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import streamlit as st
import pandas as pd
import google.generativeai as genai
import os
from dotenv import load_dotenv
import plotly.graph_objects as go
# Load environment variables from .env file
load_dotenv()
# Set page configuration
st.set_page_config(page_title="☀️AI-Based Solar Project Estimation Tool", layout="centered")
# Initialize Gemini with the API key
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.")
# Use Gemini-1.5-Pro model
model = genai.GenerativeModel("gemini-1.5-pro")
# 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()
# Build prompt for Gemini
def build_prompt(location, project_type, roof_size=None, desired_kwh=None, electricity_bill=None, ghi=None, solar_cost_per_kw=None):
if project_type == "Rooftop Solar":
prompt = f"""
You are a solar project estimator tool. Based on the following details, calculate and return only the values without any extra description:
Project Type: Rooftop Solar
Location: {location}
Roof size: {roof_size} sq meters
Monthly electricity bill: ₹{electricity_bill}
Average GHI: {ghi} kWh/m²/day
Solar system cost per kW: ₹{solar_cost_per_kw}
Respond strictly in this format (do not add anything extra):
Estimated solar system size in kW: <value>
Estimated daily solar output in kWh: <value>
Total system cost in ₹: <value>
Monthly savings in ₹: <value>
Payback period in years: <value>
"""
else: # Ground Mount Solar
prompt = f"""
You are a solar project estimator tool. Based on the following details, calculate and return only the values without any extra description:
Project Type: Ground Mount Solar
Location: {location}
Desired monthly solar production: {desired_kwh} kWh
Monthly electricity bill: ₹{electricity_bill}
Average GHI: {ghi} kWh/m²/day
Solar system cost per kW: ₹{solar_cost_per_kw}
Respond strictly in this format (do not add anything extra):
Required solar system size in kW: <value>
Estimated daily solar output in kWh: <value>
Total system cost in ₹: <value>
Monthly savings in ₹: <value>
Payback period in years: <value>
"""
return prompt
# UI - Form for user input
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))
project_type = st.radio(
"Select Solar Project Type",
options=["Rooftop Solar", "Ground Mount Solar"]
)
if project_type == "Rooftop Solar":
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)
desired_kwh = None
else:
desired_kwh = st.number_input("Enter desired monthly solar electricity production (kWh)", min_value=1)
electricity_bill = st.number_input("Enter your monthly electricity bill (₹)", min_value=0)
roof_size = None
submitted = st.form_submit_button("Get Estimate")
# Generate the solar project estimate via Gemini
if submitted and location:
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 = build_prompt(location, project_type, roof_size=roof_size, desired_kwh=desired_kwh, electricity_bill=electricity_bill, ghi=ghi, solar_cost_per_kw=solar_cost_per_kw)
# Call Gemini API
with st.spinner("Generating solar estimate with Gemini..."):
response = model.generate_content(prompt_text)
# Display structured output
st.subheader("🔹 Solar Project Estimate")
estimated_data = response.text.strip().split("\n")
system_size_kw = None
monthly_savings_rs = None
total_system_cost = None
payback_period_years = None
daily_output_kwh = None
for point in estimated_data:
if ":" in point:
try:
key, value = point.split(":", 1)
key = key.strip()
value = value.strip()
st.write(f"**{key}**: {value}")
if "Estimated solar system size" in key or "Required solar system size" in key:
system_size_kw = float(value.split()[0])
if "Monthly savings" in key:
monthly_savings_rs = float(value.split()[0])
if "Total system cost" in key:
total_system_cost = float(value.split()[0])
if "Payback period" in key:
payback_period_years = float(value.split()[0])
except ValueError:
st.warning("There was an issue processing the response. Please try again.")
# Calculate Daily Output in kWh
if system_size_kw is not None and ghi is not None:
daily_output_kwh = system_size_kw * ghi # Estimate daily output in kWh
# Show the formulas
st.subheader("🧮 Formulas Used:")
if project_type == "Rooftop Solar":
st.markdown(f"""
**For Rooftop Solar:**
- Estimated Solar System Size (kW) = Roof Size (m²) × 0.15
- Estimated Daily Solar Output (kWh) = System Size (kW) × Average GHI (kWh/m²/day)
- Total System Cost (₹) = System Size (kW) × Solar Cost per kW (₹)
- Monthly Savings (₹) = (Estimated Daily Output × 30 × Tariff Rate per kWh) [Approximate]
- Payback Period (years) = Total System Cost ÷ (Monthly Savings × 12)
""")
else:
st.markdown(f"""
**For Ground Mount Solar:**
- Required Solar System Size (kW) = Desired Monthly Solar Production ÷ (30 × Average GHI)
- Estimated Daily Solar Output (kWh) = System Size (kW) × Average GHI (kWh/m²/day)
- Total System Cost (₹) = System Size (kW) × Solar Cost per kW (₹)
- Monthly Savings (₹) = (Estimated Daily Output × 30 × Tariff Rate per kWh) [Approximate]
- Payback Period (years) = Total System Cost ÷ (Monthly Savings × 12)
""")
st.info("Note: Tariff rate is assumed based on your state electricity average or ₹7/kWh (default).")
# Visual Summary - Grouped Bar Chart
if system_size_kw is not None and total_system_cost is not None:
st.subheader("📊 Visual Summary")
fig = go.Figure(data=[
go.Bar(
name="System Size (kW)",
x=["Solar System Size", "Daily Output", "Total Cost", "Monthly Savings", "Payback Period"],
y=[system_size_kw, daily_output_kwh , total_system_cost, monthly_savings_rs, payback_period_years],
marker_color='#636EFA'
),
go.Bar(
name="Financials",
x=["Solar System Size", "Daily Output", "Total Cost", "Monthly Savings", "Payback Period"],
y=[0, 0, total_system_cost, monthly_savings_rs, payback_period_years],
marker_color='#00CC96'
)
])
fig.update_layout(
barmode='group',
title="Comparison of Solar System Parameters",
yaxis_title="Values",
xaxis_title="Parameters"
)
st.plotly_chart(fig, use_container_width=True)
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.")