from flask import Flask, request, jsonify
import google.generativeai as genai
import PIL.Image
import io
import os
from dotenv import load_dotenv
app = Flask(__name__)
load_dotenv()

# Configure Gemini API - get key from https://makersuite.google.com/app/apikey
GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')
genai.configure(api_key=GOOGLE_API_KEY)

# Initialize the model - UPDATED MODEL NAME HERE
model = genai.GenerativeModel('gemini-2.5-flash')  

def analyze_food_image(image_content) -> str:
    """
    Analyze image using Gemini API and return food description
    """
    try:
        prompt = """
        Look at this food image and:
        1. Identify the main dish/food item
        2. List visible ingredients or components, including individual words/strings of the main dish
        3. Return ONLY a simple description in this format: [main dish], [ingredients]
        For example: "pizza, pizza, cheese, tomatoes, basil" or "chocolate cake, chocolate, cake, frosting, berries"
        """
        
        # Convert bytes to PIL Image
        image_bytes = image_content.read()
        image = PIL.Image.open(io.BytesIO(image_bytes))
        
        # Generate response
        response = model.generate_content([prompt, image])
        
        # Clean and format the response
        description = response.text.strip().lower()
        description = description.replace('"', '').replace("'", '')

        print(description) # For testing purpose

        return description if description else "food dish"
        
    except Exception as e:
        print(f"Error in analysis: {str(e)}")
        return f"food dish (Error: {str(e)})"

if __name__ == '__main__':
    pass