from fastapi import FastAPI, Request
from transformers import pipeline

app = FastAPI()

# Usiamo un modello DISTILLATO (molto leggero per CPU Free)
classifier = pipeline("zero-shot-classification", model="typeform/distilbert-base-uncased-mnli")

@app.get("/")
def home():
    return {"status": "SICURISSIMO AI V170 ONLINE"}

@app.post("/analyze")
async def analyze(request: Request):
    try:
        data = await request.json()
        testo = data.get("text", "")
        cliente = data.get("client_name", "Anonimo")
        
        # Etichette semplificate per stabilità
        labels = ["pericolo sicurezza", "haccp igiene", "scadenza documenti", "formazione"]
        
        # Analisi
        res = classifier(testo, labels)
        top_label = res['labels'][0]
        score = res['scores'][0]
        
        # Calcolo Lead Score (0-100)
        lead_heat = int(score * 100)
        if top_label == "pericolo sicurezza":
            lead_heat = min(lead_heat + 20, 100)
            
        return {
            "cliente": cliente,
            "analisi_top": top_label,
            "punteggio": round(score, 2),
            "intervento_necessario": True if score > 0.6 else False,
            "lead_score": lead_heat
        }
    except Exception as e:
        return {"error": str(e)}

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=7860)