Agentic System Design/

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WebVoyager’s Architecture: A Multimodal ReAct Loop

WebVoyager’s Architecture: A Multimodal ReAct Loop

Explore the technical architecture and operational loop of the WebVoyager agent, analyzing how it perceives the web, reasons about its next step, and executes actions.

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In our last lesson, we established the core challenge for a multimodal web agent as solving the “grounding problem.” Now, we’ll explore the specific architecture that the WebVoyager agent uses to tackle this challenge.

The interaction loop

At its heart, WebVoyager operates in a continuous cycle of observing, thinking, and acting. This design allows it to navigate the dynamic and unpredictable environment of the live web in a flexible, step-by-step manner.

The interaction loop of WebVoyager is inspired by a powerful orchestration pattern we’ve already seen in this course: the ReAct (Reason + Act) pattern.

The ReAct (Reason + Act) pattern first prompts the agent to generate a natural language ‘Thought’ explaining its plan, before producing the final, executable ‘Action’
The ReAct (Reason + Act) pattern first prompts the agent to generate a natural language ‘Thought’ explaining its plan, before producing the final, executable ‘Action’

Why use the ReAct pattern here? Unlike the structured pipeline generation we saw in the last chapter, web navigation is unpredictable. Websites can change, present unexpected pop-ups, or offer multiple paths to the same goal. A rigid, pre-defined plan (like plan-and-execute) would easily fail. The ReAct pattern is the perfect fit because it allows the agent to observe the current state of the live webpage and react to it step-by-step, making it far more robust in a dynamic environment.

Instead of simply generating an action, the agent is prompted to first generate a natural language “Thought” before producing the executable “Action” code. This two-step process is crucial for its performance.

  • The thought: This is where the agent’s reasoning is made explicit. It analyzes the current webpage, considers the user’s goal, and explains its plan for the next step.

  • The action: This is the specific, executable command that the agent will perform, such as Click [10] or Type [17]; Smart Folio for iPad.

By separating thought from action, the agent’s behavior becomes more transparent and easier to debug. It forces the LMM to “think before it acts,” leading to more deliberate and accurate decision-making. ...