Update app.py

app.py

@@ -1,95 +1,79 @@
 import gradio as gr
 import pandas as pd
-import numpy as np
 from fpdf import FPDF
 import datetime
-import os
 
-# --- 2026 MARKET DATA CONFIG ---
-CONFIG = {
-    "panel_pkr_watt": 32,
-    "sun_hours": 5.2,
-    "grid_rate": 55.0,
-    "buyback_rate": 11.0,
-    "li_battery_kwh": 48000,
-    "markup": 0.15,
+# --- 2026 DYNAMIC MARKET DATA ---
+MARKET_DATA = {
+    "panel_pkr_w": 32,
+    "sun_hrs": 5.2,
+    "bank_rate": 0.14,  # Simulated Alfalah Rate
+    "installation": 0.15
 }
 
-# --- MODULE: BANK API INTEGRATION ---
-def fetch_bank_rates():
-    """
-    Simulated API call to Bank Alfalah/JS Bank for 2026 Solar Financing.
-    In production, use: requests.get('https://api.bankalfalah.com/rates')
-    """
-    return {"interest_rate": 0.14, "tenure_months": 60, "bank_name": "Bank Alfalah"}
-
-# --- MODULE: PDF GENERATOR ---
-def generate_report(load, size, cost, emi, roi):
+def generate_pdf(data):
     pdf = FPDF()
     pdf.add_page()
-    pdf.set_font("Arial", 'B', 16)
-    pdf.cell(200, 10, "Solar Solution Report - Pakistan 2026", ln=True, align='C')
+    pdf.set_font("Helvetica", 'B', 16)
+    pdf.cell(0, 10, "Solar Feasibility Report - Pakistan 2026", center=True, new_x="LMARGIN", new_y="NEXT")
     
-    pdf.set_font("Arial", size=12)
+    pdf.set_font("Helvetica", size=12)
     pdf.ln(10)
-    pdf.cell(200, 10, f"Date: {datetime.datetime.now().strftime('%Y-%m-%d')}", ln=True)
-    pdf.cell(200, 10, f"Total Connected Load: {load} Watts", ln=True)
-    pdf.cell(200, 10, f"Recommended System Size: {size} kW", ln=True)
-    pdf.cell(200, 10, f"Estimated Total Investment: PKR {cost:,}", ln=True)
-    pdf.cell(200, 10, f"Monthly EMI Plan: PKR {emi:,}/month", ln=True)
-    pdf.cell(200, 10, f"Estimated Payback Period: {roi} Years", ln=True)
+    for key, value in data.items():
+        pdf.cell(0, 10, f"{key}: {value}", new_x="LMARGIN", new_y="NEXT")
     
-    report_path = "Solar_Report_PK.pdf"
+    report_path = "Solar_Insights_Report.pdf"
     pdf.output(report_path)
     return report_path
 
-# --- CORE LOGIC ---
-def solar_engine(app_selection, counts, sys_type, backup_hrs):
-    # Load math (20% losses included)
-    watts_map = {"AC": 1500, "Fan": 80, "Fridge": 250, "Lights": 12}
-    total_watts = sum([watts_map[k] for k in app_selection])
-    
-    daily_units = (total_watts * 10) / 1000 # Avg 10h usage
-    sys_size = round((daily_units / CONFIG["sun_hours"]) * 1.2, 1)
-    
-    panel_cost = sys_size * 1000 * CONFIG["panel_pkr_watt"]
-    battery_cost = (daily_units * (backup_hrs/24) * CONFIG["li_battery_kwh"])
-    
-    total_cost = int((panel_cost + battery_cost + 200000) * (1 + CONFIG["markup"]))
+def solar_calculator(ac_count, fan_count, light_count, sys_type):
+    # Engineering Math
+    load = (ac_count * 1500) + (fan_count * 80) + (light_count * 12)
+    daily_units = (load * 8) / 1000
+    sys_kw = round((daily_units / MARKET_DATA["sun_hrs"]) * 1.2, 2)
     
     # Financials
-    bank = fetch_bank_rates()
-    p = total_cost * 0.8
-    r = bank["interest_rate"] / 12
-    n = bank["tenure_months"]
-    emi = int(p * (r * (1+r)**n) / ((1+r)**n - 1))
+    cost = int((sys_kw * 1000 * MARKET_DATA["panel_pkr_w"] + 250000) * (1 + MARKET_DATA["installation"]))
     
-    roi = round(total_cost / (daily_units * 365 * 45), 1)
+    # Bank EMI Calculation (P * r * (1+r)^n / ((1+r)^n - 1))
+    p = cost * 0.7  # 30% Downpayment
+    r = MARKET_DATA["bank_rate"] / 12
+    n = 60
+    emi = int(p * (r * (1+r)**n) / ((1+r)**n - 1))
+
+    results = {
+        "Total Load (W)": load,
+        "System Size (kW)": sys_kw,
+        "Total Cost (PKR)": f"{cost:,}",
+        "Monthly EMI (PKR)": f"{emi:,}",
+        "Date Generated": datetime.datetime.now().strftime("%Y-%m-%d")
+    }
     
-    pdf_file = generate_report(total_watts, sys_size, total_cost, emi, roi)
+    pdf_file = generate_pdf(results)
     
-    summary = f"""### 📋 System Insights
-    - **Size:** {sys_size} kW
-    - **Total Cost:** PKR {total_cost:,}
-    - **EMI:** PKR {emi:,}/mo ({bank['bank_name']})
+    summary = f"""
+    ## 📊 Estimation Results
+    - **Recommended System:** {sys_kw} kW {sys_type}
+    - **Estimated Investment:** PKR {cost:,}
+    - **Financing:** PKR {emi:,}/month via Bank Alfalah
     """
     return summary, pdf_file
 
-# --- GRADIO UI ---
-with gr.Blocks(theme=gr.themes.Default()) as demo:
-    gr.Markdown("# ☀️ Solar Consultant Pro (Pakistan)")
-    
+# --- UI DESIGN ---
+with gr.Blocks(title="Solar PK Pro") as demo:
+    gr.Markdown("# ☀️ SolarExpert Pakistan 2.0")
     with gr.Row():
         with gr.Column():
-            apps = gr.CheckboxGroup(["AC", "Fan", "Fridge", "Lights"], label="Appliances")
-            sys = gr.Dropdown(["On-Grid", "Hybrid", "Off-Grid"], label="System Type", value="Hybrid")
-            bkp = gr.Slider(0, 12, value=4, label="Battery Backup (Hours)")
-            btn = gr.Button("Analyze & Generate PDF", variant="primary")
-            
+            ac = gr.Number(label="Inverter ACs (1.5 Ton)", value=1)
+            fans = gr.Number(label="Ceiling Fans", value=4)
+            lights = gr.Number(label="LED Lights", value=10)
+            stype = gr.Dropdown(["On-Grid", "Hybrid"], label="System Architecture", value="Hybrid")
+            calc_btn = gr.Button("Calculate & Generate Report", variant="primary")
+        
         with gr.Column():
             out_md = gr.Markdown()
-            out_pdf = gr.File(label="Download Full Report")
+            out_file = gr.File(label="Download PDF Insights")
 
-    btn.click(solar_engine, inputs=[apps, gr.State(1), sys, bkp], outputs=[out_md, out_pdf])
+    calc_btn.click(solar_calculator, inputs=[ac, fans, lights, stype], outputs=[out_md, out_file])
 
 demo.launch()