Update app.py

app.py

@@ -1,45 +1,69 @@
+# app.py
 import gradio as gr
-from evo_transformer import EvoTransformer
 import matplotlib.pyplot as plt
 import pandas as pd
-import seaborn as sns
+import io
+from evo_transformer import EvoTransformer
 
-def simulate_evolution(generations):
-    model = EvoTransformer()
-    model.evolve(generations)
-    history = model.get_history()
-    
-    # Evaluation of final model
-    final_result = model.evaluate()
+def run_evolution(generations):
+    evo = EvoTransformer()
+    evo.evolve(generations)
+
+    history = evo.get_history()
+    final_eval = evo.evaluate()
     
-    # Visualization
-    fig, ax = plt.subplots(figsize=(10, 5))
     df = pd.DataFrame(history)
-    sns.lineplot(data=df.drop("memory", axis=1), markers=True, ax=ax)
-    ax.set_title("EvoTransformer Trait Evolution")
-    ax.set_ylabel("Value")
-    ax.set_xlabel("Generation")
-    plt.xticks(range(len(df)))
-    plt.tight_layout()
+    df_display = df.copy()
+    df_display["memory"] = df_display["memory"].apply(lambda x: "Enabled" if x else "Disabled")
+
+    # Radar chart
+    last_config = history[-1]
+    traits = ["layers", "attention_heads", "ffn_dim", "dropout", "memory"]
+    values = [last_config["layers"], last_config["attention_heads"],
+              last_config["ffn_dim"]/100, last_config["dropout"]*10, int(last_config["memory"])*10]
     
+    fig, ax = plt.subplots(figsize=(6,6), subplot_kw=dict(polar=True))
+    angles = [n / float(len(traits)) * 2 * 3.14159 for n in range(len(traits))]
+    values += values[:1]
+    angles += angles[:1]
+    ax.plot(angles, values, linewidth=2)
+    ax.fill(angles, values, alpha=0.3)
+    ax.set_xticks(angles[:-1])
+    ax.set_xticklabels(traits)
+    ax.set_title("Final Architecture Traits", size=15)
+
+    # File downloads
+    csv_file = io.StringIO(evo.export_csv())
+    json_file = io.StringIO(evo.export_json())
+
     return (
-        final_result["accuracy"],
-        round(final_result["params"], 2),
-        fig
+        df_display,
+        final_eval["accuracy"],
+        final_eval["params"],
+        fig,
+        ("evo_history.csv", csv_file.getvalue()),
+        ("evo_history.json", json_file.getvalue())
     )
 
-# UI
-with gr.Blocks(title="EvoTransformer: Adaptive Architecture Evolution") as demo:
-    gr.Markdown("# 🧬 EvoTransformer Demo")
-    gr.Markdown("Evolving architecture live — inspired by nature. Tune the number of generations below and visualize how traits change during evolution.")
+with gr.Blocks(title="EvoTransformer Demo") as demo:
+    gr.Markdown("# 🧬 EvoTransformer Live Demo")
+    gr.Markdown("This demo evolves a Transformer architecture and displays how traits change over generations.")
+
+    with gr.Row():
+        generations = gr.Slider(1, 10, value=5, step=1, label="Generations")
+        run_btn = gr.Button("Evolve Now 🚀")
+
+    with gr.Row():
+        acc = gr.Number(label="Estimated Accuracy")
+        params = gr.Number(label="Estimated Params (M)")
 
-    generations = gr.Slider(1, 20, value=5, step=1, label="Number of Generations")
-    btn = gr.Button("Evolve EvoTransformer")
+    table = gr.Dataframe(label="Evolution History", wrap=True)
+    plot = gr.Plot(label="Final Architecture (Radar Chart)")
 
-    accuracy = gr.Textbox(label="Estimated Accuracy", interactive=False)
-    params = gr.Textbox(label="Estimated Parameter Count (M)", interactive=False)
-    plot = gr.Plot(label="Architecture Trait Evolution")
+    with gr.Row():
+        csv_dl = gr.File(label="Download CSV", file_types=[".csv"], interactive=True)
+        json_dl = gr.File(label="Download JSON", file_types=[".json"], interactive=True)
 
-    btn.click(fn=simulate_evolution, inputs=generations, outputs=[accuracy, params, plot])
+    run_btn.click(fn=run_evolution, inputs=generations, outputs=[table, acc, params, plot, csv_dl, json_dl])
 
 demo.launch()