swarmauri_parser_slate 0.3.1.dev3

A parser for extracting text from PDFs using Slate.

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.