technical implementation for RAG ingestion pipelines, not a new product release or frontier model.

Read on dev.to — LLM tag →

• HostingPodium
• Markdown
• MuPDF
• optical character recognition
• pdfminer
• pypdf
• retrieval-augmented generation
• YOLOv8

• infra
• product

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