Greenmamba29 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
- Accept inputs: PDF file path or URL, extraction mode (text/tables/images/forms/all), OCR flag, output format (json/csv/markdown/text).
- Load the PDF and detect document type: digital native or scanned.
- If scanned and OCR=true, run OCR engine (Tesseract or cloud Vision API) to convert to text.
- 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.
- Clean extracted text: remove headers/footers, fix encoding issues, normalize whitespace.
- Structure output in requested format with source PDF reference and page numbers.
- 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)