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# Automatic AI Translations

**Date:** August 2025
**Technologies:** TypeScript, Gemini

---

## Project Overview

The Automatic AI Translations system is a client-side translation layer built for the GDGoC UAM website that enables visitors to translate the entire page into their preferred language without server round-trips or third-party API keys. Unlike traditional i18n approaches that require pre-translated content bundles, this system leverages Chrome's experimental built-in AI Translator API to perform neural machine translation directly in the browser, making the site's content accessible to a global audience with zero backend overhead.

The system integrates seamlessly with the existing Paraglide internationalization framework. While the site ships with native Spanish and English translations compiled at build time, the AI layer extends reach to 39 additional languages by translating the rendered DOM on demand. This hybrid approach preserves the performance and SEO benefits of static translation for primary locales while offering on-the-fly accessibility for everyone else.

It has also been designed to be portable and flexible and, as a matter of fact, it is the exact same scripts that power the AI translations in this portfolio.

## Technical Architecture

### Browser-Native AI Integration

The system is built around Chrome's experimental `window.Translator` API, which provides a Gemini Nano model running locally via the browser's built-in AI runtime. This architecture offers three critical advantages over cloud-based translation services:

1. **Privacy**: No text leaves the user's device
2. **Latency**: Sub-second translation without network round-trips after model download
3. **Cost**: Zero API usage fees or rate limits imposed by external providers

The `AiTranslateManager` class encapsulates all translator interactions, handling model availability checks, download progress tracking, and graceful degradation when the API is unsupported or a language pair is unavailable.

```typescript
type TranslatorAPI = {
    availability?: (opts: { sourceLanguage?: string; targetLanguage: string }) =>
        Promise<<"available" | "downloadable" | "downloading" | "unavailable">;
    create: (opts: TranslatorCreateOptions) => Promise<<TranslatorInstance>;
};
```

Before enabling translation, the system performs a capability probe: it checks `Translator.availability()` for the desired language pair, then runs a sanity translation of the word "test" to confirm the model is truly ready. This two-stage validation prevents false positives where the API reports availability before the model has finished initialization.

### Intelligent DOM Translation Engine

Translating a live React application is more complex than replacing text content. The engine must distinguish between static content, dynamically injected components, user-generated input, and code blocks. The `AiTranslateManager` implements a multi-layer filtering system:

**Tag Exclusions**: Content inside `<script>`, `<style>`, `<code>`, `<pre>`, `<svg>`, and `<canvas>` elements is never translated. These tags are excluded at the tree-walker level to prevent breaking syntax highlighting, mathematical notation, or interactive visualizations.

**Marker-Based Opt-Out**: Any element or its ancestor carrying `data-no-ai-translate` is skipped. This allows components like the language switcher itself, brand names, or code snippets to remain in their original language regardless of user settings.

**Attribute Translation**: Beyond visible text, the system translates accessibility-critical attributes including `title`, `aria-label`, `aria-description`, `alt`, and `placeholder`. This ensures that tooltips, screen reader announcements, and form hints remain meaningful after translation.

### Case Pattern Preservation

Neural translation models typically normalize casing, which destroys intentional styling like all-caps headings or title-case navigation labels. The engine detects five casing patterns before translation and reapplies them to the translated result:

- **upper**: `ABOUT US` → `SOBRE NOSOTROS`
- **lower**: `about us` → `sobre nosotros`
- **capitalized**: `About us` → `Sobre nosotros`
- **title**: `About Us` → `Sobre Nosotros`
- **none**: Mixed or irregular casing is left as-is

This detection uses Unicode-aware regex (`\p{L}`) to handle scripts beyond Latin, ensuring that Greek, Cyrillic, and CJK headings retain their intended visual hierarchy.

### Streaming and Concurrency Management

Long articles could block the UI if translated sentence-by-sentence in a single batch. The engine implements two strategies to maintain responsiveness:

**Streaming Translation**: For text nodes exceeding 150 characters, the system attempts to use `translator.translateStreaming()`, which returns a `ReadableStream` of partial results. The DOM updates incrementally as chunks arrive, giving users immediate visual feedback rather than a frozen page followed by a sudden content swap.

**Concurrency Limiting**: All translation requests pass through a semaphore-limited worker pool capped at 3 parallel operations. This prevents the browser's AI runtime from throttling or aborting requests under heavy load, and it smooths CPU usage during full-page translation.

### MutationObserver for Dynamic Content

Modern web applications mutate the DOM continuously: React hydration, lazy-loaded components, and client-side navigation all inject new text after the initial translation pass. The engine starts a `MutationObserver` on `document.documentElement` watching for `childList`, `characterData`, and `attribute` changes.

When mutations fire, the observer:

1. Collects newly added text nodes and modified attributes
2. Filters out nodes already translated to the current target language
3. Skips nodes currently marked as "translating" to prevent race conditions
4. Queues the remaining nodes through the same concurrency-limited pipeline

This design makes the system resilient to route changes in Next.js App Router. When a user navigates to a new page, the observer detects the fresh DOM subtree and translates it automatically without requiring a manual refresh or re-enable action.

### Context-Aware Caching

Translating identical strings repeatedly wastes compute and degrades perceived performance. The engine maintains an in-memory `Map` cache keyed by a structured hash that includes:

- The original text
- Source and target language codes
- Translation scope (`text`, `attr`, or `ui`)
- Element tag name and attribute name (for attribute translations)

This context awareness prevents collisions where the same English word might translate differently depending on whether it appears as button text (`"Save"` → `"Guardar"`) or an image alt attribute (`"Save"` → `"Guardar imagen"`).

The cache is ephemeral (cleared on page reload) which balances hit rates against memory usage on long browsing sessions.

### State Management and UI Integration

Translation state is managed through a React Context (`AITranslationProvider`) that wraps the application layout. It exposes:

- `active`: Whether AI translation is currently enabled
- `supported`: Whether the browser supports the Translator API
- `targetLang`: The currently selected target language code
- `progress`: Real-time download and translation progress
- `enable()` / `disable()`: Imperative controls

The provider hooks into Next.js route changes via `usePathname()`. When navigation occurs while translation is active, it triggers `aiTranslateManager.refresh()`, which re-scans the new page content without recreating the underlying translator instance. This avoids the `NotAllowedError` that Chrome throws when creating a translator outside a user gesture context.

![AI translation status bar: translation to Arabic in progress.](../../../../assets/projects/gdguam/website/ai-translations/status-bar.webp)

### Language Switcher UX

The `LanguageSwitcher` component unifies manual locale selection (Spanish/English, served by Paraglide) and AI-powered translation into a single dropdown. Its design addresses several UX challenges:

**Availability Probing**: When the dropdown opens, the system lazily checks which of the 39 AI-supported languages are available for the current source language. Languages report statuses of `available`, `downloadable`, `downloading`, or `unavailable`. Only available languages are clickable; others show a spinner during model download or are disabled.

**Persistent Preferences**: If a user selects an AI-translated language, the choice is persisted to `localStorage` as `ai-target-lang`. On subsequent visits, the system auto-restores the translation before React hydrates, ensuring the page appears in the user's preferred language immediately.

**Visual Feedback**: A sticky banner (`AITranslationBanner`) appears at the top of the viewport during active translation. It shows:

- An indeterminate shimmer bar while the language model downloads
- A determinate progress bar during DOM translation
- A warning icon with a disclaimer about potential translation inaccuracy once complete

The banner's height is dynamically exposed as a CSS variable (`--navbar-height`) so that sticky navigation and mobile menus can adjust their offset in real time.

<div style="max-width: 300px; margin: 0 auto;">

![Language selection dropdown menu.](../../../../assets/projects/gdguam/website/ai-translations/menu.webp)

</div>

### Graceful Degradation and Error Recovery

The system is designed to fail silently and recover predictably:

- **Unsupported Browsers**: The AI switcher simply does not render if `window.Translator` is absent
- **Download Failures**: If model download progress callbacks are unsupported, the engine falls back to a polling probe that attempts tiny translation calls every 250ms until success
- **Translation Errors**: Individual node failures are logged but do not abort the entire batch; the engine continues with remaining content
- **Abort Errors**: Cancelled translation sessions (e.g., user switches language mid-translation) are swallowed to prevent console noise
- **Restore on Disable**: When the user turns off AI translation or switches to a manual locale, all text nodes and attributes are restored to their original values using `WeakMap` references captured at first translation

## Challenges and Solutions

### Challenge: User Gesture Requirements

Chrome's Translator API requires a user gesture to create a translator instance. This conflicts with Next.js client-side navigation, where route changes occur programmatically.

**Solution**: The `refresh()` method reuses the existing translator instance rather than creating a new one. Since the instance was originally created during a click gesture (language selection), subsequent route changes can call `translate()` freely without violating the gesture policy.

### Challenge: Hydration Mismatches

Server-rendered HTML contains English or Spanish text, but `localStorage` might indicate the user prefers Japanese. If the AI system activates before React hydration completes, it could modify DOM nodes that React expects to own.

**Solution**: The auto-start logic runs inside a `useEffect` with an `initializedRef` guard, ensuring it only executes after React has mounted. The banner and language switcher default to non-AI states on the server, eliminating hydration mismatches entirely.

### Challenge: Preserving Interactive State

Translating form inputs or dynamic lists could overwrite user-typed values or React state.

**Solution**: The engine only translates `Text` nodes and specific attributes. It never modifies `<input>` values, `<textarea>` content, or React component props directly. The `data-no-ai-translate` marker provides an escape hatch for components that manage their own text content imperatively.