Update app.py

app.py

@@ -1,19 +1,14 @@
-"""
-HeatBee: Interactive Surrogate Explorer & Bioclimatic Dashboard
-"""
-
 import json
 from pathlib import Path
-import streamlit as st
 import numpy as np
+import pandas as pd
 import xgboost as xgb
-
-st.set_page_config(page_title="HeatBee - Vernacular Thermal Surrogate", page_icon="🏛️", layout="wide")
+import gradio as gr
+import spaces
 
 MODEL_PATH = Path("surrogate_peak_temp.json")
 BENCHMARK_JSON = Path("benchmark_results.json")
 
-@st.cache_resource
 def load_surrogate():
     if not MODEL_PATH.exists():
         return None
@@ -23,88 +18,101 @@ def load_surrogate():
 
 model = load_surrogate()
 
-st.title("🏛️ HeatBee: Vernacular Thermal Physics & AI Surrogate")
-st.markdown("""
-**Surrogate Modeling of Moroccan Rammed Earth (*Pisé*) Architecture**  
-*EnergyPlus 26.2 1D Conduction Finite Difference | Marrakesh Menara EPW (Hottest Outdoor Hour: 45.52°C)*
-""")
-
-if model is None:
-    st.error("Surrogate model not found. Please run `python cli.py --train` first.")
-    st.stop()
-
-col_ctrl, col_metrics = st.columns([1, 1], gap="large")
-
-with col_ctrl:
-    st.subheader("🛠️ Design Envelope Controls")
-    wall_t = st.slider("Pisé Wall Thickness [m]", 0.25, 0.60, 0.50, 0.05, 
-                       help="Analytical diurnal penetration depth is ~11 cm. Beyond 45 cm, mass yields diminishing returns.")
-    roof_alb = st.slider("Roof Solar Reflectance (Albedo)", 0.20, 0.85, 0.60, 0.05,
-                         help="Solar reflectance of horizontal roof finish. Dominant thermal parameter.")
-    shading = st.slider("Mashrabiya Glazing SHGC", 0.10, 0.80, 0.40, 0.05,
-                        help="Solar Heat Gain Coefficient. Lower value represents denser shading.")
-    wwr = st.slider("Courtyard Window-to-Wall Ratio", 0.20, 0.50, 0.25, 0.05)
-    vent_ach = st.slider("Ventilation Rate [ACH]", 1.0, 12.0, 4.0, 0.5,
-                         help="Free cooling ventilation rate when outdoor air is cooler than indoors.")
-
-with col_metrics:
-    st.subheader("⚡ Real-Time Physics Inference (< 1 ms)")
-    
+@spaces.GPU
+def predict_thermal_performance(wall_t, roof_alb, shading, wwr, vent_ach):
+    if model is None:
+        return "Model missing", "Model missing"
+    # Order: [wall_t, vent_ach, roof_alb, shading, wwr]
     x_in = np.array([[wall_t, vent_ach, roof_alb, shading, wwr]])
     pred_peak = float(model.predict(x_in)[0])
     peak_suppression = 45.52 - pred_peak
+    return f"{pred_peak:.2f} °C", f"{peak_suppression:.2f} °C"
+
+def get_benchmark_table(mode_choice):
+    if not BENCHMARK_JSON.exists():
+        return pd.DataFrame([{"Message": "Run `python cli.py --benchmark` to generate ablation results."}])
     
-    m1, m2 = st.columns(2)
-    m1.metric("Predicted Peak Operative Temp", f"{pred_peak:.2f} °C")
-    m2.metric("Peak Suppression vs Ambient", f"{peak_suppression:.2f} °C", 
-              help="Difference between peak outdoor ambient (45.52°C) and indoor peak operative temperature.")
-    
-    st.divider()
-    st.subheader("🔬 Benchmark Comparison")
-    
-    if BENCHMARK_JSON.exists():
-        with open(BENCHMARK_JSON) as f:
-            bench_data = json.load(f)
-            
-        mode_choice = st.radio("Benchmark Mode:", ["Mode A: As-Built Typologies (Archetype Partitions)", "Mode B: Shared Interior Mass (15cm Concrete Slab for All)"], horizontal=True)
-        mode_key = "as_built" if "Mode A" in mode_choice else "shared_interior"
-        
-        table_rows = []
-        # Ambient row
+    with open(BENCHMARK_JSON) as f:
+        bench_data = json.load(f)
+
+    mode_key = "as_built" if "Mode A" in mode_choice else "shared_interior"
+    table_rows = []
+
+    # Ambient row
+    table_rows.append({
+        "Archetype": bench_data["ambient"]["label"],
+        "Peak Temp [°C]": f"{bench_data['ambient']['peak']:.2f} °C",
+        "Mean Temp [°C]": f"{bench_data['ambient']['mean']:.2f} °C",
+        "DDH (>30°C)": f"{bench_data['ambient']['ddh_30']:.1f}",
+        "Daily Decrement (f)": f"{bench_data['ambient']['decrement_f']:.2f}"
+    })
+
+    for k, v in bench_data[mode_key].items():
         table_rows.append({
-            "Archetype": bench_data["ambient"]["label"],
-            "Peak Temp [°C]": f"{bench_data['ambient']['peak']:.2f} °C",
-            "Mean Temp [°C]": f"{bench_data['ambient']['mean']:.2f} °C",
-            "DDH (>30°C)": f"{bench_data['ambient']['ddh_30']:.1f}",
-            "Daily Decrement (f)": f"{bench_data['ambient']['decrement_f']:.2f}"
+            "Archetype": v["label"],
+            "Peak Temp [°C]": f"{v['peak']:.2f} °C",
+            "Mean Temp [°C]": f"{v['mean']:.2f} °C",
+            "DDH (>30°C)": f"{v['ddh_30']:.1f}",
+            "Daily Decrement (f)": f"{v['decrement_f']:.2f}"
         })
-        for k, v in bench_data[mode_key].items():
-            table_rows.append({
-                "Archetype": v["label"],
-                "Peak Temp [°C]": f"{v['peak']:.2f} °C",
-                "Mean Temp [°C]": f"{v['mean']:.2f} °C",
-                "DDH (>30°C)": f"{v['ddh_30']:.1f}",
-                "Daily Decrement (f)": f"{v['decrement_f']:.2f}"
-            })
+
+    return pd.DataFrame(table_rows)
+
+def get_image_path(filename):
+    path = Path(filename)
+    return str(path) if path.exists() else None
+
+with gr.Blocks(title="HeatBee - Vernacular Thermal Surrogate") as demo:
+    gr.Markdown("# 🏛️ HeatBee: Vernacular Thermal Physics & AI Surrogate")
+    gr.Markdown("**Surrogate Modeling of Moroccan Rammed Earth (*Pisé*) Architecture**\n*EnergyPlus 26.2 1D Conduction Finite Difference | Marrakesh Menara EPW (Hottest Outdoor Hour: 45.52°C)*")
+    
+    if model is None:
+        gr.Warning("Surrogate model not found. Please run `python cli.py --train` first.")
+
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("### 🛠️ Design Envelope Controls")
+            wall_t = gr.Slider(0.25, 0.60, value=0.50, step=0.05, label="Pisé Wall Thickness [m]", info="Analytical diurnal penetration depth is ~11 cm. Beyond 45 cm, mass yields diminishing returns.")
+            roof_alb = gr.Slider(0.20, 0.85, value=0.60, step=0.05, label="Roof Solar Reflectance (Albedo)", info="Solar reflectance of horizontal roof finish. Dominant thermal parameter.")
+            shading = gr.Slider(0.10, 0.80, value=0.40, step=0.05, label="Mashrabiya Glazing SHGC", info="Solar Heat Gain Coefficient. Lower value represents denser shading.")
+            wwr = gr.Slider(0.20, 0.50, value=0.25, step=0.05, label="Courtyard Window-to-Wall Ratio")
+            vent_ach = gr.Slider(1.0, 12.0, value=4.0, step=0.5, label="Ventilation Rate [ACH]", info="Free cooling ventilation rate when outdoor air is cooler than indoors.")
+
+        with gr.Column():
+            gr.Markdown("### ⚡ Real-Time Physics Inference (< 1 ms)")
+            pred_out = gr.Textbox(label="Predicted Peak Operative Temp")
+            supp_out = gr.Textbox(label="Peak Suppression vs Ambient", info="Difference between peak outdoor ambient (45.52°C) and indoor peak operative temperature.")
             
-        st.dataframe(table_rows, width="stretch")
-        st.caption("Shared boundary conditions: Roof albedo 0.60, external wall solar absorptance 0.50, glazing SHGC 0.40, 4.0 ACH free cooling, adiabatic floor and party walls.")
-    else:
-        st.info("Run `python cli.py --benchmark` to generate ablation results.")
-
-st.divider()
-st.subheader("📊 Visualizations")
-tab1, tab2, tab3 = st.tabs(["1-to-1 Heatwave Ablation Profile", "Direct Physical Sweeps", "Surrogate Parity"])
-
-with tab1:
-    fig_ab = "rigorous_ablation_heatwave_profile.png"
-    if Path(fig_ab).exists():
-        st.image(str(fig_ab))
-with tab2:
-    fig_sw = "direct_physics_sweeps.png"
-    if Path(fig_sw).exists():
-        st.image(str(fig_sw))
-with tab3:
-    fig_par = "surrogate_parity_plot.png"
-    if Path(fig_par).exists():
-        st.image(str(fig_par))
+            gr.Markdown("---")
+            gr.Markdown("### 🔬 Benchmark Comparison")
+            mode_choice = gr.Radio(
+                choices=["Mode A: As-Built Typologies (Archetype Partitions)", "Mode B: Shared Interior Mass (15cm Concrete Slab for All)"],
+                value="Mode A: As-Built Typologies (Archetype Partitions)",
+                label="Benchmark Mode:"
+            )
+            bench_table = gr.Dataframe(interactive=False)
+            gr.Markdown("*Shared boundary conditions: Roof albedo 0.60, external wall solar absorptance 0.50, glazing SHGC 0.40, 4.0 ACH free cooling, adiabatic floor and party walls.*")
+
+    gr.Markdown("---")
+    gr.Markdown("### 📊 Visualizations")
+    with gr.Tabs():
+        with gr.Tab("1-to-1 Heatwave Ablation Profile"):
+            gr.Image(value=get_image_path("rigorous_ablation_heatwave_profile.png"), show_label=False)
+        with gr.Tab("Direct Physical Sweeps"):
+            gr.Image(value=get_image_path("direct_physics_sweeps.png"), show_label=False)
+        with gr.Tab("Surrogate Parity"):
+            gr.Image(value=get_image_path("surrogate_parity_plot.png"), show_label=False)
+
+    # Reactive Bindings
+    inputs = [wall_t, roof_alb, shading, wwr, vent_ach]
+    outputs = [pred_out, supp_out]
+
+    for component in inputs:
+        component.change(fn=predict_thermal_performance, inputs=inputs, outputs=outputs)
+    
+    demo.load(fn=predict_thermal_performance, inputs=inputs, outputs=outputs)
+    mode_choice.change(fn=get_benchmark_table, inputs=[mode_choice], outputs=[bench_table])
+    demo.load(fn=get_benchmark_table, inputs=[mode_choice], outputs=[bench_table])
+
+if __name__ == "__main__":
+    demo.launch()