This document explains the PDF OCR Reader node, which extracts text from scanned PDFs and image-based documents.

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Node Inputs

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Required Fields

  • File Name: Upload PDF or select existing file from storage

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Optional Fields

  • Use Link: Enable to read from URL
  • Specify Pages: Select specific pages to read
  • Split PDF Content by Page: Get page-by-page output in a list format. Each item in the list is a single page from the PDF.
  • Image Model: Choose AI model for OCR
  • Temperature: Controls OCR accuracy (0-1)
  • Cache Response: Save results for reuse

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Show As Input Options

You can expose these fields as inputs:
  • Temperature

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Node Output

  • PDF Contents: Extracted text (single or per page)

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Node Functionality

The PDF OCR Reader can:
  • Reads image based PDF documents
  • Extracts text from images
  • Processes handwriting
  • Handles multiple pages
  • Supports various languages

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Available AI Models

  • GPT-4.1 Vision
  • GPT-4.1 Mini Vision
  • Claude 3.7 Sonnet
  • Claude 3.5 Haiku
  • Gemini 1.5 Pro
  • Gemini 1.5 Flash

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Common Use Cases

  1. Scanned Documents:
Input: Scanned contracts.pdf
Output: Searchable text
Use: Document digitization
  1. Image-Based PDFs:
Input: Photographed receipts.pdf
Output: Extracted line items
Use: Expense processing
  1. Mixed Content:
Input: Handwritten notes.pdf
Output: Digital text
Use: Note digitization

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Important Considerations

  • Advanced models (GPT-4.1 & Claude 3.7) cost 20 credits, and standard models cost 2 credits per run
In summary, the PDF OCR Reader node helps convert image-based PDFs into searchable text using advanced AI vision models.