app.py

import os
import numpy as np
import pandas as pd
import gradio as gr
import matplotlib.pyplot as plt
from fpdf import FPDF
from groq import Groq

# Set up Groq API
api_key = "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"
client = Groq(api_key=api_key)

# HVAC Load Calculation Logic
def calculate_load(room_size, insulation_type, climate, occupants, outdoor_air, dust_efficiency, design_temp,
                   material, infiltration, internal_loads, lighting_cooling_factor, heat_gain_occupant,
                   space_per_occupant, sensible_heat_factor, solar_heat_gain, shading_coefficients, cooling_load_temp_diff,
                   is_commercial=False):
    try:
        # R-values for selected materials (per inch)
        material_r_values = {
            "Fiberglass Insulation (Batt or Roll)": 3.7,
            "Expanded Polystyrene (EPS)": 4.0,
            "Extruded Polystyrene (XPS)": 5.0,
            "Spray Foam Insulation": 6.0,
            "Wood (Softwood)": 1.41,
            "Concrete (6\" thick)": 1.11,
            "Brick": 0.80,
            "Double Glazed Glass": 2.0,
            "Mineral Wool Insulation": 3.5,
            "Cellulose Insulation": 3.6,
        }

        # Get R-value based on selected material
        thermal_resistance = material_r_values.get(material, 1)

        # Placeholder calculations (replace with ASHRAE-compliant formulas)
        base_load = room_size * 10  # Base load
        insulation_factor = 0.8 if insulation_type == "Good" else 1.2
        climate_factor = 1.5 if climate == "Hot" else 0.8
        occupant_factor = occupants * heat_gain_occupant

        # Ventilation load
        ventilation_load = outdoor_air * dust_efficiency * design_temp

        # Infiltration load
        infiltration_load = room_size * infiltration

        # Internal loads
        internal_load = internal_loads * room_size

        # Lighting load
        lighting_load = room_size * lighting_cooling_factor

        # Solar heat gain
        solar_load = solar_heat_gain * shading_coefficients

        # Wall load
        wall_load = room_size * cooling_load_temp_diff * thermal_resistance

        # Total load in BTU/hr
        total_load_btu = (
            base_load * insulation_factor * climate_factor +
            occupant_factor + ventilation_load + infiltration_load +
            internal_load + lighting_load + solar_load + wall_load
        )

        # Convert to kW
        total_load_kw = total_load_btu * 0.000293071

        # Calculate tonnage
        required_tonnage = total_load_btu / 12000

        # Commercial building load: increase size factor for larger spaces
        if is_commercial:
            total_load_btu *= 1.5  # Scale load for commercial buildings
            required_tonnage = total_load_btu / 12000

        # Maintenance recommendations based on usage
        maintenance_recommendation = ""
        if room_size > 1000:
            maintenance_recommendation = "Regular HVAC maintenance is recommended, check air filters and ducts."

        # Energy savings tips based on input
        energy_savings_tips = "Consider upgrading insulation or using energy-efficient HVAC systems for better performance."

        # Determine recommendation
        recommendation = "AC is required" if climate == "Hot" else "Heater is required"

        return total_load_btu, total_load_kw, required_tonnage, recommendation, maintenance_recommendation, energy_savings_tips, {
            "Base Load": base_load,
            "Ventilation Load": ventilation_load,
            "Infiltration Load": infiltration_load,
            "Internal Load": internal_load,
            "Lighting Load": lighting_load,
            "Solar Load": solar_load,
            "Wall Load": wall_load,
        }
    except Exception as e:
        return f"Error in calculation: {e}", None, None, None, None, None, {}

# Visualization Function
def generate_plot(load_components):
    try:
        plt.figure(figsize=(10, 6))
        plt.bar(load_components.keys(), load_components.values(), color='skyblue')
        plt.xlabel("Load Components")
        plt.ylabel("Load (BTU/hr)")
        plt.title("HVAC Load Breakdown")
        plt.xticks(rotation=45, ha="right")
        plt.tight_layout()
        plot_path = "load_components.png"
        plt.savefig(plot_path)
        plt.close()
        return plot_path
    except Exception as e:
        return f"Error in generating plot: {e}"

# Gradio Interface Function
def app(room_size, insulation_type, climate, occupants, outdoor_air, dust_efficiency, design_temp,
        material, infiltration, internal_loads, lighting_cooling_factor, heat_gain_occupant,
        space_per_occupant, sensible_heat_factor, solar_heat_gain, shading_coefficients, cooling_load_temp_diff, 
        hours_of_usage, cost_per_kwh, is_commercial):
    try:
        total_load_btu, total_load_kw, required_tonnage, recommendation, maintenance_recommendation, energy_savings_tips, load_components = calculate_load(
            room_size, insulation_type, climate, occupants, outdoor_air, dust_efficiency, design_temp,
            material, infiltration, internal_loads, lighting_cooling_factor, heat_gain_occupant,
            space_per_occupant, sensible_heat_factor, solar_heat_gain, shading_coefficients, cooling_load_temp_diff,
            is_commercial
        )
        
        # Calculate energy consumption and cost
        energy_consumed_kwh = total_load_kw * hours_of_usage
        total_cost = energy_consumed_kwh * cost_per_kwh
        
        plot_path = generate_plot(load_components)
        
        # Generate a report PDF
        report_pdf = FPDF()
        report_pdf.add_page()
        report_pdf.set_font("Arial", size=12)
        report_pdf.cell(200, 10, txt="HVAC Load Calculation Report", ln=True, align="C")
        report_pdf.ln(10)
        report_pdf.multi_cell(0, 10, txt=f"Room Size: {room_size} sq ft\n"
                                         f"Insulation Type: {insulation_type}\n"
                                         f"Climate: {climate}\n"
                                         f"Number of Occupants: {occupants}\n"
                                         f"Recommended Tonnage: {required_tonnage:.2f} tons\n"
                                         f"Total HVAC Load: {total_load_btu:.2f} BTU/hr ({total_load_kw:.2f} kW)\n"
                                         f"Energy Consumed: {energy_consumed_kwh:.2f} kWh\n"
                                         f"Total Cost: ${total_cost:.2f}\n"
                                         f"Maintenance Recommendation: {maintenance_recommendation}\n"
                                         f"Energy Savings Tips: {energy_savings_tips}")
        report_pdf.output("hvac_report.pdf")
        
        return (
            f"Total HVAC Load: {total_load_btu:.2f} BTU/hr ({total_load_kw:.2f} kW)\n"
            f"Recommended Tonnage: {required_tonnage:.2f} tons\n"
            f"Recommendation: {recommendation}\n"
            f"Energy Consumed: {energy_consumed_kwh:.2f} kWh\n"
            f"Total Cost: ${total_cost:.2f}\n"
            f"Maintenance Recommendation: {maintenance_recommendation}\n"
            f"Energy Savings Tips: {energy_savings_tips}",
            plot_path,
            "hvac_report.pdf"
        )
    except Exception as e:
        return f"Error: {e}", None, None

# Gradio Interface
interface = gr.Interface(
    fn=app,
    inputs=[
        gr.Number(label="Room Size (sq ft)"),
        gr.Radio(["Good", "Poor"], label="Insulation Type"),
        gr.Radio(["Hot", "Cold"], label="Climate"),
        gr.Number(label="Number of Occupants"),
        gr.Number(label="Outdoor Air (CFM)", value=0),
        gr.Number(label="ASHRAE Dust Spot Efficiency (%)", value=100),
        gr.Number(label="Design Temperature (°C)", value=24),
        gr.Dropdown(
            label="Building Material",
            choices=["Fiberglass Insulation (Batt or Roll)", "Expanded Polystyrene (EPS)", "Extruded Polystyrene (XPS)", 
                     "Spray Foam Insulation", "Wood (Softwood)", "Concrete (6\" thick)", "Brick", "Double Glazed Glass", 
                     "Mineral Wool Insulation", "Cellulose Insulation"]
        ),
        gr.Number(label="Infiltration (CFM)"),
        gr.Number(label="Internal Loads (W/m²)"),
        gr.Number(label="Lighting Cooling Factor (W/m²)"),
        gr.Number(label="Heat Gain per Occupant (W)"),
        gr.Number(label="Space per Occupant (sq ft)"),
        gr.Number(label="Sensible Heat Factor for Occupants"),
        gr.Number(label="Solar Heat Gain (W/m²)"),
        gr.Number(label="Shading Coefficients"),
        gr.Number(label="Cooling Load Temperature Difference (°C)"),
        gr.Number(label="Hours of Usage (hrs/day)", value=5),
        gr.Number(label="Cost per kWh ($)", value=0.12),
        gr.Checkbox(label="Is Commercial Building?", value=False)
    ],
    outputs=[
        gr.Textbox(label="Results"),
        gr.Image(label="Load Breakdown Plot"),
        gr.File(label="Download HVAC Report")
    ]
)

interface.launch()