Update app.py

app.py

@@ -1,113 +1,86 @@
+# app.py
 import gradio as gr
-import pandas as pd
 import json
-import os
-from plot import plot_radar_chart
-from diagram import show_transformer_diagram
+import csv
+import io
 from evo_transformer import EvoTransformer
+from plot import plot_radar_chart
 
-# === Initialize ===
+# Global instance
 evo = EvoTransformer()
 
-# === 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 = []
-
-# === 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"
-
-    # Plot radar chart
+def evolve_model(num_generations):
+    evo.reset()  # reset before evolution
+    evo.evolve(num_generations)
+    final_config = evo.config
+    history = evo.get_history()
+    evaluation = evo.evaluate()
+
+    # Radar Chart
     try:
-        plot_radar_chart(evo.config, radar_path)
+        radar_img = plot_radar_chart(final_config)
     except Exception as e:
         print("Radar chart error:", e)
-        radar_path = None
+        radar_img = 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)
+    # Prepare history display
+    history_cards = []
+    for i, h in enumerate(history):
+        text = f"Gen {i + 1} Config: {h}"
+        history_cards.append(text)
 
-    # History cards
-    history = evo.get_history()
-    history_cards = [f"Gen {i+1} Config: {h}" for i, h in enumerate(history)]
+    # Prepare CSV and JSON
+    csv_file = io.StringIO()
+    csv_writer = csv.DictWriter(csv_file, fieldnames=history[0].keys())
+    csv_writer.writeheader()
+    csv_writer.writerows(history)
+    csv_bytes = io.BytesIO(csv_file.getvalue().encode())
 
-    # History downloadables
-    df = pd.DataFrame(history)
-    df_csv_path = "evo_history.csv"
-    df.to_csv(df_csv_path, index=False)
-
-    json_path = "evo_history.json"
-    with open(json_path, "w") as f:
-        json.dump(history, f, indent=2)
+    json_file = io.StringIO(json.dumps(history, indent=2))
+    json_bytes = io.BytesIO(json_file.getvalue().encode())
 
     return (
-        f"{score['accuracy']*100:.2f}%",
-        f"{score['params']:.2f}M params",
-        str(evo.config),
-        radar_path,
-        diagram_bytes,
+        f"{evaluation['accuracy']:.2f}%",
+        f"{evaluation['params']:.2f}M params",
+        str(final_config),
+        radar_img,
+        None,  # placeholder for future diagram
         *history_cards,
-        df_csv_path,
-        json_path
+        ("evo_history.csv", csv_bytes),
+        ("evo_history.json", json_bytes)
     )
 
-# === 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.Blocks(title="EvoTransformer") as demo:
-    gr.Markdown("""
-    # 🧬 EvoTransformer – Evolving Transformer Architectures  
-    Simulate trait mutation and adaptive architecture generation.
-    """)
+with gr.Blocks(title="🧬 EvoTransformer – Evolving Transformer Architectures") as demo:
+    gr.Markdown("## 🧬 EvoTransformer – Evolving Transformer Architectures\nSimulate trait mutation and adaptive architecture generation.")
 
     with gr.Row():
-        generations_input.render()
-        evolve_btn.render()
+        num_generations = gr.Slider(minimum=1, maximum=10, value=3, label="Number of Generations", step=1)
+        evolve_btn = gr.Button("🧬 Evolve Architecture")
 
-    accuracy_output.render()
-    params_output.render()
-    current_config_output.render()
+    with gr.Row():
+        accuracy_text = gr.Textbox(label="Simulated Accuracy")
+        param_text = gr.Textbox(label="Estimated Parameters")
+        config_text = gr.Textbox(label="Current Config Summary")
 
     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")
+    radar_output = gr.Image(label="Final Generation Trait Radar", type="pil", interactive=False)
+    diagram_output = gr.Image(label="Illustrative Transformer Structure", visible=False)
+
+    history_boxes = [gr.Textbox(label=f"Gen {i+1} Config") for i in range(10)]
 
-    for _ in range(10):
-        card = gr.Textbox(label="", interactive=False)
-        history_outputs.append(card)
+    with gr.Accordion("Downloadable Files", open=True):
+        csv_out = gr.File(label="Download CSV History")
+        json_out = gr.File(label="Download JSON History")
 
     evolve_btn.click(
         fn=evolve_model,
-        inputs=[generations_input],
+        inputs=[num_generations],
         outputs=[
-            accuracy_output,
-            params_output,
-            current_config_output,
-            radar_image,
-            diagram_image,
-            *history_outputs,
-            csv_file,
-            json_file
+            accuracy_text, param_text, config_text,
+            radar_output, diagram_output,
+            *history_boxes,
+            csv_out, json_out
         ]
     )