## (c) 2024
import streamlit as st
import requests
import json
import os
from openai import OpenAI

# Get the API key from the environment variable
API_KEY = os.getenv('PPX_KEY')

# Function to get dollar estimates for damaged objects
def get_damaged_object_estimates(damage_description):
    # Check if API key is available
    if not API_KEY:
        st.error("API key not found. Make sure it's set in the environment variables.")
        return None

    # Messages to send 
    messages = [
        {
            "role": "system",
            "content": (
                "You are an artificial intelligence assistant to help hurricane-afflicted homeowners file for insurance."
            ),
        },
        {
            "role": "user",
            "content": (
                f"Can you use this general list of damages to my home to prepare an organized, itemized list with dollar estimates that I can submit to my insurance company? \n\n {damage_description}"
            ),
        },
    ]

    # Prepare the request payload
    payload = {
        "model": "llama-3.1-sonar-small-128k-chat",
        "messages": messages,
    }

    # Make a POST request to the Perplexity API
    response = requests.post(
        "https://api.perplexity.ai/chat/completions",
        headers={
            "Authorization": f"Bearer {API_KEY}",
            "Content-Type": "application/json"
        },
        json=payload
    )

    # Check if the request was successful
    if response.status_code != 200:
        st.error(f"Error: {response.status_code} - {response.text}")
        return None

    # Process the response
    return postprocess_message_text(response.json())

def postprocess_message_text(api_response):
    """
    Extracts and formats the message content from the API response JSON.
    
    Args:
        api_response (dict): JSON response from the API.
        
    Returns:
        str: Formatted message content.
    """
    
    # Extract the content from the choices
    message_content = api_response["choices"][0]["message"]["content"]
    
    # Clean the message content (remove unnecessary escape characters)
    formatted_content = message_content.replace("\\n", "\n")

    # Fix dollar sign markdown
    formatted_content = formatted_content.replace("$", "\\$")
    
    return formatted_content

# Streamlit interface
st.title("Disaster Damage Cost Estimator")

# Input textbox for the user to enter the damage description
damage_description = st.text_area("Enter the damage description:")

# Button to trigger the API call
if st.button("Get Estimated Costs"):
    if damage_description:
        with st.spinner("Fetching cost estimates..."):
            # Call the function to get estimates
            estimated_costs = postprocess_message_text(get_damaged_object_estimates(damage_description))
            
            if estimated_costs:
                st.success("Here are the estimated costs:")
                st.write(estimated_costs)
            else:
                st.error("Failed to retrieve estimates.")
    else:
        st.error("Please enter a damage description before making a request.")