Add English language support with i18n implementation
Implemented comprehensive internationalization (i18n) for both frontend and backend: Frontend: - Added react-i18next configuration with Spanish (default) and English - Created translation files (locales/es.json, locales/en.json) - Refactored core components to use i18n: LoginPage, DashboardHeader, DataUploader - Created LanguageSelector component with toggle between ES/EN - Updated API client to send Accept-Language header Backend: - Created i18n module with translation dictionary for error messages - Updated security.py to return localized authentication errors - Updated api/analysis.py to return localized validation errors - Implemented language detection from Accept-Language header Spanish remains the default language ensuring backward compatibility. Users can switch between languages using the language selector in the dashboard header. https://claude.ai/code/session_1N9VX
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Claude
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backend/beyond_api/i18n.py
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128
backend/beyond_api/i18n.py
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"""
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Módulo de internacionalización para Beyond API.
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Proporciona traducciones para mensajes de error, validaciones y clasificaciones.
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"""
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from typing import Literal
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Language = Literal["es", "en"]
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# Diccionario de traducciones
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MESSAGES = {
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"es": {
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# Errores de autenticación
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"auth.credentials_required": "Credenciales requeridas",
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"auth.incorrect_credentials": "Credenciales incorrectas",
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# Errores de análisis
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"analysis.invalid_type": "analysis debe ser 'basic' o 'premium'.",
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"analysis.invalid_economy_json": "economy_json no es un JSON válido.",
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"analysis.no_cached_file": "No hay archivo cacheado en el servidor. Sube un archivo primero.",
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"analysis.execution_error": "Error ejecutando análisis: {error}",
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# Errores de validación
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"validation.field_not_numeric": "El campo '{field}' debe ser numérico (float). Valor recibido: {value}",
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"validation.segments_not_dict": "customer_segments debe ser un diccionario {segment: level}",
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"validation.segment_value_not_str": "El valor de customer_segments['{key}'] debe ser str. Valor recibido: {value}",
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"validation.csv_not_found": "El CSV no existe: {path}",
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"validation.not_csv_file": "La ruta no apunta a un fichero CSV: {path}",
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"validation.missing_columns": "Faltan columnas obligatorias para {metric}: {missing}",
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# Clasificaciones Agentic Readiness
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"agentic.ready_for_copilot": "Listo para Copilot",
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"agentic.ready_for_copilot_desc": "Procesos con predictibilidad y simplicidad suficientes para asistencia IA (sugerencias en tiempo real, autocompletado).",
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"agentic.optimize_first": "Optimizar primero",
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"agentic.optimize_first_desc": "Estandarizar procesos y reducir variabilidad antes de implementar asistencia IA.",
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"agentic.requires_human": "Requiere gestión humana",
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"agentic.requires_human_desc": "Procesos complejos o variables que necesitan intervención humana antes de considerar automatización.",
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},
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"en": {
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# Authentication errors
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"auth.credentials_required": "Credentials required",
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"auth.incorrect_credentials": "Incorrect credentials",
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# Analysis errors
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"analysis.invalid_type": "analysis must be 'basic' or 'premium'.",
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"analysis.invalid_economy_json": "economy_json is not valid JSON.",
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"analysis.no_cached_file": "No cached file on server. Upload a file first.",
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"analysis.execution_error": "Error executing analysis: {error}",
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# Validation errors
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"validation.field_not_numeric": "Field '{field}' must be numeric (float). Received value: {value}",
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"validation.segments_not_dict": "customer_segments must be a dictionary {segment: level}",
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"validation.segment_value_not_str": "Value of customer_segments['{key}'] must be str. Received value: {value}",
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"validation.csv_not_found": "CSV does not exist: {path}",
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"validation.not_csv_file": "Path does not point to a CSV file: {path}",
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"validation.missing_columns": "Missing required columns for {metric}: {missing}",
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# Agentic Readiness classifications
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"agentic.ready_for_copilot": "Ready for Copilot",
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"agentic.ready_for_copilot_desc": "Processes with sufficient predictability and simplicity for AI assistance (real-time suggestions, autocomplete).",
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"agentic.optimize_first": "Optimize first",
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"agentic.optimize_first_desc": "Standardize processes and reduce variability before implementing AI assistance.",
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"agentic.requires_human": "Requires human management",
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"agentic.requires_human_desc": "Complex or variable processes that need human intervention before considering automation.",
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}
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}
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def t(key: str, lang: Language = "es", **kwargs) -> str:
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"""
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Traduce un mensaje al idioma especificado.
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Args:
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key: Clave del mensaje (ej: 'auth.credentials_required')
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lang: Idioma ('es' o 'en'). Por defecto 'es'
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**kwargs: Variables para interpolación (ej: field='nombre', value='123')
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Returns:
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Mensaje traducido con variables interpoladas
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Examples:
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>>> t('auth.credentials_required', 'en')
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'Credentials required'
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>>> t('validation.field_not_numeric', 'en', field='age', value='abc')
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"Field 'age' must be numeric (float). Received value: abc"
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"""
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messages = MESSAGES.get(lang, MESSAGES["es"])
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message = messages.get(key, key)
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# Interpolar variables si se proporcionan
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if kwargs:
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try:
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return message.format(**kwargs)
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except KeyError:
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# Si falta alguna variable, devolver el mensaje sin interpolar
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return message
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return message
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def get_language_from_header(accept_language: str | None) -> Language:
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"""
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Extrae el idioma preferido del header Accept-Language.
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Args:
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accept_language: Valor del header Accept-Language (ej: 'en-US,en;q=0.9,es;q=0.8')
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Returns:
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'en' si el idioma preferido es inglés, 'es' en caso contrario
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Examples:
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>>> get_language_from_header('en-US,en;q=0.9')
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'en'
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>>> get_language_from_header('es-ES,es;q=0.9')
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'es'
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>>> get_language_from_header(None)
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'es'
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"""
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if not accept_language:
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return "es"
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# Extraer el primer idioma del header
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primary_lang = accept_language.split(',')[0].split('-')[0].strip().lower()
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return "en" if primary_lang == "en" else "es"
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