swarmauri_parser_slate 0.2.2.dev7

A parser for extracting text from PDFs using Slate.

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Swarmauri Parser Slate

PDF text parser for Swarmauri using Slate3k (a lightweight PDFMiner wrapper). Extracts text from each PDF page and returns Document instances with page metadata.

Features

• Opens PDFs with Slate3k and returns a Document per page (content = text, metadata includes page_number and source).
• Accepts file paths (string). Raises a TypeError when given anything else to prevent silent failures.
• Returns an empty list if Slate encounters parsing errors, logging the exception to stdout.

Prerequisites

• Python 3.10 or newer.
• Slate3k depends on pdfminer.six; make sure operating-system libraries required by PDFMiner (e.g., libxml2, libxslt on Linux) are installed.
• Read access to the PDF path you pass in.

Installation

# pip
pip install swarmauri_parser_slate

# poetry
poetry add swarmauri_parser_slate

# uv (pyproject-based projects)
uv add swarmauri_parser_slate

Quickstart

from swarmauri_parser_slate import SlateParser

parser = SlateParser()
documents = parser.parse("pdfs/handbook.pdf")

for doc in documents:
    print(doc.metadata["page_number"], doc.content[:120])

Handling Errors

parser = SlateParser()
try:
    docs = parser.parse("missing.pdf")
    if not docs:
        print("No pages parsed or Slate returned no text.")
except TypeError as exc:
    print(f"Bad input: {exc}")

Tips

• Slate3k works best on text-based PDFs. For scanned/bitmap PDFs, run OCR first (e.g., swarmauri_ocr_pytesseract).
• Large PDFs can consume memory; consider chunking results or streaming pages to downstream processors.
• Combine with token counting or summarization measurements in Swarmauri to further process the extracted content.

Want to help?

If you want to contribute to swarmauri-sdk, read up on our guidelines for contributing that will help you get started.