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import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import openai
import streamlit as st
import pandas as pd
import requests
# 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')
# Set up the Gemini API key (replace with your actual Gemini API key)
GEMINI_API_KEY = 'AIzaSyAGGP8I7c0YmA8xKZsEdAF9AF3ElaPoEn4'
# Set the API endpoint for Gemini
GEMINI_API_URL = "https://gemini.googleapis.com/v1/completions" # Example URL, please check the actual URL
# Streamlit UI
st.set_page_config(page_title="AI-based Solar Project Estimation Tool", layout="centered")
st.title("AI-based Solar Project Estimation Tool")
# Center all input widgets
st.write("### Enter Your Details Below:")
with st.form("solar_form"):
# Get the list of unique states from the dataset
state_options = df['State'].dropna().unique()
# Input widgets
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:
# Fetch state data from the dataset
state_data = df[df['State'].str.contains(location, case=False)].iloc[0] # Get the first match
if state_data is not None:
ghi = state_data['Avg_GHI (kWh/m²/day)']
solar_cost_per_kw = state_data['Solar_Cost_per_kW (₹)']
# Use Gemini API to generate solar project estimate (cost, savings, payback period)
prompt = 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
"""
# Request to Gemini API (Adjust headers and body according to Gemini API documentation)
response = requests.post(
GEMINI_API_URL,
headers={
"Authorization": f"Bearer {GEMINI_API_KEY}",
"Content-Type": "application/json"
},
json={
"model": "gemini-model-xyz", # Use the actual Gemini model name
"prompt": prompt,
"max_tokens": 250,
"temperature": 0.7,
"top_p": 1.0,
"n": 1
}
)
# Check for successful response
if response.status_code == 200:
result = response.json().get("choices", [])[0].get("text", "").strip()
# Display the response from the Gemini model
st.subheader("Estimated Solar System Details:")
st.write(result)
else:
st.error(f"Error: {response.status_code}. Unable to get response from Gemini API.")
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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