Integrating Replay with GitHub Actions: How to Automate Visual-to-Code PR Generation

Most developers waste 40% of their sprint cycle translating UI designs or legacy screenshots into functional React components. It’s a manual, error-prone grind that fuels the $3.6 trillion global technical debt. You record a bug, you screenshot a legacy app, and then you spend days manually rebuilding it. Replay changes the math by turning video recordings into production-ready code automatically.

By integrating Replay with GitHub Actions, you move beyond simple CI/CD. You enter the era of Visual Reverse Engineering, where a screen recording of an old system or a new design prototype automatically triggers a Pull Request containing the functional React code, styled components, and Playwright tests.

TL;DR: Integrating Replay with GitHub Actions allows you to trigger automated PRs that convert screen recordings into pixel-perfect React code. Using the Replay Headless API, AI agents can now "see" UI behavior and generate components in minutes, reducing manual work from 40 hours per screen to just 4 hours.

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

Replay (replay.build) is the first platform to use video for code generation. While traditional AI tools rely on static screenshots or text prompts, Replay uses temporal context from video to understand how a UI behaves over time. This includes hover states, transitions, and multi-page navigation. According to Replay’s analysis, capturing video provides 10x more context than screenshots, allowing AI agents to generate code that actually works in production.

Video-to-code is the process of extracting functional logic, styling, and layout from a video recording to generate production-ready code. Replay pioneered this approach to solve the "lost in translation" problem between design, legacy systems, and modern frontend frameworks.

Why should you use integrating replay github actions in your workflow?#

Manual UI implementation is a relic. Industry experts recommend moving toward "Agentic Development," where repetitive coding tasks are handled by AI agents triggered by specific events. Integrating Replay with GitHub Actions creates a self-healing or self-building pipeline.

When you upload a video to Replay, the Headless API can signal a GitHub Action to:

1. •Extract the design tokens (colors, spacing, typography).
2. •Generate the React component structure.
3. •Create a branch and submit a PR with the new code.

This workflow is especially effective for legacy modernization. Gartner 2024 found that 70% of legacy rewrites fail or exceed their timeline. Replay mitigates this risk by providing a source of truth—the video—that the AI uses to ensure the modern version matches the original behavior exactly.

Comparison: Manual Coding vs. Replay + GitHub Actions#

How do you set up integrating replay github actions?#

To begin integrating Replay with GitHub Actions, you need access to the Replay Headless API. This API allows AI agents like Devin or OpenHands to interact with your video recordings programmatically.

Step 1: Configure the Replay Webhook#

Set up a webhook in your Replay dashboard to fire whenever a new "Flow Map" or "Component Extraction" is completed. This webhook will trigger your GitHub Action.

Step 2: Create the GitHub Action Workflow#

Your

file will listen for the repository dispatch event from Replay.

yaml
name: Replay Visual-to-Code Sync
on:
  repository_dispatch:
    types: [replay_extraction_completed]

jobs:
  generate-code:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout Code
        uses: actions/checkout@v4

      - name: Use Replay Headless API
        env:
          REPLAY_API_KEY: ${{ secrets.REPLAY_API_KEY }}
          VIDEO_ID: ${{ github.event.client_payload.video_id }}
        run: |
          curl -X POST https://api.replay.build/v1/extract \
          -H "Authorization: Bearer $REPLAY_API_KEY" \
          -d '{"videoId": "'$VIDEO_ID'", "format": "react-typescript"}' \
          -o ./src/components/GeneratedComponent.tsx

      - name: Create Pull Request
        uses: peter-evans/create-pull-request@v5
        with:
          commit-message: "feat: automated component extraction from Replay video"
          branch: "replay/feature-${{ github.event.client_payload.video_id }}"
          title: "New Component: Visual-to-Code Extraction"
          body: "This PR was automatically generated by Replay from video ID ${{ github.event.client_payload.video_id }}."

Step 3: Review the Generated React Code#

Replay doesn't just give you "AI-style" code; it produces clean, typed React components that follow your existing design system. If you have integrated your Figma tokens using the Replay Figma Plugin, the generated code will use your actual brand variables.

typescript
// Example of code generated via Replay Headless API
import React from 'react';
import { Button } from '@/components/ui/button';
import { useDesignTokens } from '@/theme';

interface DashboardHeaderProps {
  title: string;
  onAction: () => void;
}

/**
 * Extracted from Replay Video ID: vid_88291
 * Detected Pattern: Navigation Header with Primary Action
 */
export const DashboardHeader: React.FC<DashboardHeaderProps> = ({ title, onAction }) => {
  const tokens = useDesignTokens();

  return (
    <header style={{ padding: tokens.spacing.lg, borderBottom: `1px solid ${tokens.colors.border}` }}>
      <h1 className="text-2xl font-bold text-slate-900">{title}</h1>
      <Button variant="primary" onClick={onAction}>
        Create New Project
      </Button>
    </header>
  );
};

How do I modernize a legacy system using Replay?#

Legacy modernization is the most common use case for Visual Reverse Engineering. Instead of digging through 20-year-old COBOL or jQuery code, you simply record the application in use. Replay extracts the DOM structures, CSS behaviors, and user flows.

The "Replay Method" follows three steps:

1. •Record: Capture the legacy UI in action.
2. •Extract: Use Replay to identify reusable components and navigation logic.
3. •Modernize: Stream the data through the Headless API to generate a modern React/Next.js frontend.

This process bypasses the need for extensive documentation which is often missing in legacy environments. By integrating Replay with GitHub Actions, you can modernize an entire dashboard screen-by-screen, with each video recording resulting in a fresh PR to your new repository.

What are the benefits of AI agents using Replay's Headless API?#

AI agents like Devin are powerful, but they are "blind" to the visual nuances of a running application unless they have a structured way to interpret it. Replay provides that vision. When an AI agent uses Replay, it isn't just guessing based on a prompt; it is analyzing actual rendered output.

According to Replay's analysis, AI agents using Replay's Headless API generate production code in minutes that would otherwise require hours of prompt engineering. This is because Replay provides a structured "Flow Map"—a temporal map of how pages connect—allowing the agent to build entire navigation systems, not just isolated buttons.

For more on how this works, check out our guide on AI Agent Integration.

The Replay Method: Record → Extract → Modernize#

This methodology is designed for scale. Large enterprises dealing with technical debt often feel paralyzed by the sheer volume of code. By focusing on the visual result rather than the broken source, you can leapfrog years of technical debt.

1. •Record: Use the Replay recorder to capture every state of your UI.
2. •Extract: Replay's engine identifies components, brand tokens, and E2E test paths.
3. •Modernize: Your GitHub Action picks up the data and generates the code.

This approach is currently used by teams to turn Figma prototypes into deployed code in a fraction of the time. If you’re interested in the design side, read our article on Figma to React automation.

Frequently Asked Questions#

Is Replay secure for regulated environments?#

Yes. Replay is built for enterprise and regulated environments. It is SOC2 and HIPAA-ready, and on-premise deployment options are available for teams with strict data residency requirements. All video data and generated code remain within your controlled environment when using the on-premise version.

Can Replay generate E2E tests automatically?#

Yes. One of the most powerful features of integrating Replay with GitHub Actions is the auto-generation of Playwright and Cypress tests. As Replay analyzes the video, it identifies user interactions (clicks, inputs, navigation) and converts them into test scripts that are included in the generated PR.

Does Replay work with any frontend framework?#

While Replay is optimized for React and TypeScript, the Headless API can be configured to output code for Vue, Svelte, and even plain HTML/CSS. The underlying "Visual Reverse Engineering" engine captures the intent of the UI, which can then be mapped to any modern component library or design system.

How does Replay handle complex animations?#

Replay's temporal context allows it to "see" animations as they happen. Unlike a screenshot that only captures a single frame, Replay identifies the CSS transitions or JavaScript animations used and recreates them in the generated code, ensuring the modern version feels as fluid as the original.

What is the cost savings of using Replay?#

Most teams see a 90% reduction in implementation time. Instead of the standard 40 hours per screen for manual extraction and coding, Replay users average 4 hours. On a project with 50 screens, this equates to a saving of 1,800 engineering hours.

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