app.py

import streamlit as st
import pandas as pd
import google.generativeai as genai
import os
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Set page configuration
st.set_page_config(page_title="AI-based Solar Project Estimation Tool", layout="centered")

# Initialize Gemini
api_key = os.getenv("GOOGLE_API_KEY")
if api_key:
    genai.configure(api_key=api_key)
else:
    st.error("API key is missing. Please set the GOOGLE_API_KEY environment variable.")

model = genai.GenerativeModel("gemini-1.5-flash")

# Load solar data
@st.cache_data
def load_data():
    df = pd.read_csv('https://huggingface.co/spaces/MLDeveloper/AI_based_Solar_Project_Estimation_Tool/resolve/main/solar_data_india_2024.csv')
    return df

df = load_data()

# Solar Calculation Function (not relying on Gemini for calculation)
def calculate_solar_estimate(roof_size, monthly_bill, electricity_price, ghi, cost_per_kw):
    daily_consumption_inr = monthly_bill / 30
    daily_consumption_kwh = daily_consumption_inr / electricity_price

    # Assume system size based on consumption
    estimated_system_size_kw = 3  # Fixed for now as realistic estimate
    peak_sun_hours = ghi  # Use GHI as sun hours (approximation)
    
    daily_solar_output_kwh = estimated_system_size_kw * peak_sun_hours * 0.75  # considering derating factor
    
    total_system_cost = estimated_system_size_kw * cost_per_kw
    
    monthly_generation_kwh = daily_solar_output_kwh * 30
    monthly_savings_inr = monthly_generation_kwh * electricity_price
    
    annual_savings_inr = monthly_savings_inr * 12
    payback_period_years = total_system_cost / annual_savings_inr

    return {
        "Estimated solar system size in kW": round(estimated_system_size_kw, 2),
        "Estimated daily solar output in kWh": round(daily_solar_output_kwh, 2),
        "Total system cost in ₹": int(total_system_cost),
        "Monthly savings in ₹": int(monthly_savings_inr),
        "Payback period in years": round(payback_period_years, 2)
    }

# UI - Form
st.title("AI-based Solar Project Estimation Tool")
st.write("### Enter Your Details:")

with st.form("solar_form"):
    state_options = df['State'].dropna().unique()
    
    location = st.selectbox("Select your State", options=sorted(state_options))
    roof_size = st.number_input("Enter your roof size (in sq meters)", min_value=1)
    monthly_bill = st.number_input("Enter your monthly electricity bill (₹)", min_value=0)
    
    submitted = st.form_submit_button("Get Estimate")

if submitted and location and roof_size > 0 and monthly_bill >= 0:
    state_data = df[df['State'].str.contains(location, case=False)].iloc[0]
    
    if state_data is not None:
        ghi = state_data['Avg_GHI (kWh/m²/day)']
        solar_cost_per_kw = state_data['Solar_Cost_per_kW (₹)']
        electricity_price = 8  # Assume ₹8/kWh
        
        # Calculate estimates
        estimates = calculate_solar_estimate(roof_size, monthly_bill, electricity_price, ghi, solar_cost_per_kw)

        # Build clean prompt for Gemini to verify the calculation
        prompt = f"""
        ONLY output these 5 points based on inputs:
        1. Estimated solar system size in kW
        2. Estimated daily solar output in kWh
        3. Total system cost in ₹
        4. Monthly savings in ₹
        5. Payback period in years
        
        Roof size = {roof_size} sq meters
        Monthly bill = ₹{monthly_bill}
        GHI = {ghi} kWh/m²/day
        Solar system cost per kW = ₹{solar_cost_per_kw}
        
        Use no description. Only numeric values clearly.
        """

        # Call Gemini API (just to double-check/validate if you want)
        with st.spinner("Generating final estimate..."):
            gemini_response = model.generate_content(prompt)
            final_response = gemini_response.text.strip()

        # Display calculated values directly (without trusting Gemini text output)
        st.subheader("Solar Project Estimate")

        for key, value in estimates.items():
            st.write(f"{key}: {value}")
    else:
        st.error("Location data not found. Please select a valid state.")
else:
    st.warning("Please fill all the fields.")