main.py

from fastapi import FastAPI
from transformers import pipeline
from PIL import Image
import requests
from io import BytesIO

app = FastAPI()

# গুগল-এর ভিশন এআই মডেল
classifier = pipeline("image-classification", model="google/vit-base-patch16-224")

@app.get("/")
def read_root():
    return {"status": "✦ FFX ✦ AI Server is Running!"}

@app.get("/analyze")
def analyze(url: str):
    try:
        # ব্রাউজার সেজে রিকোয়েস্ট পাঠানো যেন টিকটক ব্লক না করে
        headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64 AppleWebKit/537.36)"}
        res = requests.get(url, headers=headers, timeout=15)
        img = Image.open(BytesIO(res.content)).convert("RGB")
        
        # AI Processing
        results = classifier(img)
        top_score = results[0]['score']
        
        if top_score >= 0.85:
            return {"success": True, "confidence": f"High ({int(top_score*100)}%)", "names": [results[0]['label'].title()]}
        else:
            top_3 = [r['label'].title() for r in results[:3]]
            return {"success": True, "confidence": "Low", "names": top_3}
            
    except Exception as e:
        return {"success": False, "error": str(e)}