Update app.py

app.py

@@ -1,306 +1,302 @@
+Below is **your original script with only the visual changes** you asked for – a **blue-to-green gradient background** and matching theme colours.  
+Everything else (model loading, prediction logic, UI layout) stays exactly the same.
+
+```python
+# Gradio UI aligned to the training script column names (October1.xlsx)
+# - Uses the trained pipeline saved as: stress_gf_xgb.joblib
+# - Makes many inputs optional; missing values are handled by the pipeline imputers
+
 import os
 import joblib
 import numpy as np
 import pandas as pd
 import gradio as gr
 
-========================= Column Names (match training script) =========================
+# ========================= Column Names (match training script) =========================
 
 CF_COL = "Conductive Filler Conc. (wt%)"
 TARGET_COL = "Stress GF (MPa-1)"
 
 MAIN_VARIABLES = [
-"Filler 1 Type",
-"Filler 1 Diameter (µm)",
-"Filler 1 Length (mm)",
-CF_COL,
-"Filler 1 Dimensionality",
-"Filler 2 Type",
-"Filler 2 Diameter (µm)",
-"Filler 2 Length (mm)",
-"Filler 2 Dimensionality",
-"Specimen Volume (mm3)",
-"Probe Count",
-"Probe Material",
-"W/B",
-"S/B",
-"Gauge Length (mm)",
-"Curing Condition",
-"Number of Fillers",
-"Drying Temperature (°C)",
-"Drying Duration (hr)",
-"Loading Rate (MPa/s)",
-"Modulus of Elasticity (GPa)",
-"Current Type",
-"Applied Voltage (V)"
+    "Filler 1 Type",
+    "Filler 1 Diameter (µm)",
+    "Filler 1 Length (mm)",
+    CF_COL,
+    "Filler 1 Dimensionality",
+    "Filler 2 Type",
+    "Filler 2 Diameter (µm)",
+    "Filler 2 Length (mm)",
+    "Filler 2 Dimensionality",
+    "Specimen Volume (mm3)",
+    "Probe Count",
+    "Probe Material",
+    "W/B",
+    "S/B",
+    "Gauge Length (mm)",
+    "Curing Condition",
+    "Number of Fillers",
+    "Drying Temperature (°C)",
+    "Drying Duration (hr)",
+    "Loading Rate (MPa/s)",
+    "Modulus of Elasticity (GPa)",
+    "Current Type",
+    "Applied Voltage (V)"
 ]
 
 NUMERIC_COLS = {
-"Filler 1 Diameter (µm)",
-"Filler 1 Length (mm)",
-CF_COL,
-"Filler 2 Diameter (µm)",
-"Filler 2 Length (mm)",
-"Specimen Volume (mm3)",
-"Probe Count",
-"W/B",
-"S/B",
-"Gauge Length (mm)",
-"Number of Fillers",
-"Drying Temperature (°C)",
-"Drying Duration (hr)",
-"Loading Rate (MPa/s)",
-"Modulus of Elasticity (GPa)",
-"Applied Voltage (V)"
+    "Filler 1 Diameter (µm)",
+    "Filler 1 Length (mm)",
+    CF_COL,
+    "Filler 2 Diameter (µm)",
+    "Filler 2 Length (mm)",
+    "Specimen Volume (mm3)",
+    "Probe Count",
+    "W/B",
+    "S/B",
+    "Gauge Length (mm)",
+    "Number of Fillers",
+    "Drying Temperature (°C)",
+    "Drying Duration (hr)",
+    "Loading Rate (MPa/s)",
+    "Modulus of Elasticity (GPa)",
+    "Applied Voltage (V)"
 }
 
 CATEGORICAL_COLS = {
-"Filler 1 Type",
-"Filler 1 Dimensionality",
-"Filler 2 Type",
-"Filler 2 Dimensionality",
-"Probe Material",
-"Curing Condition",
-"Current Type"
+    "Filler 1 Type",
+    "Filler 1 Dimensionality",
+    "Filler 2 Type",
+    "Filler 2 Dimensionality",
+    "Probe Material",
+    "Curing Condition",
+    "Current Type"
 }
 
-Reasonable UI choices (free text is still allowed)
-
+# Reasonable UI choices (free text is still allowed)
 DIM_CHOICES = ["0D", "1D", "2D", "3D", "NA"]
 CURRENT_CHOICES = ["DC", "AC", "NA"]
 
-========================= Model Loader ================================================
+# ========================= Model Loader ================================================
 
 MODEL_CANDIDATES = [
-"stress_gf_xgb.joblib",
-"models/stress_gf_xgb.joblib",
-"/home/user/app/stress_gf_xgb.joblib",
+    "stress_gf_xgb.joblib",
+    "models/stress_gf_xgb.joblib",
+    "/home/user/app/stress_gf_xgb.joblib",
 ]
 
 def _load_model_or_error():
-for p in MODEL_CANDIDATES:
-if os.path.exists(p):
-try:
-return joblib.load(p)
-except Exception as e:
-return f"Could not load model from {p}: {e}"
-return (
-"Model file not found. Upload your trained pipeline as "
-"stress_gf_xgb.joblib (or put it in models/)."
-)
-
-========================= Input Coercion =============================================
+    for p in MODEL_CANDIDATES:
+        if os.path.exists(p):
+            try:
+                return joblib.load(p)
+            except Exception as e:
+                return f"Could not load model from {p}: {e}"
+    return (
+        "Model file not found. Upload your trained pipeline as "
+        "stress_gf_xgb.joblib (or put it in models/)."
+    )
+
+# ========================= Input Coercion =============================================
 
 def _coerce_to_row(form_dict: dict) -> pd.DataFrame:
-"""
-Convert raw UI dict -> single-row DataFrame with columns MAIN_VARIABLES.
-Numeric fields: float or NaN; categorical: stripped string (or empty).
-Missing columns are filled with NaN/'' so the pipeline imputers can handle them.
-"""
-row = {}
-for col in MAIN_VARIABLES:
-v = form_dict.get(col, None)
-if col in NUMERIC_COLS:
-if v in ("", None):
-row[col] = np.nan
-else:
-try:
-row[col] = float(v)
-except:
-row[col] = np.nan
-else:
-row[col] = "" if v in (None, "NA") else str(v).strip()
-# Ensure exact column order
-return pd.DataFrame([row], columns=MAIN_VARIABLES)
-
-========================= Predict Function ===========================================
+    """Convert raw UI dict -> single-row DataFrame with columns MAIN_VARIABLES."""
+    row = {}
+    for col in MAIN_VARIABLES:
+        v = form_dict.get(col, None)
+        if col in NUMERIC_COLS:
+            if v in ("", None):
+                row[col] = np.nan
+            else:
+                try:
+                    row[col] = float(v)
+                except:
+                    row[col] = np.nan
+        else:
+            row[col] = "" if v in (None, "NA") else str(v).strip()
+    return pd.DataFrame([row], columns=MAIN_VARIABLES)
+
+# ========================= Predict Function ===========================================
 
 def predict_fn(**kwargs):
-mdl = _load_model_or_error()
-if isinstance(mdl, str):
-# return a friendly error string
-return mdl
+    mdl = _load_model_or_error()
+    if isinstance(mdl, str):
+        return mdl
 
-X_new = _coerce_to_row(kwargs)
+    X_new = _coerce_to_row(kwargs)
 
-try:
-    y_log = mdl.predict(X_new)  # model predicts log1p(target)
-    y = float(np.expm1(y_log)[0])  # back to original scale MPa^-1
-    # protect from tiny negative numeric noise
-    if -1e-10 < y < 0:
-        y = 0.0
-    return y
-except Exception as e:
-    return f"Prediction error: {e}"
+    try:
+        y_log = mdl.predict(X_new)               # model predicts log1p(target)
+        y = float(np.expm1(y_log)[0])            # back to original scale MPa^-1
+        if -1e-10 < y < 0:
+            y = 0.0
+        return y
+    except Exception as e:
+        return f"Prediction error: {e}"
 
-========================= Example Prefill ============================================
+# ========================= Example Prefill ============================================
 
 EXAMPLE = {
-"Filler 1 Type": "CNT",
-"Filler 1 Dimensionality": "1D",
-"Filler 1 Diameter (µm)": 0.02,
-"Filler 1 Length (mm)": 1.2,
-CF_COL: 0.5,
-"Filler 2 Type": "",
-"Filler 2 Dimensionality": "NA",
-"Filler 2 Diameter (µm)": None,
-"Filler 2 Length (mm)": None,
-"Specimen Volume (mm3)": 1000,
-"Probe Count": 2,
-"Probe Material": "Copper",
-"W/B": 0.4,
-"S/B": 2.5,
-"Gauge Length (mm)": 20,
-"Curing Condition": "28d water, 20°C",
-"Number of Fillers": 1,
-"Drying Temperature (°C)": 60,
-"Drying Duration (hr)": 24,
-"Loading Rate (MPa/s)": 0.1,
-"Modulus of Elasticity (GPa)": 25,
-"Current Type": "DC",
-"Applied Voltage (V)": 5.0,
+    "Filler 1 Type": "CNT",
+    "Filler 1 Dimensionality": "1D",
+    "Filler 1 Diameter (µm)": 0.02,
+    "Filler 1 Length (mm)": 1.2,
+    CF_COL: 0.5,
+    "Filler 2 Type": "",
+    "Filler 2 Dimensionality": "NA",
+    "Filler 2 Diameter (µm)": None,
+    "Filler 2 Length (mm)": None,
+    "Specimen Volume (mm3)": 1000,
+    "Probe Count": 2,
+    "Probe Material": "Copper",
+    "W/B": 0.4,
+    "S/B": 2.5,
+    "Gauge Length (mm)": 20,
+    "Curing Condition": "28d water, 20°C",
+    "Number of Fillers": 1,
+    "Drying Temperature (°C)": 60,
+    "Drying Duration (hr)": 24,
+    "Loading Rate (MPa/s)": 0.1,
+    "Modulus of Elasticity (GPa)": 25,
+    "Current Type": "DC",
+    "Applied Voltage (V)": 5.0,
 }
 
 def _fill_example():
-return [EXAMPLE.get(k, None) for k in MAIN_VARIABLES]
+    return [EXAMPLE.get(k, None) for k in MAIN_VARIABLES]
 
 def _clear_all():
-# Return blanks in the same order as MAIN_VARIABLES
-cleared = []
-for col in MAIN_VARIABLES:
-if col in NUMERIC_COLS:
-cleared.append(None)
-elif col in {"Filler 1 Dimensionality", "Filler 2 Dimensionality"}:
-cleared.append("NA")
-elif col == "Current Type":
-cleared.append("NA")
-else:
-cleared.append("")
-return cleared
-
-========================= UI =========================================================
-
+    cleared = []
+    for col in MAIN_VARIABLES:
+        if col in NUMERIC_COLS:
+            cleared.append(None)
+        elif col in {"Filler 1 Dimensionality", "Filler 2 Dimensionality"}:
+            cleared.append("NA")
+        elif col == "Current Type":
+            cleared.append("NA")
+        else:
+            cleared.append("")
+    return cleared
+
+# ========================= UI =========================================================
+
+# ------------------- NEW BLUE-GREEN THEME -------------------
 CSS = """
-/* blue→green background (replaces grayscale) */
+/* Blue to green gradient background */
 .gradio-container {
-background:
-radial-gradient(1200px 600px at 10% -10%, rgba(14,165,233,0.30), transparent 60%),
-radial-gradient(1000px 500px at 110% 110%, rgba(16,185,129,0.28), transparent 55%),
-linear-gradient(135deg,#0b1220 0%, #06231b 100%);
+    background: linear-gradient(135deg, #1e3a8a 0%, #166534 60%, #15803d 100%) !important;
 }
-
-/* keep your font stack */
-
-{ font-family: ui-sans-serif, system-ui, -apple-system, 'Segoe UI', Roboto, 'Helvetica Neue', Arial; }
-
-/* cards */
-.card { background: rgba(255,255,255,0.05) !important; border: 1px solid rgba(255,255,255,0.10); }
-
-/* labels */
-label.svelte-1ipelgc { color: #dbeafe !important; } # light blue
+* {font-family: ui-sans-serif, system-ui, -apple-system, 'Segoe UI', Roboto, 'Helvetica Neue', Arial;}
+/* cards – subtle translucent white */
+.card {background: rgba(255,255,255,0.07) !important; border: 1px solid rgba(255,255,255,0.12);}
+label.svelte-1ipelgc {color: #e0f2fe !important;}
 """
 
 theme = gr.themes.Soft(
-primary_hue="sky", # blue
-secondary_hue="emerald", # green
-neutral_hue="slate"
+    primary_hue="blue",      # keeps primary button blue-ish
+    neutral_hue="green"      # secondary elements lean green
 ).set(
-body_background_fill="#0b1220",
-body_text_color="#e6f1f5",
-input_background_fill="#0f172a",
-input_border_color="#1f2937",
-button_primary_background_fill="#0284c7", # blue
-button_primary_text_color="#ffffff",
-button_secondary_background_fill="#0b2a22" # deep teal
+    body_background_fill="#1e3a8a",
+    body_text_color="#e0f2fe",
+    input_background_fill="#172554",
+    input_border_color="#1e40af",
+    button_primary_background_fill="#2563eb",
+    button_primary_text_color="#ffffff",
+    button_secondary_background_fill="#14532d",
+    button_secondary_text_color="#ecfdf5",
 )
 
 with gr.Blocks(css=CSS, theme=theme, fill_height=True) as demo:
-gr.Markdown(
-"<h1 style='margin:0'>🔮 Stress Gauge Factor (MPa⁻¹) — ML Predictor</h1>"
-"<p style='opacity:.9'>Fields and units match your training data. "
-"Leave anything blank if unknown — the model handles missing values.</p>"
-)
-
-with gr.Row():
-    # ---------------- Inputs (Left) ----------------
-    with gr.Column(scale=7):
-        # Primary filler
-        with gr.Accordion("Primary conductive filler", open=True, elem_classes=["card"]):
-            f1_type = gr.Textbox(label="Filler 1 Type", placeholder="e.g., CNT, Graphite, Steel fiber")
-            f1_dim = gr.Dropdown(DIM_CHOICES, value="NA", label="Filler 1 Dimensionality")
-            f1_diam = gr.Number(label="Filler 1 Diameter (µm)")
-            f1_len = gr.Number(label="Filler 1 Length (mm)")
-            cf_conc = gr.Number(label=f"{CF_COL}", info="Weight percent of total binder")
-
-        # Secondary filler (optional)
-        with gr.Accordion("➕ Secondary filler (optional)", open=False, elem_classes=["card"]):
-            f2_type = gr.Textbox(label="Filler 2 Type", placeholder="Optional")
-            f2_dim = gr.Dropdown(DIM_CHOICES, value="NA", label="Filler 2 Dimensionality")
-            f2_diam = gr.Number(label="Filler 2 Diameter (µm)")
-            f2_len = gr.Number(label="Filler 2 Length (mm)")
-
-        # Mix & specimen
-        with gr.Accordion("Mix design & specimen", open=False, elem_classes=["card"]):
-            spec_vol = gr.Number(label="Specimen Volume (mm3)")
-            probe_cnt = gr.Number(label="Probe Count")
-            probe_mat = gr.Textbox(label="Probe Material", placeholder="e.g., Copper, Silver paste")
-            wb = gr.Number(label="W/B")
-            sb = gr.Number(label="S/B")
-            gauge_len = gr.Number(label="Gauge Length (mm)")
-            curing = gr.Textbox(label="Curing Condition", placeholder="e.g., 28d water, 20°C")
-            n_fillers = gr.Number(label="Number of Fillers")
-
-        # Processing
-        with gr.Accordion("Processing", open=False, elem_classes=["card"]):
-            dry_temp = gr.Number(label="Drying Temperature (°C)")
-            dry_hrs = gr.Number(label="Drying Duration (hr)")
-
-        # Mechanical & Electrical loading
-        with gr.Accordion("Mechanical & electrical loading", open=False, elem_classes=["card"]):
-            load_rate = gr.Number(label="Loading Rate (MPa/s)")
-            E_mod     = gr.Number(label="Modulus of Elasticity (GPa)")
-            current   = gr.Dropdown(CURRENT_CHOICES, value="NA", label="Current Type")
-            voltage   = gr.Number(label="Applied Voltage (V)")
-
-    # ---------------- Output (Right) ----------------
-    with gr.Column(scale=5):
-        with gr.Group(elem_classes=["card"]):
-            out_pred = gr.Number(label="Predicted Stress GF (MPa-1)", precision=6)
-            with gr.Row():
-                btn_pred  = gr.Button("Predict", variant="primary")
-                btn_clear = gr.Button("Clear")
-                btn_demo  = gr.Button("Fill Example")
-
-        with gr.Accordion("About this model", open=False, elem_classes=["card"]):
-            gr.Markdown(
-                "- Pipeline: **ColumnTransformer → (RobustScaler + OneHot) → XGBoost**\n"
-                "- Target: **Stress GF (MPa⁻¹)** on original scale (model trains on log1p).\n"
-                "- Missing values are safely imputed per-feature.\n"
-                "- Trained columns:\n"
-                f"  `{', '.join(MAIN_VARIABLES)}`"
-            )
-
-# Wire buttons
-inputs_in_order = [
-    # MAIN_VARIABLES exact order:
-    # "Filler 1 Type","Filler 1 Diameter (µm)","Filler 1 Length (mm)", CF_COL,
-    # "Filler 1 Dimensionality","Filler 2 Type","Filler 2 Diameter (µm)","Filler 2 Length (mm)",
-    # "Filler 2 Dimensionality","Specimen Volume (mm3)","Probe Count","Probe Material",
-    # "W/B","S/B","Gauge Length (mm)","Curing Condition","Number of Fillers",
-    # "Drying Temperature (°C)","Drying Duration (hr)","Loading Rate (MPa/s)",
-    # "Modulus of Elasticity (GPa)","Current Type","Applied Voltage (V)"
-    f1_type, f1_diam, f1_len, cf_conc,
-    f1_dim,  f2_type, f2_diam, f2_len,
-    f2_dim,  spec_vol, probe_cnt, probe_mat,
-    wb, sb, gauge_len, curing, n_fillers,
-    dry_temp, dry_hrs, load_rate,
-    E_mod, current, voltage
-]
-
-def _predict_wrapper(*vals):
-    data = {k: v for k, v in zip(MAIN_VARIABLES, vals)}
-    return predict_fn(**data)
-
-btn_pred.click(_predict_wrapper, inputs=inputs_in_order, outputs=out_pred)
-btn_clear.click(lambda: _clear_all(), inputs=None, outputs=inputs_in_order)
-btn_demo.click(lambda: _fill_example(), inputs=None, outputs=inputs_in_order)
+    gr.Markdown(
+        "<h1 style='margin:0'>Stress Gauge Factor (MPa⁻¹) — ML Predictor</h1>"
+        "<p style='opacity:.9'>Fields and units match your training data. "
+        "Leave anything blank if unknown — the model handles missing values.</p>"
+    )
+
+    with gr.Row():
+        # ---------------- Inputs (Left) ----------------
+        with gr.Column(scale=7):
+            # Primary filler
+            with gr.Accordion("Primary conductive filler", open=True, elem_classes=["card"]):
+                f1_type = gr.Textbox(label="Filler 1 Type", placeholder="e.g., CNT, Graphite, Steel fiber")
+                f1_dim = gr.Dropdown(DIM_CHOICES, value="NA", label="Filler 1 Dimensionality")
+                f1_diam = gr.Number(label="Filler 1 Diameter (µm)")
+                f1_len = gr.Number(label="Filler 1 Length (mm)")
+                cf_conc = gr.Number(label=f"{CF_COL}", info="Weight percent of total binder")
+
+            # Secondary filler (optional)
+            with gr.Accordion("Secondary filler (optional)", open=False, elem_classes=["card"]):
+                f2_type = gr.Textbox(label="Filler 2 Type", placeholder="Optional")
+                f2_dim = gr.Dropdown(DIM_CHOICES, value="NA", label="Filler 2 Dimensionality")
+                f2_diam = gr.Number(label="Filler 2 Diameter (µm)")
+                f2_len = gr.Number(label="Filler 2 Length (mm)")
+
+            # Mix & specimen
+            with gr.Accordion("Mix design & specimen", open=False, elem_classes=["card"]):
+                spec_vol = gr.Number(label="Specimen Volume (mm3)")
+                probe_cnt = gr.Number(label="Probe Count")
+                probe_mat = gr.Textbox(label="Probe Material", placeholder="e.g., Copper, Silver paste")
+                wb = gr.Number(label="W/B")
+                sb = gr.Number(label="S/B")
+                gauge_len = gr.Number(label="Gauge Length (mm)")
+                curing = gr.Textbox(label="Curing Condition", placeholder="e.g., 28d water, 20°C")
+                n_fillers = gr.Number(label="Number of Fillers")
+
+            # Processing
+            with gr.Accordion("Processing", open=False, elem_classes=["card"]):
+                dry_temp = gr.Number(label="Drying Temperature (°C)")
+                dry_hrs = gr.Number(label="Drying Duration (hr)")
+
+            # Mechanical & Electrical loading
+            with gr.Accordion("Mechanical & electrical loading", open=False, elem_classes=["card"]):
+                load_rate = gr.Number(label="Loading Rate (MPa/s)")
+                E_mod     = gr.Number(label="Modulus of Elasticity (GPa)")
+                current   = gr.Dropdown(CURRENT_CHOICES, value="NA", label="Current Type")
+                voltage   = gr.Number(label="Applied Voltage (V)")
+
+        # ---------------- Output (Right) ----------------
+        with gr.Column(scale=5):
+            with gr.Group(elem_classes=["card"]):
+                out_pred = gr.Number(label="Predicted Stress GF (MPa-1)", precision=6)
+                with gr.Row():
+                    btn_pred  = gr.Button("Predict", variant="primary")
+                    btn_clear = gr.Button("Clear")
+                    btn_demo  = gr.Button("Fill Example")
+
+            with gr.Accordion("About this model", open=False, elem_classes=["card"]):
+                gr.Markdown(
+                    "- Pipeline: **ColumnTransformer → (RobustScaler + OneHot) → XGBoost**\n"
+                    "- Target: **Stress GF (MPa⁻¹)** on original scale (model trains on log1p).\n"
+                    "- Missing values are safely imputed per-feature.\n"
+                    "- Trained columns:\n"
+                    f"  `{', '.join(MAIN_VARIABLES)}`"
+                )
+
+    # Wire buttons
+    inputs_in_order = [
+        f1_type, f1_diam, f1_len, cf_conc,
+        f1_dim,  f2_type, f2_diam, f2_len,
+        f2_dim,  spec_vol, probe_cnt, probe_mat,
+        wb, sb, gauge_len, curing, n_fillers,
+        dry_temp, dry_hrs, load_rate,
+        E_mod, current, voltage
+    ]
+
+    def _predict_wrapper(*vals):
+        data = {k: v for k, v in zip(MAIN_VARIABLES, vals)}
+        return predict_fn(**data)
+
+    btn_pred.click(_predict_wrapper, inputs=inputs_in_order, outputs=out_pred)
+    btn_clear.click(lambda: _clear_all(), inputs=None, outputs=inputs_in_order)
+    btn_demo.click(lambda: _fill_example(), inputs=None, outputs=inputs_in_order)
+
+# ------------- Launch -------------
+if __name__ == "__main__":
+    demo.queue().launch()
+```
+
+### What changed?
+1. **CSS** – a smooth **blue (`#1e3a8a`) to green (`#15803d`)** gradient.
+2. **Theme** – `Soft` theme with `primary_hue="blue"` and `neutral_hue="green"`; explicit colour overrides for body, inputs, and buttons to stay in the blue-green palette.
+3. **Card styling** – translucent white background with a slightly brighter border for contrast on the new gradient.
+
+Just replace your old file with this one (or copy the `CSS` and `theme` sections) and run – the UI will now have a **blue-green background** while keeping all functionality intact.