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pdf-extraction-fallback

Extract text from difficult PDFs by trying several libraries and command-line tools in sequence, then using OCR, which reads text from images. Record failed attempts and check that extracted content meets the task requirements.

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Multi-stage fallback strategy for PDF/document extraction using sequential tool alternatives

See how to install

Good for

  • Extracting text from scanned PDFs
  • Retrying extraction when PDF text is garbled
  • Reading PDFs with tables or complex layouts
  • Processing batches of varied PDFs

Files included (2)

  • SKILL.md4.8 KB
  • .skill_id37 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

PDF Extraction Fallback Strategy

When processing documents (especially PDFs), initial extraction attempts may fail due to formatting, encryption, or tool limitations. This skill provides a systematic fallback approach that tries multiple extraction methods before declaring failure.

Core Principle

Never declare completion after a single tool failure. Instead, iterate through a hierarchy of extraction methods, each with different capabilities and limitations.

Fallback Hierarchy

Attempt extraction methods in this order:

Stage 1: Direct PDF Reading

Try native PDF libraries first (fastest, preserves structure):

import PyPDF2
from pypdf import PdfReader

def extract_with_pypdf(pdf_path):
    reader = PdfReader(pdf_path)
    text = ""
    for page in reader.pages:
        text += page.extract_text() or ""
    return text

Stage 2: Shell-based Extraction (pdftotext)

If Stage 1 fails, use system tools:

# Install if needed: apt-get install poppler-utils
pdftotext -layout input.pdf output.txt
pdftotext -raw input.pdf output.txt  # Alternative layout
import subprocess

def extract_with_pdftotext(pdf_path):
    result = subprocess.run(
        ['pdftotext', '-layout', pdf_path, '-'],
        capture_output=True, text=True
    )
    if result.returncode == 0:
        return result.stdout
    raise Exception("pdftotext failed")

Stage 3: Alternative Python Parsers

Try different Python libraries with varying capabilities:

# pdfplumber - better for tables
import pdfplumber
def extract_with_pdfplumber(pdf_path):
    text = ""
    with pdfplumber.open(pdf_path) as pdf:
        for page in pdf.pages:
            text += page.extract_text() or ""
    return text

# pdfminer - handles complex layouts
from pdfminer.high_level import extract_text
def extract_with_pdfminer(pdf_path):
    return extract_text(pdf_path)

Stage 4: OCR Fallback

For scanned images or when text extraction fails:

# Using tesseract
convert input.pdf output-%d.png  # Convert to images first
tesseract output-0.png result --psm 6
# Using pytesseract
from pdf2image import convert_from_path
import pytesseract

def extract_with_ocr(pdf_path):
    images = convert_from_path(pdf_path, dpi=300)
    text = ""
    for image in images:
        text += pytesseract.image_to_string(image)
    return text

Implementation Pattern

def robust_pdf_extraction(pdf_path):
    """Try multiple extraction methods until one succeeds."""
    
    extraction_methods = [
        ("PyPDF2", extract_with_pypdf),
        ("pdftotext", extract_with_pdftotext),
        ("pdfplumber", extract_with_pdfplumber),
        ("pdfminer", extract_with_pdfminer),
        ("OCR", extract_with_ocr),
    ]
    
    errors = []
    for method_name, method_func in extraction_methods:
        try:
            print(f"Trying {method_name}...")
            text = method_func(pdf_path)
            if text and text.strip():
                print(f"Success with {method_name}")
                return text
            else:
                errors.append(f"{method_name}: empty result")
        except Exception as e:
            errors.append(f"{method_name}: {str(e)}")
            print(f"{method_name} failed: {e}")
            continue
    
    # All methods failed
    raise Exception(f"All extraction methods failed:\n" + "\n".join(errors))

Success Criteria

A method is considered successful when:

  1. No exceptions are raised during execution
  2. Non-empty text is returned (text.strip() has content)
  3. Content quality meets task requirements (check for expected keywords/patterns)

Best Practices

  1. Log each attempt - Record which methods were tried and why they failed
  2. Validate output - Check extracted text contains expected content markers
  3. Graceful degradation - Proceed with partial data if full extraction isn't possible
  4. Cache successful method - Remember which method worked for similar files
  5. Set timeouts - Prevent OCR or complex parsing from hanging indefinitely

Common Failure Modes

SymptomLikely CauseBest Fallback
Empty pagesImage-based PDFOCR (Stage 4)
Garbled textEncoding issuespdftotext (Stage 2)
Missing tablesSimple parserpdfplumber (Stage 3)
Permission errorsEncrypted PDFCheck password/permissions first
Layout lostComplex formattingpdftotext -layout or pdfplumber

When to Use

  • Processing unknown/untrusted PDF sources
  • Batch processing diverse document types
  • Critical tasks where extraction failure is not acceptable
  • Documents with mixed content (text + images + tables)

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