Create app.py

app.py

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+import gradio as gr
+
+# -------------------------------
+# Appliance Data (Pakistan)
+# -------------------------------
+APPLIANCES = [
+    ("LED Light", 15),
+    ("Ceiling Fan", 80),
+    ("Refrigerator", 200),
+    ("LED TV", 120),
+    ("Washing Machine", 500),
+    ("Iron", 1000),
+    ("Water Pump (1 HP)", 750),
+    ("Air Conditioner (1 Ton)", 1500),
+    ("Laptop", 100),
+    ("Desktop Computer", 300),
+]
+
+PEAK_SUN_HOURS = 5
+
+# -------------------------------
+# Calculation Logic
+# -------------------------------
+def calculate_solar(
+    selected_appliances,
+    city,
+    system_type,
+    battery_type,
+    backup_hours,
+    *values
+):
+    quantities = values[:len(APPLIANCES)]
+    hours = values[len(APPLIANCES):]
+
+    total_daily_wh = 0
+
+    for i, (name, watt) in enumerate(APPLIANCES):
+        if name in selected_appliances:
+            total_daily_wh += watt * quantities[i] * hours[i]
+
+    if total_daily_wh == 0:
+        return "❌ Please select at least one appliance."
+
+    daily_units = total_daily_wh / 1000
+    system_kw = round(daily_units / PEAK_SUN_HOURS, 2)
+
+    panel_watt = 550
+    panels_required = int((system_kw * 1000) / panel_watt) + 1
+    inverter_kw = round(system_kw + 1, 1)
+
+    battery_kwh = 0
+    if system_type != "On-Grid":
+        battery_kwh = round((daily_units / 24) * backup_hours, 2)
+
+    panel_cost = system_kw * 1000 * 45
+    inverter_cost = inverter_kw * 120000
+    battery_cost = battery_kwh * (120000 if battery_type == "Lithium" else 35000)
+
+    total_cost = int((panel_cost + inverter_cost + battery_cost) * 1.1)
+
+    monthly_units = daily_units * 30
+    monthly_saving = int(monthly_units * 60)
+
+    return f"""
+🌞 Solar System Recommendation (Pakistan)
+
+📍 City: {city}
+⚡ System Type: {system_type}
+
+🔌 Daily Load
+• {daily_units:.2f} Units
+
+🔋 System Design
+• Solar Size: {system_kw} kW
+• Panels: {panels_required} × {panel_watt}W
+• Inverter: {inverter_kw} kW
+• Battery: {battery_kwh} kWh ({battery_type})
+
+💰 Estimated Cost
+• PKR {total_cost:,}
+
+📉 Savings
+• Monthly Units: {monthly_units:.1f}
+• Monthly Saving: PKR {monthly_saving:,}
+
+⚠️ Estimated values for Pakistan market.
+"""
+
+# -------------------------------
+# UI
+# -------------------------------
+with gr.Blocks() as app:
+    gr.Markdown("## ☀️ Solar Panel Calculator (Pakistan)")
+
+    appliance_names = [a[0] for a in APPLIANCES]
+
+    selected_appliances = gr.CheckboxGroup(
+        appliance_names, label="Select Appliances"
+    )
+
+    qty_inputs = []
+    hour_inputs = []
+
+    for name, _ in APPLIANCES:
+        with gr.Row():
+            qty_inputs.append(gr.Number(label=f"{name} Quantity", value=1))
+            hour_inputs.append(gr.Number(label=f"{name} Usage Hours", value=5))
+
+    city = gr.Dropdown(
+        ["Lahore", "Karachi", "Islamabad", "Faisalabad", "Multan", "Other"],
+        label="City",
+    )
+
+    system_type = gr.Radio(
+        ["On-Grid", "Off-Grid", "Hybrid"], value="Hybrid", label="System Type"
+    )
+
+    battery_type = gr.Radio(
+        ["Lead Acid", "Lithium"], value="Lead Acid", label="Battery Type"
+    )
+
+    backup_hours = gr.Slider(2, 12, value=6, step=1, label="Backup Hours")
+
+    btn = gr.Button("🔍 Calculate")
+
+    output = gr.Textbox(lines=18, label="Result")
+
+    btn.click(
+        calculate_solar,
+        inputs=[
+            selected_appliances,
+            city,
+            system_type,
+            battery_type,
+            backup_hours,
+            *qty_inputs,
+            *hour_inputs,
+        ],
+        outputs=output,
+    )
+
+app.launch()