app.py

import gradio as gr
import os
from groq import Groq

# Initialize Groq client
client = Groq(api_key=os.environ.get("CHATAPI"))

def calculate_carbon_footprint(energy_consumption, transportation_km, waste_production, water_usage, food_choices):
    try:
        # Calculate carbon footprint
        carbon_footprint = (
            energy_consumption * 0.5 +
            transportation_km * 0.15 +
            waste_production * 0.66 +
            water_usage * 0.027 +
            {"Meat-heavy": 2.0, "Balanced": 1.5, "Vegetarian": 1.0, "Vegan": 0.5}[food_choices]
        )
        
        # Add randomness for realism
        carbon_footprint *= random.uniform(0.9, 1.1)
        
        # Calculate number of trees needed for offset
        trees_needed = round(carbon_footprint * 1000 / 22)
        
        # Create the message for the language model
        message = (
            f"Your estimated carbon footprint is {carbon_footprint:.2f} tons of CO2 per year.\n\n"
            f"To offset this and reach net zero, you would need to plant approximately {trees_needed} trees.\n\n"
            "Note: This is a simplified calculation. Actual values may vary based on more detailed factors."
        )
        
        # Get a response from the language model
        chat_completion = client.chat.completions.create(
            messages=[
                {
                    "role": "user",
                    "content": message,
                }
            ],
            model="llama3-8b-instant"  # Replace with the correct model identifier
        )
        
        result = chat_completion['choices'][0]['message']['content']
        
        return result
    except KeyError as e:
        return f"An invalid food choice was selected: {str(e)}"
    except Exception as e:
        return f"An error occurred: {str(e)}"

iface = gr.Interface(
    fn=calculate_carbon_footprint,
    inputs=[
        gr.Slider(0, 1000, step=1, label="Energy Consumption (kWh/month)"),
        gr.Slider(0, 50000, step=1, label="Transportation (km/year)"),
        gr.Slider(0, 50, step=1, label="Waste Production (kg/week)"),
        gr.Slider(0, 1000, step=1, label="Water Usage (liters/day)"),
        gr.Radio(["Meat-heavy", "Balanced", "Vegetarian", "Vegan"], label="Food Choices")
    ],
    outputs="text",
    title="Carbon Footprint Calculator with Language Model",
    description="Enter your usage details to get a detailed analysis of your carbon footprint and offset requirements."
)

iface.launch()