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.")