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import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os
import requests
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
# Get the Gemini API key from the environment
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
# Gemini API URL
GEMINI_API_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent"
# Load the solar data CSV file
df = pd.read_csv('https://huggingface.co/spaces/MLDeveloper/AI_based_Solar_Project_Estimation_Tool/resolve/main/solar_data_india_2024.csv')
# Streamlit UI
st.set_page_config(page_title="AI-based Solar Project Estimation Tool", layout="centered")
st.title("AI-based Solar Project Estimation Tool")
st.write("### Enter Your Details Below:")
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)
electricity_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 electricity_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 (₹)']
prompt_text = f"""
Estimate the solar system for the location '{location}' based on the following details:
- Roof size: {roof_size} sq meters
- Monthly electricity bill: ₹{electricity_bill}
- Average GHI (solar radiation) for {location}: {ghi} kWh/m²/day
- Solar system cost per kW in {location}: ₹{solar_cost_per_kw}
Provide:
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
"""
# Define the headers for the API request
headers = {
"Authorization": f"Bearer {GEMINI_API_KEY}",
"Content-Type": "application/json"
}
# Define the request payload
payload = {
"model": "gemini-1.5-flash",
"messages": [{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt_text}],
"temperature": 0.7
}
# Make the API request
response = requests.post(GEMINI_API_URL, json=payload, headers=headers)
# Check the response from the API
if response.status_code == 200:
result = response.json()
generated_content = result['choices'][0]['message']['content']
# Display the generated content (solar estimates)
st.subheader("Solar Project Estimate")
st.write(generated_content)
else:
st.error(f"Error: {response.status_code} - {response.text}")
else:
st.error("Sorry, the location entered does not match any available data.")
else:
st.warning("Please fill out all fields to see your solar project estimate.")
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