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A simple CLI to extract text from documents using the Mistral OCR API.

Project description

Mistral OCR

A simple CLI to extract text from documents using the Mistral OCR API.

Installation

pip install .

Or with uv:

uv sync

Configuration

Set your Mistral API key as an environment variable or in a .env file:

MISTRAL_API_KEY="your-api-key"

Usage

mistral-ocr <document_source> [options]

The document source can be a URL, a local file path, or - to read from stdin.

Examples

# Process a PDF from a URL
mistral-ocr https://example.com/document.pdf

# Process a local file
mistral-ocr ./invoice.pdf

# Pipe from stdin
cat document.pdf | mistral-ocr -

# Process specific pages only (0-indexed)
mistral-ocr large-doc.pdf --pages 0,2,5

# Output as JSON (great for piping to jq)
mistral-ocr document.pdf --json | jq '.pages[0].markdown'

# Extract tables as HTML
mistral-ocr document.pdf --table-format html

# Include headers and footers
mistral-ocr document.pdf --extract-headers --extract-footers

# Include base64-encoded images in response
mistral-ocr document.pdf --include-images

# Check page count and estimated cost before processing
mistral-ocr large-doc.pdf --dry-run

Options

Option Description
-p, --pages Comma-separated page numbers to process (0-indexed)
--json Output full JSON response instead of markdown
--table-format Table output format: markdown or html
--extract-headers Include page headers
--extract-footers Include page footers
--include-images Include base64-encoded images in response
--image-limit N Maximum number of images to extract
--image-min-size N Minimum image dimension in pixels
--model NAME Model override (default: mistral-ocr-latest)
--dry-run Show page count and estimated cost without processing
-v, --verbose Enable verbose logging

Development

uv sync --group dev
uv run pytest tests/

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