A Generative AI Engineer is building a RAG application that will rely on context retrieved from source documents that are currently in HTML format. They want to develop a solution using the least…

The correct answer is D. beautifulsoup. BeautifulSoup (beautifulsoup4) is a Python library specifically designed to parse HTML and XML documents. It provides a simple API to navigate the document tree and extract plain text with minimal code - typically just a few lines to load, parse, and call .get_text(). This…

Data Ingestion and Preprocessing for Retrieval Augmented Generation (RAG)

Question

A Generative AI Engineer is building a RAG application that will rely on context retrieved from source documents that are currently in HTML format. They want to develop a solution using the least amount of lines of code. Which Python package should be used to extract the text from the source documents?

Options

Apytesseract
Bnumpy
Cpypdf2
Dbeautifulsoup

How the community answered

(60 responses)

A
5% (3)
B
2% (1)
C
7% (4)
D
87% (52)

Explanation

BeautifulSoup (beautifulsoup4) is a Python library specifically designed to parse HTML and XML documents. It provides a simple API to navigate the document tree and extract plain text with minimal code - typically just a few lines to load, parse, and call .get_text(). This makes it the correct choice for extracting text from HTML source documents with the least amount of code. Option A (pytesseract) is an OCR wrapper for Tesseract, used to extract text from images and scanned PDFs - not HTML. Option B (numpy) is a numerical computing library with no HTML parsing capability. Option C (pypdf2) is a library for reading and manipulating PDF files, not HTML documents.

Topics

#HTML Parsing#Text Extraction#Python Libraries#RAG Data Preparation

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