PDF Extractor

Overview

Extract and structure content from PDFs—including scanned documents via OCR—delivering clean text, parsed tables, identified metadata, and form data ready for downstream processing.

When to Use

• •Extracting invoice data from supplier PDF invoices
• •Parsing technical datasheets for battery specifications
• •Processing government compliance documents and permits
• •Converting scanned contracts into editable text
• •Batch-extracting data from hundreds of procurement PDFs

Instructions

1. •Accept inputs: PDF file path or URL, extraction mode (text/tables/images/forms/all), OCR flag, output format (json/csv/markdown/text).
2. •Load the PDF and detect document type: digital native or scanned.
3. •If scanned and OCR=true, run OCR engine (Tesseract or cloud Vision API) to convert to text.
4. •Extract content based on mode:
   • •Text: parse all text with page/paragraph structure preserved.
   • •Tables: detect table regions, extract rows/columns into structured data.
   • •Images: extract embedded images with position metadata.
   • •Forms: identify form fields and their values.
5. •Clean extracted text: remove headers/footers, fix encoding issues, normalize whitespace.
6. •Structure output in requested format with source PDF reference and page numbers.
7. •Return extraction summary: pages processed, tables found, confidence score (OCR), output file path.

Environment

OCR_ENGINE=tesseract
GOOGLE_VISION_API_KEY=your_key_optional
OUTPUT_FORMAT=json
BATCH_SIZE=10
TEMP_DIR=./pdf_processing

Examples

Input:

file: ./invoices/lithium_supplier_inv_2026.pdf
mode: tables
ocr: false
output_format: csv

Output:

Extraction complete.
Pages processed: 3
Tables found: 2
Rows extracted: 47
Output: ./output/lithium_supplier_inv_2026_tables.csv
Confidence: 99.2% (digital PDF)