Laratext Laravel Package

Product Decisions This Supports

• Internationalization (i18n) Strategy: Enables a scalable, automated approach to localization, reducing manual effort in maintaining translation files across multiple languages.
• Developer Experience (DX): Simplifies translation workflows by eliminating ambiguity in translation keys (e.g., no more guessing what key_name refers to) while preserving flexibility for dynamic content.
• Cost Efficiency: Integrates with affordable translation APIs (e.g., OpenAI’s gpt-5.4-nano) and supports batch processing to minimize API costs during bulk translations.
• Roadmap Prioritization:
  • Phase 1: Adopt for core product strings to reduce localization backlog.
  • Phase 2: Extend to user-generated content (UGC) or dynamic templates (e.g., emails) where placeholders (:name) are critical.
  • Phase 3: Custom translator for domain-specific terminology (e.g., legal/medical jargon) via TranslatorInterface.
• Build vs. Buy: Avoids reinventing translation infrastructure (e.g., custom scripts for key extraction/translation) while offering more control than SaaS tools like Lokalise.
• Use Cases:
  • Multilingual SaaS platforms (e.g., dashboards, onboarding flows).
  • Content-heavy apps (e.g., blogs, e-commerce product pages).
  • Global enterprises needing compliance with regional language requirements.

When to Consider This Package

• Adopt if:
  • Your Laravel app requires >3 languages and translations are a bottleneck (e.g., manual JSON edits, broken keys).
  • You need automated drift detection (e.g., source text changes in code but translations lag).
  • Your team lacks dedicated localization resources but can invest in API costs (e.g., OpenAI credits).
  • You use Blade templates or PHP helpers for dynamic content with placeholders (e.g., :user_name).
• Look elsewhere if:
  • You only support 1–2 languages (overhead of API keys/configuration may not justify benefits).
  • Your translations require human review (e.g., legal/brand-sensitive content) before deployment.
  • You’re constrained by API quotas (e.g., Google Translate’s free tier limits) and have high translation volume.
  • Your app uses non-Laravel frameworks (e.g., React Native, Django) or static sites.
  • You need offline translation tools (e.g., POEditor integration) or CAT tools (e.g., Crowdin, Pootle).

How to Pitch It (Stakeholders)

For Executives (Business Case)

"Laratext automates 80% of our localization workflow, cutting translation costs by [X]% and reducing time-to-market for new languages. By integrating with OpenAI/Google Translate, we eliminate manual JSON file management—freeing up [Team Name] to focus on growth. For example, [Competitor] launches in 5 languages in 3 months; we can match that with minimal overhead. The --prune feature also cleans up stale translations, reducing storage costs. ROI: [Estimated savings from reduced dev hours/API costs]."

Key Metrics to Track:

• % reduction in manual translation effort.
• Time saved per language addition (e.g., "From 2 weeks to 2 days").
• API cost per translation (e.g., "$0.005/key" vs. "$0.10/key" with human translators).

For Engineering (Technical Value)

*"Laratext solves two critical pain points:

1. Translation Key Ambiguity: No more guessing what auth.login.button means—it now stores both the key and default text (e.g., text('auth.login.button', 'Sign In')), with auto-generated fallbacks (e.g., text('user.profile') → "Profile").
2. Automated Sync: The laratext:scan command detects:
   • New keys in code → translates them.
   • Drifted keys (source text changed) → retranslates them.
   • Orphan keys (unused in code) → optionally prunes them. Example: After editing a Blade file, run php artisan laratext:scan --write to auto-update all languages in one command.

Integration Effort:

• Low: Drop-in replacement for Laravel’s __() helper. Replace:

  __('auth.login.button') // Ambiguous
  

  with:

  text('auth.login.button') // Self-documenting
  

• Blade Support: Use @text('key') directly in views.
• API Flexibility: Swap between OpenAI, Google, or custom translators via config. Example:

  // config/texts.php
  'default_translator' => \EduLazaro\Laratext\Translators\ClaudeTranslator::class;
  

DevOps Considerations:

• Add to CI pipeline to run laratext:scan --write --prune nightly.
• Monitor API costs (e.g., OpenAI’s gpt-5.4-nano is ~$0.000005/token).
• Cache translations locally to reduce API calls for unchanged keys.

Call to Action: "Let’s pilot this for our [Module X] with 3 languages (EN/ES/FR). If it reduces localization time by 50%, we’ll expand to all product areas."