Update app.py

app.py

@@ -1,60 +1,69 @@
 import gradio as gr
-import datetime
 from inference import generate_response
-from logger import log_feedback
-from init_model import initialize_evo_model
-from init_save import retrain_model
+from logger import log_user_feedback
+from dashboard import update_dashboard_plot
+from watchdog import retrain_model
 
-print(f"===== Application Startup at {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')} =====")
+evo_output = gr.Textbox(label="🧠 EvoTransformer Suggestion")
+gpt_output = gr.Textbox(label="💬 GPT-3.5 Suggestion")
+feedback_output = gr.Textbox(visible=False)
 
-# Reinitialize EvoTransformer model on startup
-initialize_evo_model()
-
-# Gradio app logic
 def evo_chat(goal, sol1, sol2):
-    if not goal.strip() or not sol1.strip() or not sol2.strip():
-        return "❌ Please fill all fields.", "", "", "", "", gr.update(visible=False)
-
-    suggestion = generate_response(goal, sol1, sol2)
-    return "", "", "", suggestion, "", gr.update(visible=True)
-
-def log_user_feedback(goal, sol1, sol2, winner):
-    status = log_feedback(goal, sol1, sol2, winner)
-    return status
+    response = generate_response(goal, sol1, sol2)
+    evo = response.get("evo_suggestion", "Error")
+    gpt = response.get("gpt_suggestion", "Error")
+    return evo, gpt
 
-def retrain_evo_model():
-    success = retrain_model()
-    return "✅ Retrained successfully." if success else "⚠️ Retrain failed."
+def handle_feedback(goal, sol1, sol2, winner):
+    try:
+        log_user_feedback(goal, sol1, sol2, winner)
+        return "✅ Feedback logged. Thank you!"
+    except Exception as e:
+        return f"❌ Failed to log: {e}"
 
-with gr.Blocks(css=".gradio-container {font-family: 'Segoe UI'; font-size: 16px;}") as demo:
+with gr.Blocks(title="EvoTransformer v2.1 – Compare Options and Learn") as demo:
     gr.Markdown("## 🧠 EvoTransformer v2.1 – Compare Options and Learn")
 
     with gr.Row():
-        goal = gr.Textbox(label="Goal", placeholder="e.g. Escape from house on fire")
-    
+        goal_input = gr.Textbox(label="Goal", placeholder="e.g. Escape from house on fire")
     with gr.Row():
-        sol1 = gr.Textbox(label="Option 1", placeholder="e.g. Exit house through main door")
-        sol2 = gr.Textbox(label="Option 2", placeholder="e.g. Hide under bed")
+        option1_input = gr.Textbox(label="Option 1", placeholder="e.g. Exit house through main door")
+        option2_input = gr.Textbox(label="Option 2", placeholder="e.g. Hide under bed")
+
+    compare_btn = gr.Button("🔍 Compare")
 
     with gr.Row():
-        error_box = gr.Textbox(label="Error", visible=False)
-    
-    model_suggestion = gr.Textbox(label="Model Suggestion")
-    
-    compare_button = gr.Button("🔍 Compare")
-    compare_button.click(evo_chat, inputs=[goal, sol1, sol2], outputs=[error_box, sol1, sol2, model_suggestion, goal, compare_button])
+        evo_output.render()
+        gpt_output.render()
 
     with gr.Row():
-        winner_choice = gr.Radio(["Solution 1", "Solution 2"], label="Which was better?")
+        winner_dropdown = gr.Radio(["Solution 1", "Solution 2"], label="Which was better?")
         feedback_btn = gr.Button("✅ Log Feedback")
-        feedback_status = gr.Textbox(label="", interactive=False)
-        feedback_btn.click(log_user_feedback, inputs=[goal, sol1, sol2, winner_choice], outputs=[feedback_status])
 
-    gr.Markdown("## 📊 Dashboard")
+    feedback_output.render()
+
+    compare_btn.click(
+        fn=evo_chat,
+        inputs=[goal_input, option1_input, option2_input],
+        outputs=[evo_output, gpt_output]
+    )
+
+    feedback_btn.click(
+        fn=handle_feedback,
+        inputs=[goal_input, option1_input, option2_input, winner_dropdown],
+        outputs=[feedback_output]
+    )
+
+    with gr.Row():
+        gr.Markdown("### 📊 Dashboard")
+        dashboard_plot = gr.Plot()
+        update_dashboard_plot(dashboard_plot)
+
     with gr.Row():
         retrain_button = gr.Button("♻️ Retrain Evo")
-        retrain_output = gr.Textbox(label="Retrain Status")
-        retrain_button.click(retrain_evo_model, outputs=[retrain_output])
+        retrain_status = gr.Textbox(label="Retrain Status")
+
+    retrain_button.click(fn=retrain_model, inputs=[], outputs=[retrain_status])
 
-# Launch with SSR and shareable link if needed
-demo.launch(share=True, server_name="0.0.0.0", server_port=7860, show_error=True, ssr_mode=True)
+if __name__ == "__main__":
+    demo.launch(share=True)