pdf

name	pdf
description	Extract text and tables from PDF files. Use when a user uploads a PDF document that needs to be processed.

PDF Processing for Text Extraction

Purpose

Extract readable text and structured tables from PDF files. This skill is designed to feed extracted content into downstream processing (e.g., document summarization for PPT generation).

When to Use

• User uploads a .pdf file
• Need to extract document content for summarization, analysis, or conversion to other formats
• PDF contains text that can be extracted without OCR
• PDF contains tables that need to be captured as structured data

Approach

Step 1: Try pdfplumber First (Best for Text + Tables)

import pdfplumber

text_parts = []
tables = []

with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        # Extract text (preserves layout better than pypdf)
        t = page.extract_text()
        if t:
            text_parts.append(t.strip())

        # Extract tables as 2D arrays
        page_tables = page.extract_tables()
        for pt in page_tables:
            if pt and len(pt) >= 2:
                tables.append(pt)

Why pdfplumber first:

• Better layout preservation for complex documents
• Native table extraction with cell coordinates
• Falls back gracefully per-page

Step 2: Fallback to pypdf (Text Only)

from pypdf import PdfReader

reader = PdfReader("document.pdf")
text_parts = []
for page in reader.pages:
    t = page.extract_text()
    if t:
        text_parts.append(t.strip())

Use pypdf when:

• pdfplumber is not installed
• pdfplumber raises an exception
• Table extraction is not needed

Step 3: OCR for Scanned PDFs (Last Resort)

# Requires: pip install pytesseract pdf2image
import pytesseract
from pdf2image import convert_from_path

images = convert_from_path('scanned.pdf')
text = ""
for i, image in enumerate(images):
    text += f"Page {i+1}:\n"
    text += pytesseract.image_to_string(image)
    text += "\n\n"

When to use OCR:

• PDF is scanned (image-based, no selectable text)
• pdftotext or pdfplumber returns empty text
• Text quality is garbled or contains only symbols

Step 4: Command Line Tools

# Fast plain text extraction
pdftotext input.pdf output.txt

# Preserve layout
pdftotext -layout input.pdf output.txt

# Specific page range
pdftotext -f 1 -l 5 input.pdf output.txt

Handling Common Issues

Problem	Solution
Empty text (scanned PDF)	Use OCR (Step 3)
Garbled text	Check if PDF is encrypted or uses non-standard encoding
Tables not extracting	Try page.extract_tables(settings={"vertical_strategy": "lines"})
Memory issues on large PDFs	Process page-by-page in a loop
Images instead of text	OCR or skip if images are decorative

Integration Notes

For PPT generation pipeline:

1. Extract text → pass to document-summarizer skill
2. Extract tables → pass alongside text to summarizer
3. Combine pages with double newline: "\n\n".join(text_parts)
4. Attach page count: len(pdf.pages)

Output Format

Return (raw_text: str, tables: list[list[list[str]]], page_count: int):

• raw_text: all pages joined with double newlines
• tables: list of tables, each table is list[list[str]] (rows → cells)
• page_count: total number of pages