model.py

from transformers import pipeline
from PIL import Image
import io
from utils import explain_prediction, get_treatment_and_fertilizer, check_alert

classifier = pipeline("image-classification", model="huggingface/your-model")

def diagnose_disease(image_bytes):
    image = Image.open(io.BytesIO(image_bytes))
    prediction = classifier(image)[0]
    
    label = prediction['label']
    score = prediction['score']
    explanation = explain_prediction(label)
    treatment, fertilizer = get_treatment_and_fertilizer(label)
    alert = check_alert(label)

    return {
        "prediction": label,
        "confidence": score,
        "explanation": explanation,
        "treatment": treatment,
        "fertilizer": fertilizer,
        "alert": alert
    }