"""Internationalization support for the RAG demo"""

TRANSLATIONS = {
    "en": {
        # Corpus tab
        "corpus_management": "Corpus Management",
        "corpus_description": "Upload a PDF document or use the default corpus. The document will be split into chunks for retrieval.",
        "upload_pdf": "Upload PDF",
        "chunk_size": "Chunk Size (characters)",
        "chunk_overlap": "Chunk Overlap (characters)",
        "process_corpus": "Process Corpus",
        "status": "Status",

        # Retrieval tab
        "retrieval_config": "Retrieval Configuration",
        "embedding_model": "Embedding Model",
        "top_k": "Top K (number of chunks to retrieve)",
        "similarity_threshold": "Similarity Threshold (minimum score)",

        # Generation tab
        "generation_config": "Generation Configuration",
        "llm_model": "Language Model",
        "temperature": "Temperature (creativity)",
        "max_tokens": "Max Tokens (response length)",

        # Query tab
        "ask_question": "Ask a Question",
        "your_question": "Your Question",
        "question_placeholder": "Enter your question here...",
        "example_questions": "Example Questions",
        "submit_query": "Submit Query",
        "answer": "Answer",
        "retrieved_chunks": "Retrieved Chunks",
        "prompt_sent": "Prompt Sent to LLM",
        "errors": "Errors",

        # Results
        "similarity_score": "Similarity Score",
        "no_corpus": "Please process a corpus first in the Corpus tab.",

        # Messages
        "error": "Error",
        "success": "Success",
        "processing": "Processing...",
    },
    "fr": {
        # Onglet Corpus
        "corpus_management": "Gestion du Corpus",
        "corpus_description": "Téléchargez un document PDF ou utilisez le corpus par défaut. Le document sera divisé en chunks pour la récupération.",
        "upload_pdf": "Télécharger un PDF",
        "chunk_size": "Taille des Chunks (caractères)",
        "chunk_overlap": "Chevauchement des Chunks (caractères)",
        "process_corpus": "Traiter le Corpus",
        "status": "Statut",

        # Onglet Retrieval
        "retrieval_config": "Configuration du Retrieval",
        "embedding_model": "Modèle d'Embedding",
        "top_k": "Top K (nombre de chunks à récupérer)",
        "similarity_threshold": "Seuil de Similarité (score minimum)",

        # Onglet Génération
        "generation_config": "Configuration de la Génération",
        "llm_model": "Modèle de Langage",
        "temperature": "Température (créativité)",
        "max_tokens": "Max Tokens (longueur de la réponse)",

        # Onglet Query
        "ask_question": "Poser une Question",
        "your_question": "Votre Question",
        "question_placeholder": "Entrez votre question ici...",
        "example_questions": "Questions d'Exemple",
        "submit_query": "Soumettre la Question",
        "answer": "Réponse",
        "retrieved_chunks": "Chunks Récupérés",
        "prompt_sent": "Prompt Envoyé au LLM",
        "errors": "Erreurs",

        # Résultats
        "similarity_score": "Score de Similarité",
        "no_corpus": "Veuillez d'abord traiter un corpus dans l'onglet Corpus.",

        # Messages
        "error": "Erreur",
        "success": "Succès",
        "processing": "Traitement en cours...",
    }
}

def get_text(key, language="en"):
    """Get translated text for a given key and language"""
    return TRANSLATIONS.get(language, TRANSLATIONS["en"]).get(key, key)