app.py

import gradio as gr
import openai
import os
from PIL import Image

# Set up the OpenAI API key and prompt from environment variables (secrets)
openai.api_key = os.getenv('OPENAI_API_KEY').strip()
nutrition_prompt = os.getenv('NUTRITION_PROMPT').strip()

# Function to call GPT-4o-mini to get nutritional information from text description
def get_nutritional_info(description):
    prompt = f"{nutrition_prompt}: {description}"
    
    try:
        response = openai.ChatCompletion.create(
            model="gpt-4o-mini",  # Ensure this is the correct model identifier
            messages=[
                {"role": "system", "content": "You are a nutrition expert."},
                {"role": "user", "content": prompt}
            ],
            max_tokens=300,
            temperature=0.7
        )
        return response.choices[0].message['content'].strip()
    except Exception as e:
        return f"Oops! Something went wrong with nutritional breakdown: {str(e)}"

# Gradio interface function
def analyze_meal(image, description):
    if image is not None:
        # Handling if image is given but no text description is provided
        if not description:
            return "Please describe your meal in the text box below the image upload."
        try:
            # Process the image if necessary or use the description
            result = get_nutritional_info(description)
            return result
        except Exception as e:
            return f"Error processing image or description: {str(e)}"
    elif description:
        # Use the description to get nutritional information
        try:
            result = get_nutritional_info(description)
            return result
        except Exception as e:
            return f"Error processing description: {str(e)}"
    else:
        return "Please upload an image and provide a description of the meal."

# Gradio app layout
inputs = [
    gr.Image(label="Upload your meal (Take a bite out of that picture!)", type="pil"),
    gr.Textbox(label="Describe your meal if image recognition fails", lines=2, placeholder="e.g., a plate of upma with coconut chutney")
]

outputs = gr.Textbox(label="Nutritional Breakdown (Let's see what’s on your plate!)")

# Launch the Gradio app with a fun and playful description
app = gr.Interface(
    fn=analyze_meal, 
    inputs=inputs, 
    outputs=outputs, 
    title="NOMP NOMP: Nutrition on My Plate", 
    description="👋 Welcome to NOMP NOMP! Nomp nomp... what's on your plate? Upload a picture or tell us about your meal, and we'll break it down nutritionally for you!"
)

if __name__ == "__main__":
    app.launch()