provisioning-outreach/presentations/rust-laspalmas-250926/info/aurora_18n_ftl_plan.md

considering we want to stick to nushell, how can we introduce i18n and fluent files into this framework project for pages ?
  do we need to crate a nushell plugin for i18n and FTL files ?
  Let us ultrathink on this for easy to use, admin and generate via AI or builders

✻ Thinking…

  The user is asking about introducing internationalization (i18n) and Fluent (.ftl) files into the AuroraFrame project. They want to stick with Nushell and are
  wondering if they need to create a Nushell plugin for i18n and FTL files. They want me to think deeply about making it easy to use, administer, and generate via
   AI or builders.

  Let me think about this:

  1. Fluent is Mozilla's localization system that uses .ftl files for translations. It's more powerful than traditional i18n systems because it handles
  pluralization, gender, and complex formatting rules.
  2. Current Architecture: AuroraFrame is built with:
    - Nushell for scripting
    - KCL for configuration
    - Tera for templating
    - AI integration via MCP
  3. Options for i18n integration:
    - Native Nushell plugin for Fluent
    - Use existing Rust fluent-rs library via a wrapper
    - Integrate at the Tera template level
    - Build a custom solution using Nushell's data processing
  4. Considerations:
    - Easy to use for developers
    - AI-friendly for content generation
    - Works with the multi-output strategy (web/email/mobile)
    - Type-safe with KCL schemas

  Let me think about the best approach:

  Since we're in plan mode, I should research what's available and present a comprehensive plan for implementing i18n with Fluent in the AuroraFrame.

  I should look at:

- How Fluent works
- How to integrate it with Nushell
- How to make it work with the existing KCL schemas
- How to make it AI-friendly
- How to support multiple output formats

⏺ Let me deeply analyze the i18n and Fluent integration options for AuroraFrame within the Nushell ecosystem.

  Now let me think about how to design a comprehensive i18n solution for AuroraFrame that:

  1. Stays within the Nushell ecosystem
  2. Uses Fluent/FTL files
  3. Is easy to use for developers
  4. Can be generated/managed via AI
  5. Works with the existing KCL schema system
  6. Integrates with Tera templates
  7. Supports multiple output formats (web/email/mobile)

   🌐 Deep Analysis: i18n & Fluent Integration for AuroraFrame

  After analyzing the requirements and ecosystem, here's my comprehensive approach for integrating i18n with Fluent into AuroraFrame:

  Architecture Overview

  ┌─────────────────────────────────────────────────────┐
  │                   AuroraFrame i18n                   │
  ├─────────────────────────────────────────────────────┤
  │  KCL Schemas  →  AI Generator  →  FTL Files         │
  │       ↓              ↓                ↓             │
  │  Type Safety    MCP Server    Fluent Bundle         │
  │       ↓              ↓                ↓             │
  │  Validation    Translations   Template Engine       │
  │       ↓              ↓                ↓             │
  │  [Web Output] [Email Output] [Mobile Output]        │
  └─────────────────────────────────────────────────────┘

  Proposed Solution: Hybrid Approach

  1. nu_plugin_fluent (Rust Plugin)

  Create a performant Nushell plugin that wraps fluent-rs:

  // Core functionality

- parse_ftl: Parse FTL files into message bundles
- localize: Get localized messages with arguments
- validate_ftl: Check FTL syntax and references
- list_messages: Extract all message IDs for type checking

  1. Native Nushell i18n Framework

  Pure Nushell orchestration layer for developer experience:

# High-level commands

  aurora i18n init         # Initialize i18n for project
  aurora i18n add <locale> # Add new locale
  aurora i18n generate     # AI-generate translations
  aurora i18n validate     # Check all translations
  aurora i18n extract      # Extract strings from templates

  1. KCL Schema Integration

  Type-safe message definitions:

  schema I18nMessage:
      id: str                    # Message ID
      description: str           # Context for translators
      parameters: [Parameter]    # Type-safe parameters
      variants: [Variant]        # Plurals, gender, etc.

  schema LocaleConfig:
      code: str                  # en-US, es-ES, etc.
      name: str                  # English, Spanish
      fallback: str?             # Fallback locale
      direction: "ltr" | "rtl"   # Text direction

  Implementation Plan

  Phase 1: Core Plugin Development

  nu_plugin_fluent (Rust):
  use nu_plugin::{Plugin, PluginCommand};
  use fluent::{FluentBundle, FluentResource};

  struct FluentPlugin;

  impl Plugin for FluentPlugin {
      fn commands(&self) -> Vec<Box<dyn PluginCommand>> {
          vec![
              Box::new(ParseFtl),
              Box::new(Localize),
              Box::new(ValidateFtl),
              Box::new(ExtractMessages),
          ]
      }
  }

  // Command: localize
  // Usage: fluent localize "welcome-message" --locale "en-US" --args {name: "User"}

  Phase 2: Nushell Framework Layer

  framework/i18n.nu:

# Smart locale detection

  export def detect_locale [] {
      # Check: URL param > Cookie > Header > System > Default
      let url_locale = ($env.QUERY_PARAMS?.locale?)
      let cookie_locale = ($env.COOKIES?.locale?)
      let header_locale = parse_accept_language $env.ACCEPT_LANGUAGE?
      let system_locale = ($env.LANG? | str substring 0..5)
      let default_locale = "en-US"

      $url_locale | default $cookie_locale | default $header_locale | default $system_locale | default $default_locale
  }

# Fluent message loader with caching

  export def load_messages [locale: string, namespace: string = "main"] {
      let cache_key = $"($locale):($namespace)"

      if $cache_key in $i18n_cache {
          return ($i18n_cache | get $cache_key)
      }

      let ftl_path = $"locales/($locale)/($namespace).ftl"
      let messages = (fluent parse_ftl $ftl_path)

      $i18n_cache = ($i18n_cache | insert $cache_key $messages)
      $messages
  }

  Phase 3: AI-Powered Generation

  MCP Integration for Translation:

# AI-powered FTL generation

  export def "ai i18n generate" [
      source_locale: string = "en-US"
      target_locale: string
      --context: string      # Additional context for AI
  ] {
      # Extract messages from source
      let source_messages = (fluent extract_messages $"locales/($source_locale)")

      # Generate via MCP
      let translations = (aurora ai translate $source_messages
          --from $source_locale
          --to $target_locale
          --format ftl
          --context $context)

      # Validate and save
      let validated = (fluent validate_ftl $translations)
      $translations | save $"locales/($target_locale)/messages.ftl"
  }

  Phase 4: Template Integration

  Tera Filter for i18n:

# Register Tera filter

  export def register_i18n_filters [tera_env: any] {
      # Add 'fluent' filter to Tera
      # Usage in template: {{ "welcome-message" | fluent(name="User") }}

      let fluent_filter = {|msg_id, args|
          let locale = (detect_locale)
          let messages = (load_messages $locale)
          fluent localize $msg_id --bundle $messages --args $args
      }

      $tera_env | add_filter "fluent" $fluent_filter
      $tera_env | add_filter "t" $fluent_filter  # Alias
  }

  FTL File Structure

  locales/
  ├── en-US/
  │   ├── main.ftl          # Main messages
  │   ├── errors.ftl        # Error messages
  │   └── emails.ftl        # Email-specific
  ├── es-ES/
  │   ├── main.ftl
  │   ├── errors.ftl
  │   └── emails.ftl
  └── locale.kcl             # Locale configuration

  Example FTL (main.ftl):

# Brand terms

  -brand-name = AuroraFrame

# Welcome section

  welcome-title = Welcome to { -brand-name }
  welcome-message =
      { $user_type ->
          [new] Start your journey with { -brand-name }
          [returning] Welcome back to { -brand-name }
         *[other] Welcome to { -brand-name }
      }

# Pluralization

  page-count =
      { $count ->
          [0] No pages
          [one] 1 page
         *[other] { $count } pages
      } built in { $time }ms

  Easy Admin Interface

  CLI Commands:

# Initialize i18n

  aurora i18n init --locales en-US,es-ES,fr-FR

# Add translations interactively

  aurora i18n add-message
  > Message ID: welcome-title
  > Default text: Welcome to {-brand-name}
  > Description: Main welcome heading

# Generate missing translations

  aurora i18n sync --ai

# Validate all locales

  aurora i18n validate --fix

# Extract from templates

  aurora i18n extract src/**/*.html

  AI Builder Integration

# AI-powered message builder

  export def "ai i18n builder" [] {
      print "🤖 AuroraFrame i18n AI Builder"

      # Analyze project structure
      let pages = (find_pages)
      let components = (find_components)

      # Generate message suggestions
      let suggestions = (aurora ai analyze
          --prompt "Generate i18n message structure for these pages and components"
          --context {pages: $pages, components: $components})

      # Interactive review
      for msg in $suggestions {
          print $"Suggested: ($msg.id)"
          print $"  Text: ($msg.default_text)"
          let approve = (input "Add this message? (y/n/edit): ")

          if $approve == "y" {
              add_message $msg
          } else if $approve == "edit" {
              let edited = (edit_message $msg)
              add_message $edited
          }
      }
  }

  Multi-Output Support

# Different formatting per output type

  export def format_for_output [text: string, output_type: string] {
      match $output_type {
          "web" => $text  # HTML-safe output
          "email" => ($text | strip_markdown | wrap_email_template)
          "mobile" => ({
              text: $text,
              rtl: (is_rtl_locale (detect_locale)),
              formatted: (parse_fluent_markup $text)
          } | to json)
      }
  }

  Type Safety with KCL

# locale-config.k

  import "messages.k"

  locales: [LocaleConfig] = [
      {
          code = "en-US"
          name = "English (US)"
          messages = messages_en_US
          fallback = None
      }
      {
          code = "es-ES"
          name = "Español"
          messages = messages_es_ES
          fallback = "en-US"
      }
  ]

# Compile-time validation

  check:
      all locale in locales {
          locale.messages.keys() == required_message_ids
      }

  Benefits of This Approach

  1. Performance: Rust plugin for fast FTL parsing
  2. Developer Experience: Pure Nushell commands
  3. Type Safety: KCL validates message IDs
  4. AI-Ready: Built for content generation
  5. Multi-Output: Format per platform
  6. Hot Reload: Watch FTL files for changes
  7. Extensible: Easy to add new locales
  8. Testable: Validate all translations

  Why Not Pure Nushell?

  While we could parse FTL in pure Nushell, using fluent-rs via plugin provides:

- Battle-tested FTL parser
- Complex plural/gender rules
- Performance for large message catalogs
- Compatibility with Fluent ecosystem

  Next Steps

  1. Create nu_plugin_fluent Rust crate
  2. Implement core i18n.nu framework
  3. Add MCP tools for translation
  4. Create example multilingual site
  5. Document best practices

  This architecture provides the best of all worlds: Rust performance, Nushell ergonomics, AI assistance, and type safety - perfectly aligned with
  AuroraFrame's philosophy.

    i18n & Fluent Integration Plan for AuroraFrame

     Implementation Steps:

     1. Create nu_plugin_fluent (Rust Plugin)
       - Wrap fluent-rs for FTL parsing and localization
       - Commands: parse_ftl, localize, validate_ftl, extract_messages
       - Handle plurals, gender, and complex language rules
     2. Build Nushell i18n Framework (framework/i18n.nu)
       - High-level commands: aurora i18n init/add/generate/validate
       - Smart locale detection (URL > Cookie > Header > System)
       - Message caching and hot reload
       - Multi-output formatting (web/email/mobile)
     3. Integrate with KCL Schemas
       - Define I18nMessage and LocaleConfig schemas
       - Type-safe message IDs and parameters
       - Compile-time validation of translations
     4. Add AI-Powered Translation via MCP
       - Generate FTL files from schemas
       - Auto-translate between locales
       - Interactive message builder
       - Context-aware suggestions
     5. Create Tera Template Integration
       - Add 'fluent' and 't' filters for templates
       - Format output per platform (web/email/mobile)
       - Handle RTL languages properly

     File Structure:

     auroraframe-fluent-plugin/     # Rust plugin
     locales/                        # FTL files per locale
     framework/i18n.nu              # Nushell i18n framework
     framework/i18n-schemas.k       # KCL type definitions

     Benefits:

     - Type-safe i18n with compile-time checking
     - AI-assisted translation generation
     - Native Nushell developer experience
     - Fast Rust-powered FTL processing
     - Multi-platform output support

     This hybrid approach leverages Rust for performance, Nushell for ergonomics, and AI for content generation - perfectly aligned with
     AuroraFrame's architecture.

      but locales can be global or/and extended per page !!!
  probably we shoud require to have some kind of site and page settings for build tasks !!!

✻ Thinking…

  Excellent point! The user is pointing out that locales should be flexible and hierarchical:

  1. Global locales - site-wide translations (navigation, footer, common UI elements)
  2. Page-specific locales - content that's specific to individual pages
  3. Extended/overridden locales - where pages can override or extend global translations

  This means we need:

- A hierarchical locale system
- Site-level settings for default/available locales
- Page-level settings for locale overrides/extensions
- A build system that merges these appropriately
- KCL schemas to define this structure

  This is much more sophisticated than a simple flat locale structure. We need:

  1. Site Configuration (site.k or similar):
    - Available locales
    - Default locale
    - Fallback chains
    - Global message namespaces
  2. Page Configuration (per page):
    - Page-specific locale overrides
    - Additional locale files
    - Locale inheritance rules
  3. Build Process:
    - Merge global + page-specific locales
    - Handle conflicts/overrides
    - Generate per-page locale bundles
    - Optimize for performance
  4. Directory Structure:
  locales/
  ├── global/           # Site-wide translations
  │   ├── en-US/
  │   ├── es-ES/
  │   └── fr-FR/
  ├── pages/            # Page-specific translations
  │   ├── blog/
  │   │   ├── en-US/
  │   │   └── es-ES/
  │   └── products/
  │       ├── en-US/
  │       └── es-ES/
  └── locale.k          # Locale configuration

  This requires rethinking the architecture to be more sophisticated and build-aware.

⏺ You're absolutely right! That's a crucial architectural insight. We need a hierarchical locale system with global + page-specific
  locales, integrated with build settings. Let me redesign this properly:

✻ Thinking…

  The user is absolutely right. Let me redesign the i18n system with this hierarchical approach. I need to:

  1. Create KCL schemas for site and page configuration that includes locale settings
  2. Design directory structure that supports global and page-specific locales
  3. Build system integration that merges locales during build
  4. Locale resolution that follows a priority chain: page-specific > global > fallback

  Let me start with the configuration schemas and directory structure.

⏺ 🌐 Enhanced Hierarchical Locale Architecture

  You're absolutely correct! Let me redesign this with proper global + page-specific locale architecture integrated with build settings: