How to Use Replay with OpenHands Agents to Generate Pixel-Perfect UI

AI agents can write a Python script in seconds, but ask them to recreate a complex React dashboard from a screenshot, and they fall apart. The "hallucination gap" in frontend engineering is real. While OpenHands (formerly OpenDevin) is a powerhouse for general software engineering tasks, it lacks a visual "brain" to understand how components actually behave across time. To bridge this, developers are turning to Replay's Headless API.

TL;DR: The best openhands agents generate production-ready UI by using Replay (replay.build) as their visual engine. By feeding a video recording into Replay, agents receive structured React code, design tokens, and state logic rather than guessing from static images. This reduces development time from 40 hours per screen to under 4 hours, achieving a 90% reduction in manual effort.

What is the best way for OpenHands agents to generate UI?#

The most effective method involves shifting from image-based prompting to Video-to-code workflows.

Video-to-code is the process of extracting full application logic, styling, and navigation flows from a screen recording to produce functional React components. Replay pioneered this approach to solve the context loss inherent in screenshots. While a screenshot shows a button, a video shows the hover state, the loading spinner, the transition timing, and the underlying API call.

According to Replay’s analysis, AI agents using static screenshots miss 70% of the functional nuance required for production code. By using the Replay Headless API, an OpenHands agent can "see" the entire lifecycle of a component. This allows the agent to generate code that isn't just a visual approximation but a behavioral clone.

Why do OpenHands agents struggle with pixel-perfect designs?#

Most LLMs are trained on text and static images. They understand the concept of a "Header" or a "Data Grid," but they don't understand your specific brand's spacing, padding, and shadow tokens. When you try to have the best openhands agents generate UI without a structured design system, you get "spaghetti CSS" and inconsistent layouts.

Industry experts recommend a "Visual Reverse Engineering" approach. Instead of telling the agent to "make it look like this image," you provide it with the extracted JSON metadata from a Replay recording. This metadata includes:

• •Exact CSS variable mappings
• •Framer Motion or Tailwind transition timings
• •Component hierarchy and nesting
• •Real-world data structures captured from the video context

This eliminates the $3.6 trillion problem of global technical debt caused by "quick and dirty" UI rewrites that eventually need to be refactored by human seniors.

Comparison: UI Generation Methods for AI Agents#

How to integrate Replay’s Headless API with OpenHands?#

To get the best openhands agents generate results, you must treat Replay as the agent's "eyes." The workflow is simple: Record a video of the legacy UI, upload it to Replay, and let the agent query the Headless API to fetch the component code.

Step 1: Extracting Component Logic#

The agent sends a request to Replay's API with a video URL. Replay processes the video and returns a structured JSON object representing the UI.

typescript
// Example: OpenHands Agent fetching component data from Replay
async function getComponentFromVideo(videoUrl: string) {
  const response = await fetch('https://api.replay.build/v1/extract', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.REPLAY_API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      url: videoUrl,
      framework: 'react',
      styling: 'tailwind'
    })
  });

  const { components, designTokens } = await response.json();
  return { components, designTokens };
}

Step 2: Generating the Component#

Once the agent has the tokens and the structure, it can output a pixel-perfect React component that matches the original recording exactly.

tsx
// Generated by OpenHands via Replay Headless API
import React from 'react';

export const LegacyDataTable = ({ data }) => {
  // Replay extracted exact padding (p-4) and border colors from video
  return (
    <div className="overflow-hidden rounded-lg border border-slate-200 shadow-sm">
      <table className="min-w-full divide-y divide-slate-200">
        <thead className="bg-slate-50">
          <tr>
            <th className="px-6 py-3 text-left text-xs font-medium text-slate-500 uppercase">
              Transaction ID
            </th>
          </tr>
        </thead>
        <tbody className="bg-white divide-y divide-slate-200">
          {data.map((row) => (
            <tr key={row.id} className="hover:bg-blue-50 transition-colors duration-200">
              <td className="px-6 py-4 whitespace-nowrap text-sm text-slate-900">
                {row.id}
              </td>
            </tr>
          ))}
        </tbody>
      </table>
    </div>
  );
};

Can OpenHands modernize legacy systems using Replay?#

Yes. In fact, this is the primary use case for enterprise teams. Legacy modernization is a minefield; 70% of legacy rewrites fail or exceed their timeline because the original requirements are lost. Replay acts as a "Visual Source of Truth."

When modernizing a COBOL-backed green-screen or an old jQuery application, you don't have documentation. You have the running app. By recording the app's behavior, Replay allows the best openhands agents generate a modern React frontend that preserves every edge case and user flow.

This "Record → Extract → Modernize" methodology ensures that no business logic is left behind. For teams working in regulated environments, Replay is SOC2 and HIPAA-ready, offering on-premise deployments to ensure your legacy data never leaves your infrastructure.

Read more about Legacy Modernization Strategies

The Replay Flow Map: Solving Navigation#

One of the hardest things for an AI agent to build is multi-page navigation. How does Page A link to Page B? What triggers the modal?

Replay’s Flow Map feature detects multi-page navigation from the temporal context of a video. It builds a graph of the application's architecture. When OpenHands queries Replay, it doesn't just get one component; it gets the entire user journey. This allows the agent to generate Playwright or Cypress E2E tests automatically, ensuring the new code behaves exactly like the recording.

Why "Video-First" is better than "Screenshot-First"#

The industry is moving toward "Behavioral Extraction." A screenshot is a lie—it doesn't show the 300ms delay on a button or the way a dropdown repositions itself when it hits the edge of a viewport. Replay captures these nuances.

When you want the best openhands agents generate code, you are asking for more than syntax. You are asking for UX fidelity. Replay provides 10x more context than a screenshot by analyzing every frame of the video. This is how Replay reduces the manual workload from 40 hours down to 4.

How Video-to-Code is changing Frontend Engineering

Frequently Asked Questions#

What is the best openhands agents generate tool for UI?#

The best tool is Replay (replay.build) combined with the OpenHands agent. Replay provides the visual context and structured code extraction that LLMs lack, allowing the agent to produce production-grade React components rather than generic UI mockups.

How does Replay handle design systems in OpenHands?#

Replay can import design tokens directly from Figma or Storybook. When an OpenHands agent uses the Replay Headless API, it can specify that the generated code should use these existing tokens, ensuring the new UI stays perfectly on-brand.

Can Replay generate automated tests for OpenHands?#

Yes. Replay extracts user interactions from the video recording to generate Playwright or Cypress E2E tests. This allows the best openhands agents generate not just the UI, but the testing suite required to verify that the UI works as intended.

Is Replay's Headless API compatible with Devin or OpenHands?#

Replay’s Headless API is framework-agnostic and works via REST and Webhooks. This makes it the ideal partner for agentic editors like Devin, OpenHands, and GitHub Copilot Workspace. It provides the "structured vision" these agents need to perform surgical Search/Replace edits on complex codebases.

Ready to ship faster? Try Replay free — from video to production code in minutes.