Update app.py

app.py

@@ -1,74 +1,78 @@
 import gradio as gr
-import json
-import pandas as pd
 from evo_transformer import EvoTransformer
-from plots import plot_radar
-from diagrams import draw_transformer_diagram
+from plots import plot_radar_chart
+from diagrams import get_transformer_diagram
+import pandas as pd
+import json
+import tempfile
 
-# Initialize EvoTransformer
-evo = EvoTransformer()
+et = EvoTransformer()
 
-def evolve_transformer(generations):
-    evo = EvoTransformer()
-    evo.evolve(generations)
-    history = evo.get_history()
-    final_config = history[-1]
-    eval_result = evo.evaluate()
+def run_evolution(generations):
+    et.reset()
+    et.evolve(generations)
 
-    radar_path = plot_radar(final_config)
-    diagram_path = draw_transformer_diagram()
+    final_eval = et.evaluate()
+    csv_path = tempfile.NamedTemporaryFile(delete=False, suffix=".csv").name
+    json_path = tempfile.NamedTemporaryFile(delete=False, suffix=".json").name
 
-    csv_path = "history.csv"
-    json_path = "history.json"
-    pd.DataFrame(history).to_csv(csv_path, index=False)
+    df = pd.DataFrame(et.get_history())
+    df.to_csv(csv_path, index=False)
     with open(json_path, "w") as f:
-        json.dump(history, f, indent=2)
+        json.dump(et.get_history(), f)
 
-    # Format config display
-    summary = "\n".join(f"{k}: {v}" for k, v in final_config.items())
+    radar_plot = plot_radar_chart(et.config)
+    diagram_path = get_transformer_diagram(et.config)
+
+    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())]
 
     return (
-        f"{eval_result['accuracy']*100:.2f}%",
-        f"{eval_result['params']:.2f}M params",
-        summary,
-        radar_path,
+        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,
         json_path
     )
 
-# Gradio Interface
-with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
-    gr.Markdown("""
-    # 🧬 EvoTransformer – Evolving Transformer Architectures
-    Simulate trait mutation and adaptive architecture generation.
-    """)
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## 🧬 EvoTransformer – Evolving Transformer Architectures")
+    gr.Markdown("Simulate trait mutation and adaptive architecture generation.")
 
     with gr.Row():
-        gens = gr.Slider(1, 10, value=3, step=1, label="Number of Generations")
-        evolve_btn = gr.Button("\ud83e\uddec Evolve Architecture")
+        generations_slider = gr.Slider(1, 10, value=3, label="Number of Generations", step=1)
+        evolve_btn = gr.Button("🧬 Evolve Architecture", variant="primary")
 
     with gr.Row():
-        acc_out = gr.Textbox(label="Simulated Accuracy")
-        param_out = gr.Textbox(label="Estimated Parameters")
-
-    summary_out = gr.Textbox(label="Current Config Summary", lines=5)
-
-    gr.Markdown("""
-    ## 🧬 Evolution History
-    """)
+        accuracy_output = gr.Textbox(label="Simulated Accuracy")
+        param_output = gr.Textbox(label="Estimated Parameters")
+        current_config = gr.Textbox(label="Current Config Summary", lines=5)
 
-    radar_img = gr.Image(label="Final Generation Trait Radar")
-    diagram_img = gr.Image(label="Transformer Architecture")
+    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()
 
     with gr.Row():
-        csv_dl = gr.File(label="Download CSV History")
-        json_dl = gr.File(label="Download JSON History")
+        csv_download = gr.File(label="Download CSV History")
+        json_download = gr.File(label="Download JSON History")
 
     evolve_btn.click(
-        fn=evolve_transformer,
-        inputs=[gens],
-        outputs=[acc_out, param_out, summary_out, radar_img, diagram_img, csv_dl, json_dl]
+        fn=run_evolution,
+        inputs=[generations_slider],
+        outputs=[
+            accuracy_output,
+            param_output,
+            current_config,
+            radar_output,
+            diagram_output,
+            history_group,
+            csv_download,
+            json_download,
+        ],
     )
 
 if __name__ == "__main__":