Principle:Mistralai Client python OCR Document Processing
| Knowledge Sources | |
|---|---|
| Domains | Document_Processing, OCR, Vision |
| Last Updated | 2026-02-15 14:00 GMT |
Overview
A document understanding technique that extracts text, tables, and images from documents (PDFs, images) using optical character recognition and vision models.
Description
OCR Document Processing uses Mistral's vision-language model to extract structured content from documents. Unlike traditional OCR that only extracts text, this approach understands document layout, extracts tables in structured formats, identifies and extracts images, and produces markdown-formatted output. Documents can be provided as URLs or uploaded files. The API supports page-level processing with options for image extraction and table formatting.
Usage
Use this principle when you need to extract content from PDFs, scanned documents, or images. The OCR API returns structured per-page results with markdown text, table data, and extracted images.
Theoretical Basis
Vision-based document processing:
- A vision-language model processes document page images
- Layout analysis identifies text regions, tables, and images
- Text is extracted with formatting preserved as markdown
- Tables are extracted in configurable formats (markdown, HTML, or raw)
- Images are optionally extracted as base64-encoded data