Update app.py

app.py

@@ -1,34 +1,39 @@
-# app.py
-
 import gradio as gr
 from evo_transformer import EvoTransformer
 import pandas as pd
-import matplotlib.pyplot as plt
-import tempfile
-import os
 import json
+import tempfile
+import matplotlib.pyplot as plt
+import numpy as np
 
-# === Initialize Model ===
 model = EvoTransformer()
 
-# === Create Interface Components ===
-generations = gr.Slider(1, 10, value=3, step=1, label="Number of Generations")
-
-evolve_btn = gr.Button("🧬 Evolve Architecture")
-
-accuracy_out = gr.Textbox(label="Simulated Accuracy")
-params_out = gr.Textbox(label="Estimated Parameters")
+def plot_radar(history):
+    traits = ["layers", "attention_heads", "ffn_dim", "dropout"]
+    labels = traits
+    last = history[-1]
+    values = [
+        last["layers"] / 12,
+        last["attention_heads"] / 12,
+        last["ffn_dim"] / 2048,
+        last["dropout"] / 0.5,
+    ]
+    angles = np.linspace(0, 2 * np.pi, len(traits), endpoint=False).tolist()
+    values += values[:1]
+    angles += angles[:1]
+
+    fig, ax = plt.subplots(figsize=(5,5), subplot_kw=dict(polar=True))
+    ax.plot(angles, values, "o-", linewidth=2)
+    ax.fill(angles, values, alpha=0.25)
+    ax.set_thetagrids(np.degrees(angles[:-1]), labels)
+    ax.set_title("Final Generation Trait Radar")
+    ax.grid(True)
+
+    img_path = tempfile.NamedTemporaryFile(suffix=".png", delete=False).name
+    plt.savefig(img_path)
+    plt.close(fig)
+    return img_path
 
-tabbox = gr.Textbox(label="Current Config Summary")
-
-# Dynamic display of evolution history
-history_display = [gr.Textbox(label=f"Gen {i+1} Config") for i in range(10)]
-
-# Download buttons
-csv_btn = gr.File(label="Download CSV History")
-json_btn = gr.File(label="Download JSON History")
-
-# === Helper: Create Evolution Radar Plot ===
 def evolve_and_display(gens):
     try:
         model.evolve(generations=gens)
@@ -70,36 +75,41 @@ def evolve_and_display(gens):
             None, None, None
         )
 
-# === Interface Layout ===
-with gr.Blocks(title="EvoTransformer Demo") as demo:
+with gr.Blocks() as demo:
     gr.Markdown("# 🧬 EvoTransformer – Evolving Transformer Architectures")
     gr.Markdown("Simulate trait mutation and adaptive architecture generation.")
-    with gr.Row():
-        generations.render()
-        evolve_btn.render()
 
     with gr.Row():
-        accuracy_out.render()
-        params_out.render()
+        generations = gr.Slider(1, 10, value=3, step=1, label="Number of Generations")
+        evolve_btn = gr.Button("🧬 Evolve Architecture")
 
     with gr.Row():
-        radar_plot.render()
-        tabbox.render()
+        acc_out = gr.Text(label="Simulated Accuracy")
+        param_out = gr.Text(label="Estimated Parameters")
 
-    with gr.Row():
-        for box in history_display:
-            box.render()
+    summary_out = gr.Textbox(label="Current Config Summary", lines=5)
+
+    with gr.Accordion("🧬 Evolution History", open=False):
+        hist_outputs = [gr.Textbox(label=f"Gen {i+1} Config", lines=4) for i in range(10)]
+
+    radar_plot = gr.Image(label="Final Generation Trait Radar")
 
     with gr.Row():
-        csv_btn.render()
-        json_btn.render()
+        csv_out = gr.File(label="Download CSV History")
+        json_out = gr.File(label="Download JSON History")
 
     evolve_btn.click(
         evolve_and_display,
         inputs=[generations],
-        outputs=[accuracy_out, params_out, tabbox, *history_display, radar_plot, csv_btn, json_btn],
+        outputs=[
+            acc_out,
+            param_out,
+            summary_out,
+            *hist_outputs,
+            radar_plot,
+            csv_out,
+            json_out
+        ],
     )
 
-# === Launch App ===
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()