Update app.py

app.py

@@ -1,94 +1,125 @@
+# app.py
+
 import gradio as gr
-import matplotlib.pyplot as plt
-import pandas as pd
-import numpy as np
-import io
 from evo_transformer import EvoTransformer
+import pandas as pd
+import matplotlib.pyplot as plt
+import tempfile
+import os
+import json
 
-# Global instance (resettable)
-evo = EvoTransformer()
-
-# === Visualization Functions ===
-def plot_radar(config):
-    labels = ["Layers", "Attention Heads", "FFN Dim", "Dropout", "Memory"]
-    values = [
-        config["layers"],
-        config["attention_heads"],
-        config["ffn_dim"],
-        int(config["dropout"] * 100),
-        int(config["memory"])
-    ]
-    angles = np.linspace(0, 2 * np.pi, len(labels), endpoint=False).tolist()
-    values += values[:1]
-    angles += angles[:1]
+# === Initialize Model ===
+model = EvoTransformer()
 
-    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 Architecture (Radar Chart)")
-    return fig
+# === Create Interface Components ===
+generations = gr.Slider(1, 10, value=3, step=1, label="Number of Generations")
+
+evolve_btn = gr.Button("🧬 Evolve Architecture")
 
-def evolve_and_display(generations):
-    global evo
-    evo = EvoTransformer()  # Reset model
-    evo.evolve(generations)
+accuracy_out = gr.Textbox(label="Simulated Accuracy")
+params_out = gr.Textbox(label="Estimated Parameters")
 
-    df = evo.get_history_df()
-    final_config = evo.get_final_config()
-    accuracy, params = evo.evaluate()
+tabbox = gr.Textbox(label="Current Config Summary")
 
-    fig = plot_radar(final_config)
+# Dynamic display of evolution history
+history_display = [gr.Textbox(label=f"Gen {i+1} Config") for i in range(10)]
 
-    json_file = io.BytesIO()
-    json_file.write(evo.get_history_json().encode("utf-8"))
-    json_file.seek(0)
+# Download buttons
+csv_btn = gr.File(label="Download CSV History")
+json_btn = gr.File(label="Download JSON History")
 
-    csv_file = io.BytesIO()
-    df.to_csv(csv_file, index=False)
-    csv_file.seek(0)
+# === Helper: Create Evolution Radar Plot ===
+def plot_radar(history):
+    import numpy as np
+
+    traits = ["layers", "attention_heads", "ffn_dim", "dropout", "memory"]
+    N = len(traits)
+    values = [history[-1].get(t, 0) for t in traits]
+    values = [int(v) if isinstance(v, bool) else v for v in values]
+
+    angles = np.linspace(0, 2 * np.pi, N, 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([a * 180 / np.pi for a in angles[:-1]], traits)
+    ax.set_title("Last Gen Trait Radar", fontsize=14)
+    plt.tight_layout()
+
+    tmp = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
+    plt.savefig(tmp.name)
+    plt.close()
+    return tmp.name
+
+radar_plot = gr.Image(label="Final Generation Trait Radar")
+
+# === Main Evolution Logic ===
+def evolve_and_display(gens):
+    model.evolve(generations=gens)
+    history = model.get_history()
+    eval_result = model.evaluate()
+
+    # Format summary
+    summary = "\n".join([f"{k}: {v}" for k, v in history[-1].items()])
+
+    # Fill up to 10 generations of history for display
+    history_txt = [json.dumps(h, indent=2) for h in history]
+    while len(history_txt) < 10:
+        history_txt.append("")
+
+    # Generate CSV + JSON
+    df = pd.DataFrame(history)
+    csv_path = tempfile.NamedTemporaryFile(suffix=".csv", delete=False).name
+    json_path = tempfile.NamedTemporaryFile(suffix=".json", delete=False).name
+    df.to_csv(csv_path, index=False)
+    with open(json_path, "w") as jf:
+        json.dump(history, jf, indent=2)
+
+    # Plot radar
+    radar_img = plot_radar(history)
 
     return (
-        accuracy,
-        params,
-        gr.Tabs.update(visible=True),
-        [gr.Textbox.update(value=str(row)) for _, row in df.iterrows()],
-        fig,
-        (csv_file, "evo_history.csv"),
-        (json_file, "evo_history.json"),
+        f"{eval_result['accuracy']*100:.2f}%",
+        f"{eval_result['params']:.2f}M params",
+        summary,
+        *history_txt,
+        radar_img,
+        csv_path,
+        json_path,
     )
 
-# === Gradio UI ===
-with gr.Blocks(title="EvoTransformer Live Demo") as demo:
-    gr.Markdown(
-        "🚀 **EvoTransformer Live Demo**\n\n"
-        "This demo evolves a Transformer architecture and displays how traits change over generations."
-    )
+# === Interface Layout ===
+with gr.Blocks(title="EvoTransformer Demo") 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():
-        generations = gr.Slider(1, 10, value=5, label="Generations")
-        evolve_btn = gr.Button("Evolve Now 🚀")
+        accuracy_out.render()
+        params_out.render()
 
     with gr.Row():
-        accuracy_out = gr.Number(label="Estimated Accuracy", value=0)
-        params_out = gr.Number(label="Estimated Params (M)", value=0)
+        radar_plot.render()
+        tabbox.render()
 
-    tabbox = gr.Tabs(visible=False)
-    with tabbox:
-        with gr.Tab(label="Evolution History"):
-            history_display = [gr.Textbox(label=str(i+1), interactive=False) for i in range(10)]
-        with gr.Tab(label="Radar View"):
-            radar_plot = gr.Plot()
+    with gr.Row():
+        for box in history_display:
+            box.render()
 
     with gr.Row():
-        csv_btn = gr.File(label="Download CSV")
-        json_btn = gr.File(label="Download JSON")
+        csv_btn.render()
+        json_btn.render()
 
     evolve_btn.click(
         evolve_and_display,
         inputs=[generations],
-        outputs=[accuracy_out, params_out, tabbox, history_display, radar_plot, csv_btn, json_btn]
+        outputs=[accuracy_out, params_out, tabbox, *history_display, radar_plot, csv_btn, json_btn],
     )
 
+# === Launch App ===
 if __name__ == "__main__":
     demo.launch()