app.py

from flask import Flask, request, jsonify
import torch
from PIL import Image
from transformers import AutoModelForImageClassification, AutoImageProcessor
import io

app = Flask(__name__)

# 1. Model loading directly from Hugging Face
# Ye model automatic download hoga jab aap 'Factory Rebuild' karenge
model_name = "SanketJadhav/PlantDiseaseClassifier-Resnet50"
print("Loading model... please wait.")
model = AutoModelForImageClassification.from_pretrained(
    "aapka-model-name", 
    use_safetensors=False
)processor = AutoImageProcessor.from_pretrained(model_name)
print("Model loaded successfully!")

@app.route("/", methods=["GET"])
def home():
    return jsonify({"status": "Server is running on port 7860"})

@app.route("/predict", methods=["POST"])
def predict():
    try:
        # Check if file is in request
        if 'file' not in request.files:
            return jsonify({"error": "No file uploaded"}), 400
        
        # Read and process image
        file = request.files['file'].read()
        image = Image.open(io.BytesIO(file)).convert("RGB")
        
        # Model Prediction
        inputs = processor(images=image, return_tensors="pt")
        outputs = model(**inputs)
        logits = outputs.logits
        predicted_class = logits.argmax(-1).item()
        
        # Get Label
        label = model.config.id2label[predicted_class]
        return jsonify({"prediction": label})
        
    except Exception as e:
        return jsonify({"error": str(e)}), 500

if __name__ == "__main__":
    # BOHAT ZAROORI: Hugging Face sirf port 7860 ko accept karta hai
    print("Starting Flask server on port 7860...")
    app.run(host="0.0.0.0", port=7860)