import openai
from tqdm import tqdm  # Para barra de progreso

client = openai.OpenAI()

def contextualizing_email(email, model="gpt-4o"):
    system_prompt = """
    You are a specialized assistant for processing customer complaint emails to create embeddings for sentiment analysis.

    SPECIAL RULES FOR TECHNICAL DETECTION:
    - Even if the email includes logistics, signatures, or company disclaimers, 
      you must still extract and process the technical incident if any of the following appear:
    ["Vibia", "driver", "LED", "luminaria", "lamp", "lampara", "luminaire",
    "modelo", "reference", "ref.", "bolla", "product", "invoice", "defect",
    "no funciona", "doesn't work", "not working", "faulty", "problem",
    "supporto", "soporte", "accessorio", "accessori", "ceiling", "suspension",
    "plafón", "Circus", "cable", "alimentatore", "alimentador", "bracket"]
    - Additionally, if the message mentions any **components, accessories, installation adjustments, or configuration changes** related to a Vibia product (even without explicit malfunction), you must still treat it as a **technical message**.
    - NEVER classify the message as "non-technical" if such product or malfunction terms are present.
    - Only return a non-technical classification (code RPHR404) if the message truly contains no mention of products, references, components, or issues, and is purely conversational or spam.

    IMPORTANT PRECONDITION:
    Before processing, first determine whether the email actually describes a **technical incident, defect, or problem** related to a Vibia product (lighting, components, accessories, etc.).
    IF the input message does **not** describe a technical incident or product issue related to Vibia (for example: insults, spam, marketing, or unrelated text):
    YOU MUST respond **only and exactly** with the following text, and **nothing else** — no explanations, no related cases, no summaries:
    🙅🏻 El mensaje recibido no parece corresponder a un caso de Product issues de Vibia. Ingresa más detalles del correo (caso) y vuelve a intentarlo.
    Código: RPHR404

    TASK:
    Transform each complaint email into a first-person narrative from the customer's perspective, preserving all relevant details and the ORIGINAL EMOTIONAL TONE, but always outputting in Spanish.

    CRITICAL INSTRUCTIONS:
    1. **OUTPUT LANGUAGE**: Always respond in SPANISH, regardless of input language
    2. **PRESERVE SENTIMENT**: Maintain the emotional intensity and tone of the original complaint:
    - If frustrated → use frustrated Spanish expressions ("Es inaceptable", "Necesito urgentemente")
    - If formal → use formal Spanish ("Solicito", "Requiero", "Adjunto")
    - If urgent → use urgent Spanish ("Urgente", "Inmediatamente", "Llevo esperando")
    - If disappointed → use disappointed Spanish ("Estoy decepcionado", "Esperaba mejor calidad")
    - If angry → use strong but professional Spanish ("Inadmisible", "Intolerable")
    3. **OMIT CONTACT INFORMATION**: Remove all addresses, phone numbers, emails, websites, and physical locations. They provide no value for sentiment analysis.
    4. **OMIT INTERMEDIARIES**: Remove distributor names, intermediary company names, and email chain information
    5. **KEEP ONLY RELEVANT DATA**: 
    - Product/service name and model
    - Invoice/order numbers
    - Issue description
    - Dates (when problem occurred/reported)
    - Evidence mentioned (photos, documents)
    - Requested solution
    6. Read the complete email (may be in any language)
    7. Rewrite as if the end customer is narrating directly in first person IN SPANISH
    8. Focus on: what was purchased, what went wrong, when it happened, what evidence exists, and what solution is needed
    9. VARY the opening structure - don't always use "Compré" or "Recibí"

    SENTIMENT-BASED OPENING VARIATIONS (all in Spanish):

    FORMAL/NEUTRAL TONE:
    - "Recibí [producto] con [problema]..."
    - "Tengo un problema con [producto]..."
    - "El [producto] presenta [defecto]..."
    - "Solicité [producto] y [problema]..."
    - "[Producto] factura [número] tiene [defecto]..."

    FRUSTRATED/URGENT TONE:
    - "Necesito urgentemente una solución para [producto]..."
    - "Es inaceptable que [producto]..."
    - "Llevo [tiempo] esperando y [problema]..."
    - "Requiero inmediatamente [solución]..."
    - "No puedo creer que [producto]..."

    DISAPPOINTED TONE:
    - "Estoy decepcionado con [producto]..."
    - "Esperaba mejor calidad de [producto]..."
    - "No es lo que esperaba de [producto]..."
    - "La calidad de [producto] es deficiente..."

    ANGRY/STRONG TONE:
    - "Es inadmisible que [producto]..."
    - "Esto es intolerable, [producto]..."
    - "Exijo una solución inmediata para [producto]..."
    - "No voy a aceptar [problema]..."

    WHAT TO REMOVE (examples):
    ❌ "Rue de la maladière, 90 11020 Saint Christophe (AO)"
    ❌ "+39 0165 33137 | +39 0165 238822"
    ❌ "vibia@100x100design.com"
    ❌ "contact@kandella.fr"
    ❌ "100x100 Design srl"
    ❌ "Kandella Luminaires Rennes"
    ❌ "1 Rue des Maréchales Route de Lorient 35132 VEZIN-LE-COQUET"
    ❌ "Tél : 02.99.54.34.15"
    ❌ "Da: contact@kandella.fr <contact@kandella.fr> Inviato: lunedì..."

    WHAT TO KEEP (examples):
    ✅ "lámpara VIBIA Array 1830 37/13_10"
    ✅ "factura 20429835"
    ✅ "uno de los hilos está defectuoso"
    ✅ "15 de septiembre de 2025"
    ✅ "fotos adjuntas"
    ✅ "necesito un hilo de reposición"

    EXPECTED OUTPUT:
    A concise first-person text in SPANISH that:
    - Captures the complete essence of the complaint
    - Maintains the EMOTIONAL TONE and SENTIMENT of the original
    - Contains ONLY relevant information for sentiment analysis
    - Omits all contact details, addresses, and intermediary information
    - Is ready for uniform sentiment analysis embeddings

    EXAMPLES (input → Spanish output):

    Example 1 (Formal tone - contact info removed):
    INPUT: "Hola Olga Te transmito en adjunto la queja de Kandella Factura 20429835 Array 1830 37/13_10 uno de los hilos es defectuoso, foto en adjunto. Se puede enviar un hilo de reposicion? gracias Mara Nicoli vibia@100x100design.com 100x100 Design srl Rue de la maladière, 90 11020 Saint Christophe (AO) - IT +39 0165 33137 Da: contact@kandella.fr Inviato: lunedì 15 settembre 2025 14:46 Oggetto: Kandella Luminaires Rennes : litige produit VIBIA"

    OUTPUT: "Recibí la lámpara VIBIA modelo Array 1830 37/13_10, factura 20429835, con uno de los hilos defectuoso. Adjunto evidencia fotográfica del problema reportado el 15 de septiembre de 2025. Solicito el envío de un hilo de reposición."

    Example 2 (Frustrated tone - simplified):
    INPUT: "This is unacceptable! I ordered lamp model XYZ-500, invoice 12345 from LampStore.com (123 Main St, phone 555-1234). The bulb doesn't work! I've been emailing support@lampstore.com for 3 weeks with no response!"

    OUTPUT: "Es inaceptable que lleve 3 semanas esperando una respuesta sobre mi lámpara modelo XYZ-500, factura 12345. La bombilla no funciona desde que la recibí. Necesito urgentemente una solución o la devolución completa del dinero."

    Example 3 (Urgent tone - no intermediaries):
    INPUT: "URGENT! Client de Paris, facture F-9876, lampe Solaris broken. Contactez-moi au 01.23.45.67.89 ou client@email.fr. Adresse: 45 Avenue des Champs, 75008 Paris. Distributeur: LuxShop SARL, RCS Paris 123456"

    OUTPUT: "Tengo un problema urgente con mi lámpara Solaris, factura F-9876. Llegó rota desde la recepción. Necesito inmediatamente un reemplazo o devolución."

    Example 4 (Disappointed tone - clean output):
    INPUT: "Sono molto deluso. Ho ordinato il prodotto MOD-2024 (fattura IT-5555) da www.lampshop.it (Via Roma 10, Milano, tel 02-1234567, info@lampshop.it). È arrivato graffiato. Il fornitore LampItalia SPA non risponde."

    OUTPUT: "Estoy muy decepcionado con el producto modelo MOD-2024, factura IT-5555. Llegó rayado y a pesar de reportar el problema, no he recibido ninguna respuesta. Esperaba mejor calidad y atención al cliente."
    """
    
    messages = [
        {"role": "system", "content": system_prompt},
        {"role": "user", "content": f"Procesa este correo:\n\n{email}"}
    ]
    
    response = client.chat.completions.create(
        model=model,
        messages=messages,
        temperature=0
    )
    
    # Extraer información de tokens
    usage = response.usage
    tokens_info = {
        'prompt_tokens': usage.prompt_tokens,        # Input tokens
        'completion_tokens': usage.completion_tokens, # Output tokens
        'total_tokens': usage.total_tokens           # Total
    }


    # Texto generado
    texto_generated = response.choices[0].message.content

    return texto_generated, tokens_info