Extract text from PDFs when read_file fails or returns unreadable data. Use dedicated command-line tools or Python libraries to retrieve text and tables, preserve spacing where possible, inspect document properties, and validate the extracted content.
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Extract PDF text content using shell tools or Python libraries when read_file PDF handler fails
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
The read_file tool with filetype='pdf' can be unreliable for PDF text extraction. It may:
Use run_shell with dedicated PDF extraction tools instead of relying on read_file for PDFs.
pdftotext input.pdf output.txt
Or to extract to stdout:
pdftotext input.pdf -
With layout preservation:
pdftotext -layout input.pdf output.txt
pdfinfo input.pdf
Useful for checking page count, dimensions, and PDF properties before extraction.
import fitz # PyMuPDF
doc = fitz.open("input.pdf")
text = ""
for page in doc:
text += page.get_text()
doc.close()
import pdfplumber
with pdfplumber.open("input.pdf") as pdf:
for page in pdf.pages:
text = page.extract_text()
tables = page.extract_tables()
Check PDF exists and is readable:
pdfinfo input.pdf 2>/dev/null || echo "PDF not accessible"
Extract text using pdftotext:
pdftotext -layout input.pdf - > extracted_text.txt
If pdftotext fails, try Python fallback:
import fitz
doc = fitz.open("input.pdf")
for i, page in enumerate(doc):
print(f"--- Page {i+1} ---")
print(page.get_text())
doc.close()
Verify extraction succeeded:
| Tool | Best For |
|---|---|
pdftotext | Fast, simple text extraction |
pdftotext -layout | Preserving spacing/formatting |
PyMuPDF | Complex PDFs, programmatic access |
pdfplumber | Tables and structured data |
# In your agent workflow, prefer this pattern:
result = run_shell(command="pdftotext document.pdf -", timeout=30)
if result.stdout and len(result.stdout.strip()) > 0:
content = result.stdout
else:
# Fallback to Python
content = execute_python_to_extract_pdf("document.pdf")
apt-get install poppler-utils (for pdftotext/pdfinfo)pip install pymupdf pdfplumber아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Prepare audio stems, the separate parts of a track, for mixing by matching their durations with silence, loops, or crossfades. Verify each generated and processed file before moving to the next production step.
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Produce audio in separate stems, meaning individual instrument tracks, and verify each output as you go. Align track lengths with silence, loops, or crossfades, then apply effects, mix a master, and package the files.
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Build serverless endpoints that relay external API requests for a dashboard while keeping API keys on the server. Includes Vercel examples for input checks, caching, cross-origin access, and consistent JSON responses.
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Produce a master track and separate audio parts through a structured Python workflow. Apply filters and reverb, export WAV files with consistent settings, package them in a ZIP archive, and check that the deliverables meet the requested specifications.
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Keep document creation moving when web searches and page retrieval repeatedly fail. The skill preserves the original task, uses the model’s existing knowledge, and clearly identifies information that could not be checked against external sources.
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When Python execution repeatedly fails in execute_code_sandbox, use a file-based alternative: save the script, run it through the shell, and capture results or errors. The guidance covers paths, imports, timeouts, structured output, and optional cleanup.
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