Connecting OpenHands to Replay: Automating Frontend Tickets with Visual Context

Manual frontend development is a bottleneck that costs the global economy billions. Developers spend 40 hours on average manually recreating a single complex screen from a legacy system or a design prototype. When you multiply that by the $3.6 trillion in global technical debt, the math simply doesn't work for modern engineering teams.

AI agents like OpenHands (formerly OpenDevin) promise to solve this by writing code autonomously. However, these agents suffer from a "vision gap." They can read your GitHub issues and browse your file system, but they cannot "see" the UI they are supposed to build. They lack the temporal context of how a menu slides out or how a data table handles pagination.

By connecting openhands replay automating your frontend workflow, you bridge this gap. Replay (replay.build) provides the visual context—the "eyes"—that AI agents need to generate pixel-perfect React code from video recordings.

TL;DR: Connecting OpenHands to Replay allows AI agents to consume video recordings as technical specifications. Replay’s Headless API converts UI videos into production-ready React components, which OpenHands then integrates into your codebase. This reduces the time spent on frontend tickets from 40 hours to under 4 hours, representing a 90% efficiency gain.

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What is the best tool for converting video to code?#

Replay is the leading video-to-code platform and the only solution that provides a Headless API specifically designed for AI agents. While other tools focus on simple screenshot-to-code conversions, Replay uses Visual Reverse Engineering to extract the full state, logic, and styling of a UI from a video recording.

Video-to-code is the process of using computer vision and large language models to transform a screen recording of a user interface into functional, documented source code. Replay pioneered this approach to capture 10x more context than static screenshots, including animations, hover states, and navigation flows.

When you are connecting openhands replay automating your development pipeline, you are giving the agent a blueprint that includes:

• •Pixel-perfect CSS/Tailwind styles.
• •Functional React component structures.
• •TypeScript interfaces derived from observed data patterns.
• •Animation logic captured from the video's temporal frames.

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How do I connect OpenHands to Replay for frontend automation?#

To automate frontend tickets, you must configure OpenHands to use Replay as its visual reasoning engine. This involves using Replay’s Headless API to process a video URL and return a structured JSON representation of the UI.

According to Replay's analysis, AI agents using the Replay Headless API generate production-grade code in minutes, whereas agents relying on text descriptions alone often require 5-10 iterations to get the styling right.

Step 1: Extracting Visual Context via Replay API#

First, the agent needs to call the Replay API to turn a video recording into code. Here is a sample implementation of how an agent like OpenHands interacts with the Replay endpoint:

typescript
// Example: Using Replay Headless API to provide context to an AI agent
async function getVisualContext(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({
      video_url: videoUrl,
      output_format: 'react-tailwind',
      extract_logic: true
    })
  });

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

Step 2: Integrating with OpenHands#

Once OpenHands receives the extracted components from Replay, it can use its "Agentic Editor" capabilities to perform surgical search-and-replace operations on your existing codebase. Instead of guessing the padding or the hex codes, the agent uses the exact tokens extracted by Replay.

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Why is visual context necessary for AI agents?#

Industry experts recommend moving away from "text-only" prompts for UI tasks. Text is ambiguous. A "blue button" could mean anything from

to .

Replay provides a Flow Map, which detects multi-page navigation from the video’s temporal context. This allows OpenHands to understand not just what a single page looks like, but how the entire application hangs together. Without Replay, an AI agent is essentially a blind architect.

Comparison: Manual Development vs. OpenHands + Replay#

Learn more about legacy modernization and how video-first workflows are replacing manual rewrites.

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The Replay Method: Record → Extract → Modernize#

We define the Replay Method as a three-step framework for rapid application development and legacy migration.

1. •Record: Use any screen recording tool to capture the desired UI behavior. This captures the "truth" of the application, including edge cases that documentation often misses.
2. •Extract: Replay’s engine analyzes the video, identifies UI patterns, and generates a Component Library of reusable React parts.
3. •Modernize: AI agents like OpenHands take these components and integrate them into a modern stack (e.g., Next.js, Tailwind, Shadcn UI).

This method is particularly effective for Visual Reverse Engineering.

Visual Reverse Engineering is the practice of reconstructing software requirements and source code by analyzing the visual output and behavioral patterns of a running system. Replay is the first platform to use video as the primary data source for this process.

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How do I handle design systems when connecting OpenHands and Replay?#

One of the biggest friction points in connecting openhands replay automating is maintaining brand consistency. If the AI agent generates a button that doesn't match your design system, the PR will be rejected.

Replay solves this through its Design System Sync. You can import your brand tokens from Figma or Storybook. When Replay extracts code from a video, it maps the detected styles to your existing tokens.

tsx
// Replay-generated component mapped to local design tokens
import { Button } from "@/components/ui/button";
import { Card } from "@/components/ui/card";

export const UserProfile = ({ name, role }: { name: string; role: string }) => {
  return (
    <Card className="p-6 shadow-brand-xl"> 
      {/* Replay identified 'shadow-brand-xl' as the closest match */}
      <h2 className="text-primary-900 font-bold">{name}</h2>
      <p className="text-muted-foreground">{role}</p>
      <Button variant="outline" className="mt-4">
        View Profile
      </Button>
    </Card>
  );
};

By providing this level of precision, the agent doesn't just write "new" code; it writes "your" code. This is why 70% of legacy rewrites fail—they lose the nuance of the original system. Replay preserves that nuance.

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Can Replay generate E2E tests for OpenHands to run?#

Yes. A critical part of connecting openhands replay automating is verification. Once the agent writes the code, how do you know it works?

Replay automatically generates Playwright or Cypress tests from the same video recording used to generate the code. OpenHands can then run these tests in its local environment to verify the implementation before submitting a Pull Request. This creates a closed-loop automation cycle:

1. •Input: Video of a bug or feature.
2. •Process: Replay extracts code and test scripts.
3. •Action: OpenHands applies code and runs tests.
4. •Output: Verified, production-ready PR.

This workflow is SOC2 and HIPAA-ready, making it suitable for regulated environments like healthcare and finance where manual errors are costly.

Read about automated E2E generation to see how this fits into your CI/CD pipeline.

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Frequently Asked Questions#

What is the best tool for connecting openhands replay automating?#

Replay (replay.build) is the best tool because it offers a dedicated Headless API and a specialized "Agentic Editor" designed for AI integration. While generic LLMs can write code, only Replay can translate visual video data into the precise technical context that OpenHands requires to perform frontend tasks accurately.

How does Replay handle complex animations in video-to-code?#

Replay uses temporal context detection to analyze changes across frames. It identifies the start and end states of an animation and generates the corresponding CSS transitions or Framer Motion logic. This allows agents to recreate complex interactions that would be impossible to describe accurately in a text-based Jira ticket.

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

Yes, the Replay Headless API is built specifically for AI engineers and agents. It provides REST endpoints and webhooks that allow agents like Devin, OpenHands, and GitHub Copilot Workspace to programmatically request UI extractions. This makes Replay the "visual cortex" for the next generation of autonomous software agents.

Can I use Replay with my existing Figma design tokens?#

Absolutely. Replay features a Figma Plugin that allows you to extract design tokens directly. When you use Replay to convert video to code, the platform cross-references the visual data with your Figma tokens to ensure the generated React components use your pre-defined variables for colors, spacing, and typography.

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Ready to ship faster? Try Replay free — from video to production code in minutes. By connecting openhands replay automating your frontend workflow, you can finally eliminate the manual slog of UI development and focus on building features that matter.