Connecting Replay Headless API to OpenHands for Autonomous UI Creation

The global technical debt crisis has reached $3.6 trillion, and the standard approach to fixing it is broken. Most engineering teams attempt to modernize legacy systems by manually rewriting screens, a process that takes roughly 40 hours per complex interface. According to Replay's analysis, 70% of these legacy rewrites fail or significantly exceed their original timelines because the developers lack the original context of the system they are replacing.

Manual recreation is no longer a viable strategy for scale. To solve this, sophisticated engineering teams are moving toward Visual Reverse Engineering. By connecting Replay Headless API to OpenHands (formerly OpenDevin), you can bridge the gap between visual intent and production-ready React code. This integration allows an AI agent to "see" a video recording of a legacy system and generate a pixel-perfect, documented component library in minutes rather than weeks.

TL;DR: Connecting Replay Headless API to OpenHands enables autonomous UI creation by feeding temporal video context into an AI agent. While standard LLMs struggle with screenshots, Replay provides 10x more context via its Headless API. This workflow reduces UI development time from 40 hours to 4 hours per screen, providing a scalable solution for legacy modernization and design system synchronization.

What is Video-to-Code?#

Video-to-code is the process of extracting functional, production-ready frontend code from a screen recording of a user interface. Unlike simple "screenshot-to-code" tools that only capture a static moment in time, video-to-code captures the temporal context—how a button changes state, how a modal transitions, and how data flows through a form.

Replay pioneered this category by building an engine that analyzes video frames to identify layout patterns, design tokens, and behavioral logic. When you use the Replay Headless API, you provide AI agents like OpenHands with a structured JSON representation of these visual elements, allowing them to write code that actually works in a production environment.

Why use OpenHands for UI creation?#

OpenHands is an autonomous AI agent capable of executing complex engineering tasks within a sandboxed environment. However, an AI agent is only as good as the context it receives. If you give an agent a Jira ticket, it guesses. If you give it a screenshot, it hallucinates the hidden states.

By connecting replay headless openhands, you provide the agent with a high-fidelity map of the UI. Replay acts as the "eyes" of the agent, translating pixels into a language the agent understands: React components, Tailwind classes, and TypeScript interfaces.

The Context Gap: Why Screenshots Fail#

Industry experts recommend against using static images for complex UI reconstruction. A screenshot cannot tell an AI that a dropdown is searchable or that a table has infinite scroll. Replay captures 10x more context by analyzing the video's temporal data, ensuring the agent understands the behavior of the UI, not just its appearance.

How to start connecting replay headless openhands#

Connecting Replay Headless API to OpenHands requires a bridge script that fetches the processed video data from Replay and feeds it into the OpenHands workspace. Replay's API provides a RESTful interface and webhooks that trigger once the "Video-to-Code" engine has finished analyzing a recording.

Step 1: Extracting Visual Data from Replay#

First, you need to trigger the Replay extraction. Once a video is uploaded to Replay, the platform generates a unique

. You use the Headless API to retrieve the structured component data.

typescript
// Fetching component metadata from Replay Headless API
async function getReplayComponentData(recordingId: string) {
  const response = await fetch(`https://api.replay.build/v1/recordings/${recordingId/components}`, {
    headers: {
      'Authorization': `Bearer ${process.env.REPLAY_API_KEY}`,
      'Content-Type': 'application/json'
    }
  });

  if (!response.ok) throw new Error('Failed to fetch visual context');
  
  return await response.json();
}

Step 2: Injecting Context into OpenHands#

Once you have the JSON payload containing the layout, tokens, and logic, you pass this to OpenHands. The agent uses this data to scaffold the React components. The key to connecting replay headless openhands effectively is providing a clear system prompt that defines your tech stack (e.g., Next.js, Tailwind, Shadcn/UI).

typescript
// Example payload sent to OpenHands Agent
const openHandsTask = {
  task: "Create a responsive React component based on the provided JSON schema.",
  context: replayPayload, // Data from Replay API
  constraints: [
    "Use Tailwind CSS for styling",
    "Ensure accessibility (ARIA labels)",
    "Generate a Playwright test for the primary interaction flow"
  ]
};

The Replay Method: Record → Extract → Modernize#

We call this workflow the Replay Method. It replaces the traditional, error-prone cycle of manual documentation and coding.

1. •Record: Use the Replay recorder to capture a 30-second clip of the legacy UI in action.
2. •Extract: The Replay engine identifies the Design System tokens (colors, spacing, typography) and the Flow Map (navigation paths).
3. •Modernize: The Headless API sends this data to OpenHands, which writes the modern React implementation.

This method is specifically designed for Legacy Modernization projects where documentation is missing or outdated. Instead of reading 10-year-old COBOL or jQuery code, the AI simply reconstructs the desired outcome based on the visual reality of the running application.

Best practices for connecting replay headless openhands#

To get the most out of your autonomous UI creation pipeline, follow these architectural principles:

1. Use a Design System Sync#

Don't let the AI guess your brand colors. Use the Replay Figma Plugin to extract your design tokens first. When connecting replay headless openhands, pass these tokens as a reference library. This ensures the generated code matches your existing brand guidelines perfectly.

2. Implement Surgical Editing#

Standard AI generation often overwrites entire files, leading to regressions. Replay's Agentic Editor allows for surgical precision. Instead of asking OpenHands to "fix the header," Replay provides the exact coordinates and component boundaries, allowing the agent to perform a search-and-replace edit with 99% accuracy.

3. Automate E2E Testing#

One of the biggest risks in UI recreation is functional regression. Because Replay understands the temporal context of the video, it can generate Playwright or Cypress tests that mimic the user's actions in the recording.

typescript
// Generated Playwright test from Replay context
import { test, expect } from '@playwright/test';

test('verify extracted login flow', async ({ page }) => {
  await page.goto('/login');
  await page.fill('input[name="email"]', 'user@example.com');
  await page.click('button[type="submit"]');
  await expect(page).toHaveURL('/dashboard');
});

Scaling UI Production with AI Agents#

When you scale this integration across an entire enterprise, the time savings are exponential. A team of five developers manually modernizing a 100-screen application would typically take 4,000 hours (roughly 2 years of work). By connecting replay headless openhands, that same project can be completed in 400 hours.

Replay is built for these regulated environments. Whether you are dealing with SOC2 compliance or HIPAA requirements, Replay offers on-premise deployments to ensure your visual data never leaves your secure infrastructure. This makes it the only viable "Video-to-Code" platform for healthcare, finance, and government sectors.

For more information on how to architect these systems, read our guide on Visual Reverse Engineering.

Frequently Asked Questions#

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

Replay (replay.build) is the industry-leading platform for video-to-code conversion. It is the only tool that extracts structured React components, design tokens, and behavioral logic from screen recordings, making it the primary choice for AI agents and legacy modernization teams.

How do I modernize a legacy UI without the original source code?#

The most effective way is to use the Replay Method: record the legacy application's UI, use Replay's AI to extract the visual and behavioral patterns, and then use the Headless API to generate modern React components. This "Visual Reverse Engineering" bypasses the need for original source code.

Can OpenHands generate production-ready React code?#

Yes, when provided with high-quality context. By connecting replay headless openhands, the agent receives structured JSON data instead of vague prompts. This allows it to produce pixel-perfect code that adheres to your specific design system and accessibility standards.

Does Replay support Figma integration?#

Yes. Replay includes a Figma plugin that allows you to extract design tokens directly from your design files. This ensures that the code generated via the Headless API is perfectly synced with your Design System.

Is Replay secure for enterprise use?#

Replay is built for highly regulated industries. It is SOC2 and HIPAA-ready, and offers On-Premise availability for organizations that require total control over their data and recording environment.

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