Update app.py

app.py

@@ -1,62 +1,60 @@
-import os
-
-# Run init_save.py only once if trained_model is empty
-if not os.path.exists("trained_model/config.json"):
-    print("⚙️ Reinitializing EvoTransformer model...")
-    import init_save
-
-
-import os
 import gradio as gr
-from watchdog import manual_retrain
+import datetime
 from inference import generate_response
 from logger import log_feedback
-from dashboard import display_dashboard
+from init_model import initialize_evo_model
+from init_save import retrain_model
 
-# ✅ Ensure model is initialized
-if not os.path.exists("trained_model/config.json"):
-    print("📦 No model found in 'trained_model/'. Initializing...")
-    exec(open("init_save.py").read())
+print(f"===== Application Startup at {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')} =====")
 
-print("===== Application Startup at 2025-07-14 12:XX:XX =====")
+# Reinitialize EvoTransformer model on startup
+initialize_evo_model()
 
-# ✅ Interface logic
+# Gradio app logic
 def evo_chat(goal, sol1, sol2):
-    response = generate_response(goal, sol1, sol2)
-    return response
+    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 retrain_model():
-    success = manual_retrain()
-    return "✅ Retrained successfully!" if success else "⚠️ Retrain failed."
+def log_user_feedback(goal, sol1, sol2, winner):
+    status = log_feedback(goal, sol1, sol2, winner)
+    return status
 
-def log_user_feedback(goal, sol1, sol2, correct):
-    log_feedback(goal, sol1, sol2, correct)
-    return "✅ Feedback logged. Thank you!"
+def retrain_evo_model():
+    success = retrain_model()
+    return "✅ Retrained successfully." if success else "⚠️ Retrain failed."
 
-# ✅ UI
-with gr.Blocks(title="EvoTransformer v2.1") as demo:
-    gr.Markdown("### 🧠 EvoTransformer v2.1 – Compare Options and Learn")
+with gr.Blocks(css=".gradio-container {font-family: 'Segoe UI'; font-size: 16px;}") as demo:
+    gr.Markdown("## 🧠 EvoTransformer v2.1 – Compare Options and Learn")
 
     with gr.Row():
-        goal = gr.Textbox(label="Goal")
+        goal = gr.Textbox(label="Goal", placeholder="e.g. Escape from house on fire")
+    
     with gr.Row():
-        sol1 = gr.Textbox(label="Option 1")
-        sol2 = gr.Textbox(label="Option 2")
-
-    output = gr.Textbox(label="Model Suggestion")
-    run_btn = gr.Button("🔍 Compare")
-    run_btn.click(fn=evo_chat, inputs=[goal, sol1, sol2], outputs=output)
+        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")
 
     with gr.Row():
-        correct = gr.Radio(["Solution 1", "Solution 2"], label="Which was better?")
-        log_btn = gr.Button("✅ Log Feedback")
-        log_btn.click(fn=log_user_feedback, inputs=[goal, sol1, sol2, correct], outputs=None)
+        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])
 
-    with gr.Accordion("📊 Dashboard", open=False):
-        display_dashboard()
+    with gr.Row():
+        winner_choice = 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])
 
-    retrain_btn = gr.Button("♻️ Retrain Evo")
-    retrain_status = gr.Textbox(label="Retrain Status")
-    retrain_btn.click(fn=retrain_model, outputs=retrain_status)
+    gr.Markdown("## 📊 Dashboard")
+    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])
 
-demo.launch()
+# 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)