Update app.py

app.py

@@ -1,79 +1,114 @@
 import gradio as gr
-from evo_transformer import EvoTransformer
-from plots import plot_radar_chart
-from diagrams import get_transformer_diagram
 import pandas as pd
 import json
-import tempfile
+import os
+from evo_transformer import EvoTransformer
+from plot import plot_radar_chart
+from diagram import plot_architecture_diagram
 
-et = EvoTransformer()
+# === Initialize ===
+evo = EvoTransformer()
 
-def run_evolution(generations):
-    et.reset()
-    et.evolve(generations)
+# === Gradio Output Placeholders ===
+accuracy_output = gr.Text(label="Simulated Accuracy")
+params_output = gr.Text(label="Estimated Parameters")
+current_config_output = gr.Text(label="Current Config Summary")
+radar_image = gr.Image(label="Final Generation Trait Radar")
+diagram_image = gr.Image(label="Illustrative Transformer Structure")
+history_outputs = []
 
-    final_eval = et.evaluate()
-    csv_path = tempfile.NamedTemporaryFile(delete=False, suffix=".csv").name
-    json_path = tempfile.NamedTemporaryFile(delete=False, suffix=".json").name
+# === Core Evolution Function ===
+def evolve_model(generations):
+    evo.__init__()  # Reset EvoTransformer
+    evo.evolve(generations)
+    score = evo.evaluate()
+    radar_path = "radar_chart.png"
+    diagram_path = "architecture_diagram.png"
 
-    df = pd.DataFrame(et.get_history())
-    df.to_csv(csv_path, index=False)
-    with open(json_path, "w") as f:
-        json.dump(et.get_history(), f)
+    # Plot radar chart
+    try:
+        plot_radar_chart(evo.config, radar_path)
+    except Exception as e:
+        print("Radar chart error:", e)
+        radar_path = None
+
+    # Plot architecture diagram
+    diagram_bytes = None
+    try:
+        plot_architecture_diagram(evo.config)
+        if os.path.exists(diagram_path):
+            with open(diagram_path, "rb") as f:
+                diagram_bytes = f.read()
+    except Exception as e:
+        print("Diagram plot error:", e)
+
+    # History cards
+    history = evo.get_history()
+    history_cards = [f"Gen {i+1} Config: {h}" for i, h in enumerate(history)]
 
-    radar_plot = plot_radar_chart(et.config)
-    diagram_path = get_transformer_diagram(et.config)
+    # History downloadables
+    df = pd.DataFrame(history)
+    df_csv_path = "evo_history.csv"
+    df.to_csv(df_csv_path, index=False)
 
-    history_outputs = [gr.Textbox(label=f"Gen {i+1} Config", value=json.dumps(cfg, indent=2), lines=4) for i, cfg in enumerate(et.get_history())]
+    json_path = "evo_history.json"
+    with open(json_path, "w") as f:
+        json.dump(history, f, indent=2)
 
     return (
-        f"{final_eval['accuracy']*100:.2f}%",
-        f"{final_eval['params']:.2f}M params",
-        json.dumps(et.config, indent=2),
-        radar_plot,
-        diagram_path,
-        history_outputs,
-        csv_path,
+        f"{score['accuracy']*100:.2f}%",
+        f"{score['params']:.2f}M params",
+        str(evo.config),
+        radar_path,
+        diagram_bytes,
+        *history_cards,
+        df_csv_path,
         json_path
     )
 
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("## 🧬 EvoTransformer – Evolving Transformer Architectures")
-    gr.Markdown("Simulate trait mutation and adaptive architecture generation.")
+# === Gradio Interface ===
+generations_input = gr.Slider(1, 10, value=3, step=1, label="Number of Generations")
+evolve_btn = gr.Button("\U0001F9EC Evolve Architecture")
 
-    with gr.Row():
-        generations_slider = gr.Slider(1, 10, value=3, label="Number of Generations", step=1)
-        evolve_btn = gr.Button("🧬 Evolve Architecture", variant="primary")
+with gr.Blocks(title="EvoTransformer") as demo:
+    gr.Markdown("""
+    # 🧬 EvoTransformer – Evolving Transformer Architectures  
+    Simulate trait mutation and adaptive architecture generation.
+    """)
 
     with gr.Row():
-        accuracy_output = gr.Textbox(label="Simulated Accuracy")
-        param_output = gr.Textbox(label="Estimated Parameters")
-        current_config = gr.Textbox(label="Current Config Summary", lines=5)
+        generations_input.render()
+        evolve_btn.render()
 
-    with gr.Column():
-        gr.Markdown("## 🧬 Evolution History")
-        radar_output = gr.Image(label="Final Generation Trait Radar", height=400)
-        diagram_output = gr.Image(label="Illustrative Transformer Structure", height=300)
-        history_group = gr.Group()
+    accuracy_output.render()
+    params_output.render()
+    current_config_output.render()
 
-    with gr.Row():
-        csv_download = gr.File(label="Download CSV History")
-        json_download = gr.File(label="Download JSON History")
+    gr.Markdown("## 🧬 Evolution History")
+    radar_image.render()
+    diagram_image.render()
+
+    with gr.Accordion("Downloadable Files", open=True):
+        csv_file = gr.File(label="Download CSV History")
+        json_file = gr.File(label="Download JSON History")
+
+    for _ in range(10):
+        card = gr.Textbox(label="", interactive=False)
+        history_outputs.append(card)
 
     evolve_btn.click(
-        fn=run_evolution,
-        inputs=[generations_slider],
+        fn=evolve_model,
+        inputs=[generations_input],
         outputs=[
             accuracy_output,
-            param_output,
-            current_config,
-            radar_output,
-            diagram_output,
-            history_group,
-            csv_download,
-            json_download,
-        ],
+            params_output,
+            current_config_output,
+            radar_image,
+            diagram_image,
+            *history_outputs,
+            csv_file,
+            json_file
+        ]
     )
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()