The Multimodal Web Agent Challenge
Explore the fundamental challenges of web automation, including the limitations of text-only agents and the critical “grounding problem” that arises with multimodal models.
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Problem space: Multimodal web agents
So far in this course, we’ve seen agents designed for specific, relatively contained environments. Now, we’re going to explore a new and incredibly complex environment for agents to operate in: the live web.
What is a web agent?
A web agent is an autonomous system designed to navigate and interact with real-world websites to complete tasks on behalf of a user. Unlike a simple web scraper that just extracts data, a true web agent can perform actions like a human: clicking buttons, typing in forms, and making decisions based on what it sees.
Our goal in this chapter is to design an agent that, given a high-level instruction like “Find the cheapest flight from New York to London next Tuesday,” can autonomously browse a website and return a final answer.
The foundational tool: HTML
To perform any action, an agent must first understand the structure of a webpage. The primary source for this understanding is the website’s HTML (Hypertext Markup Language).
HTML is the skeleton of a webpage. For an agent, it’s an incredibly valuable source of signals because it explicitly defines the interactive elements on a page. By parsing the HTML, an agent can perform a number of functions outlined below.
Identify elements: It can see every button, input field, link, and image on the page.
Understand element types: It knows the difference between a clickable
<button>and a fillable<input type="text">.Extract textual content: It can read the text labels on buttons and links, which is crucial for understanding their function.
For early web agents, HTML was the only way they could perceive their environment. However, as ...