from fastapi import APIRouter, HTTPException
from pydantic import BaseModel

from app.pipelines.text_ai import analyze_ai_text
from app.pipelines.fakenews import analyze_fakenews_text

router = APIRouter()

class TextRequest(BaseModel):
    text: str

@router.post("/analyze/text")
async def analyze_text(body: TextRequest):
    if not body.text or not body.text.strip():
        raise HTTPException(status_code=400, detail="Le texte ne peut pas être vide.")
    res = analyze_ai_text(body.text)
    return {
        "status": "success",
        "verdict": res["verdict"],
        "ai_prob": res["ai_prob"],
        "human_prob": res["human_prob"]
    }

@router.post("/analyze/fakenews")
async def analyze_fakenews(body: TextRequest):
    if not body.text or not body.text.strip():
        raise HTTPException(status_code=400, detail="Le texte ne peut pas être vide.")
    res = analyze_fakenews_text(body.text)
    return {
        "status": "success",
        "verdict": res["verdict"],
        "fake_prob": res["fake_prob"],
        "real_prob": res["real_prob"]
    }

@router.post("/analyze/text/full")
async def analyze_text_full(body: TextRequest):
    if not body.text or not body.text.strip():
        raise HTTPException(status_code=400, detail="Le texte ne peut pas être vide.")
    res_ai = analyze_ai_text(body.text)
    res_fn = analyze_fakenews_text(body.text)
    
    is_ai = res_ai["is_ai"]
    is_fake = res_fn["is_fake"]
    
    if is_ai and is_fake:
        verdict = "DANGER MAX : Fake news générée par IA"
    elif is_ai and not is_fake:
        verdict = "Texte IA mais contenu vérifié"
    elif not is_ai and is_fake:
        verdict = "Désinformation humaine"
    else:
        verdict = "Texte humain, contenu vérifié"
        
    return {
        "status": "success",
        "verdict": verdict,
        "ai_prob": res_ai["ai_prob"],
        "fake_news_prob": res_fn["fake_prob"],
        "is_ai_generated": is_ai,
        "is_fake_news": is_fake
    }