How to Web Scrape Wikipedia with LLM Agents

Simple guide to using LangChain Agents and Tools with OpenAI’s LLMs and Function Calling for web scraping of Wikipedia

Kenneth Leung
DataDrivenInvestor

Photo by Built Robotics on Unsplash

Web scraping Wikipedia is a useful technique for extracting valuable information, thanks to its vast collection of structured and unstructured data. Traditional tools like Selenium, while effective, tend to be manual and time-consuming.

The impressive capabilities of large language models (LLMs) and the ability to connect them to the Internet have ushered in new possibilities in many use cases, including the domain of web scraping.

In this article, we harness the powerful combination of LLM agents, tools, and function calling to extract data from Wikipedia readily.

Disclaimer: This content is meant for educational purposes, and adheres to Wikipedia’s terms of use (Creative Commons Attribution-ShareAlike 4.0 International License). Do check and comply with the terms of service of any website before engaging in web scraping. This article does not encourage or endorse any form of illegal web scraping activities.

Contents

(1) Context and Data
(2) Toolkit
(3) Step-by-Step Guide

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