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local-pdf-extraction

Extract text from local PDF files with pdftotext or PyMuPDF, a Python library for reading PDFs. Convert individual files or batches into text files that an agent can read for summarization, analysis, or further data extraction.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Extract text from local PDFs using pdftotext or PyMuPDF via run_shell

설치 방법 보기

이럴 때 유용합니다

  • Converting local PDFs to text for summarization
  • Extracting text from multiple PDFs in one batch
  • Reading PDFs that appear as binary data in read_file

포함된 파일(2)

  • SKILL.md2.8 KB
  • .skill_id34 B

SKILL.md(원문)

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Local PDF Extraction Workflow

Use this skill when you need to extract text from PDF files that exist locally on the filesystem, and read_file returns binary data instead of readable text.

When to Use

  • PDF files exist in the local workspace or known directories
  • read_file on PDFs returns binary/garbled data instead of text
  • You need to process PDF content for analysis, summarization, or data extraction

Step-by-Step Instructions

Step 1: Locate PDF Files

First, list directory contents to find all PDF files:

ls -la *.pdf
# or for recursive search
find . -name "*.pdf" -type f

Step 2: Extract PDFs to Text

Choose one of these methods based on available tools:

Method A: Using pdftotext (poppler-utils)

# Extract single PDF
pdftotext input.pdf output.txt

# Batch extract all PDFs in directory
for pdf in *.pdf; do
    pdftotext "$pdf" "${pdf%.pdf}.txt"
done

Method B: Using PyMuPDF (fitz) via Python

python3 << 'EOF'
import fitz  # PyMuPDF
import glob
import os

for pdf_path in glob.glob("*.pdf"):
    doc = fitz.open(pdf_path)
    text = ""
    for page in doc:
        text += page.get_text()
    
    txt_path = pdf_path.replace(".pdf", ".txt")
    with open(txt_path, "w", encoding="utf-8") as f:
        f.write(text)
    print(f"Extracted: {pdf_path} -> {txt_path}")
EOF

Step 3: Read Extracted Text Files

Once extracted, use read_file to read the .txt files:

# Now you can read the text files normally
content = read_file(filetype="txt", file_path="document.txt")

Step 4: Process Content

Proceed with your analysis, summarization, or data extraction on the text content.

Complete Workflow Example

# Step 1: Find PDFs
ls -la *.pdf

# Step 2: Extract all PDFs to text
for pdf in *.pdf; do
    pdftotext "$pdf" "${pdf%.pdf}.txt"
done

# Step 3: Verify extraction
ls -la *.txt

Or as a Python script via run_shell:

python3 << 'SCRIPT'
import fitz, glob
for pdf in glob.glob("*.pdf"):
    doc = fitz.open(pdf)
    text = "".join(page.get_text() for page in doc)
    with open(pdf.replace(".pdf", ".txt"), "w") as f:
        f.write(text)
    print(f"Done: {pdf}")
SCRIPT

Troubleshooting

  • pdftotext not found: Install with apt-get install poppler-utils or use PyMuPDF method
  • Empty text output: PDF may be image-based; consider OCR tools like pdftoppm + tesseract
  • Encoding issues: Ensure output files use UTF-8 encoding

Key Takeaways

  1. Never use read_file directly on PDFs for text extraction
  2. Always list directory first to confirm PDF locations
  3. Use run_shell with pdftotext or PyMuPDF for reliable extraction
  4. Batch process when multiple PDFs exist
  5. Read the resulting .txt files for further processing

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