app.py

import streamlit as st
import numpy as np
import pandas as pd
from translate import Translator

# Translator setup
def translate_text(text, lang_code):
    try:
        translator = Translator(to_lang=lang_code)
        return translator.translate(text)
    except Exception:
        return text  # Fallback to original text

# Multi-language setup
languages = {
    "English": "en",
    "Spanish": "es",
    "French": "fr",
    "German": "de",
    "Chinese": "zh"
}

# Appliance list
appliance_list = [
    "1. LED Bulb",
    "2. Fan",
    "3. LED TV",
    "4. Computer",
    "5. Refrigerator",
    "6. Washing Machine",
    "7. Water Pump",
    "8. Iron",
    "9. Microwave Oven",
    "10. Water Dispenser",
    "11. Geyser",
    "12. Heater",
    "13. Dishwasher",
    "14. Inverter AC",
    "15. Others",
]

# Streamlit app configuration
st.set_page_config(page_title="International Solar Designer", layout="centered")

# Sidebar language selection
selected_language = st.sidebar.selectbox("Select Language", options=list(languages.keys()))
lang_code = languages[selected_language]

# App title
st.title(translate_text("Solar System Designer", lang_code))

# Sidebar appliance selection
st.sidebar.subheader(translate_text("Select Appliances", lang_code))
appliance_name = st.sidebar.selectbox("Choose Appliance", appliance_list)

if appliance_name == "15. Others":
    appliance_name = st.sidebar.text_input("Enter Appliance Name", "")

# Appliance data storage
appliance_data = []

# Add appliance button logic
if "appliance_data" not in st.session_state:
    st.session_state["appliance_data"] = appliance_data

# Input fields for appliances
if appliance_name != "15. Others":
    wattage = st.number_input(
        translate_text(f"{appliance_name} - Wattage (W):", lang_code), min_value=0, step=1, key=f"{appliance_name}_wattage"
    )
    hours = st.number_input(
        translate_text(f"{appliance_name} - Daily Usage (hours):", lang_code), min_value=0, step=1, key=f"{appliance_name}_hours"
    )
    quantity = st.number_input(
        translate_text(f"{appliance_name} - Quantity:", lang_code), min_value=0, step=1, key=f"{appliance_name}_quantity"
    )
    
    # When the "Add Appliance" button is clicked
    if st.button(translate_text("Add Appliance", lang_code)):
        if wattage > 0 and hours > 0 and quantity > 0:
            appliance_data = st.session_state["appliance_data"]
            appliance_data.append({
                "Appliance": appliance_name,
                "Wattage (W)": wattage,
                "Daily Usage (hours)": hours,
                "Quantity": quantity
            })
            st.session_state["appliance_data"] = appliance_data  # Store data in session

            st.success(translate_text(f"{appliance_name} added successfully!", lang_code))
        else:
            st.error(translate_text("Please fill in all appliance details before adding.", lang_code))

# Display added appliances in a table format
if st.session_state["appliance_data"]:
    st.subheader(translate_text("Added Appliances", lang_code))
    appliance_df = pd.DataFrame(st.session_state["appliance_data"])
    st.dataframe(appliance_df)

# Calculate recommendations
if st.button(translate_text("Calculate Recommendations", lang_code)):
    if not st.session_state["appliance_data"]:
        st.error(translate_text("Please add at least one appliance.", lang_code))
    else:
        total_load = sum(item["Wattage (W)"] * item["Quantity"] for item in st.session_state["appliance_data"])  # in Watts
        total_energy_consumption = sum(
            item["Wattage (W)"] * item["Daily Usage (hours)"] * item["Quantity"] for item in st.session_state["appliance_data"]
        ) / 1000  # in kWh/day

        # Solar panel calculation
        solar_panel_capacity = 550  # Fixed capacity of a solar panel in Watts
        sunlight_hours = 5  # Average peak sunlight hours
        panels_required = np.ceil(total_energy_consumption / (solar_panel_capacity / 1000 * sunlight_hours))

        # Inverter calculation (20% buffer added)
        inverter_capacity = np.ceil(total_load * 1.2 / 1000)  # in kW

        # Battery requirement
        battery_efficiency = 0.95  # Assuming Lithium-Ion battery
        battery_capacity_kWh = total_energy_consumption / battery_efficiency  # in kWh
        battery_capacity_ah = battery_capacity_kWh * 1000 / 48  # Assuming a 48V system
        batteries_required = np.ceil(battery_capacity_ah / 200)  # Assuming 200 Ah per battery

        # Output
        st.subheader(translate_text("System Recommendations", lang_code))
        st.write(translate_text(f"Total Load: {total_load} Watts", lang_code))
        st.write(translate_text(f"Inverter Required: {inverter_capacity} kW", lang_code))
        st.write(translate_text(f"Solar Panels Required: {int(panels_required)} (550W each)", lang_code))
        st.write(translate_text(f"Batteries Required: {int(batteries_required)} (200 Ah, 48V system)", lang_code))

        # Suggestions
        st.subheader(translate_text("System Design Suggestions", lang_code))
        suggestions = [
            "Ensure panels are installed at the optimal tilt angle.",
            "Consider a hybrid system for grid integration.",
            "Use MPPT charge controllers for efficiency.",
            "Plan for future system expansion.",
            "Choose high-quality and reliable components.",
            "Consult a certified solar installer for best practices."
        ]
        for suggestion in suggestions:
            st.write(translate_text(suggestion, lang_code))

# Footer: Developed by
st.markdown(f"<br><hr><p style='text-align: center;'>Developed by Engr Muhammad Arsalan</p>", unsafe_allow_html=True)