Update app.py

app.py

@@ -113,6 +113,7 @@ if __name__ == "__main__":
     demo.launch()
 '''
 
+# app.py
 # app.py
 
 import gradio as gr
@@ -129,15 +130,15 @@ from inference import (
     load_model,
 )
 
-FEEDBACK_LOG = "feedback_log.csv"
 GENOME_LOG = "genome_log.csv"
+FEEDBACK_LOG = "feedback_log.csv"
 
 # 🧠 Ask Evo
 def ask_evo(question, option1, option2, history, user_vote):
     options = [option1.strip(), option2.strip()]
     result = evo_chat_predict(history, question.strip(), options)
 
-    # Create feedback_log.csv with headers if it doesn't exist
+    # Create feedback_log.csv if it doesn't exist
     if not os.path.exists(FEEDBACK_LOG):
         with open(FEEDBACK_LOG, "w", encoding="utf-8", newline="") as f:
             writer = csv.writer(f)
@@ -154,12 +155,10 @@ def ask_evo(question, option1, option2, history, user_vote):
         "vote": user_vote.strip() if user_vote else ""
     }
 
-    # Log feedback
     with open(FEEDBACK_LOG, "a", newline='', encoding="utf-8") as f:
         writer = csv.DictWriter(f, fieldnames=row.keys())
         writer.writerow(row)
 
-    # Prepare outputs
     evo_output = f"Answer: {row['evo_answer']} (Confidence: {row['confidence']})\n\nReasoning: {row['reasoning']}\n\nContext used: {row['context']}"
     gpt_output = get_gpt_response(question)
     history.append(row)
@@ -170,8 +169,20 @@ def ask_evo(question, option1, option2, history, user_vote):
     stats_text = f"Layers: {stats.get('num_layers', '?')} | Heads: {stats.get('num_heads', '?')} | FFN: {stats.get('ffn_dim', '?')} | Memory: {stats.get('memory_enabled', '?')} | Accuracy: {stats.get('accuracy', '?')}"
     sys_text = f"Device: {sys_stats['device']} | CPU: {sys_stats['cpu_usage_percent']}% | RAM: {sys_stats['memory_used_gb']}GB / {sys_stats['memory_total_gb']}GB | GPU: {sys_stats['gpu_name']} ({sys_stats['gpu_memory_used_gb']}GB / {sys_stats['gpu_memory_total_gb']}GB)"
 
-    return evo_output, gpt_output, stats_text, sys_text, history, get_top_genomes()
+    genome_df = get_top_genomes()
+    return evo_output, gpt_output, stats_text, sys_text, history, genome_df
 
+# 📊 Top genome stats
+def get_top_genomes(n=5):
+    if not os.path.exists(GENOME_LOG):
+        return pd.DataFrame()
+    try:
+        df = pd.read_csv(GENOME_LOG)
+        if "score" in df.columns:
+            df = df.sort_values(by="score", ascending=False)
+        return df.tail(n)
+    except Exception:
+        return pd.DataFrame()
 
 # 🔁 Manual retrain button
 def retrain_evo():
@@ -185,28 +196,13 @@ def export_feedback():
         return pd.DataFrame()
     return pd.read_csv(FEEDBACK_LOG)
 
-# 🧹 Clear
+# 🧹 Clear UI
 def clear_all():
-    return "", "", "", "", [], None, pd.DataFrame()
+    return "", "", "", "", "", "", pd.DataFrame(), {}, pd.DataFrame()
 
-# 🏆 Load top genomes
-def get_top_genomes(n=5):
-    if os.path.exists(GENOME_LOG):
-        df = pd.read_csv(GENOME_LOG)
-
-        # 🛡 Check if 'score' column exists
-        if "score" in df.columns:
-            df = df.sort_values(by="score", ascending=False).head(n)
-            return df.reset_index(drop=True)
-        else:
-            return pd.DataFrame({"error": ["No 'score' column in genome_log.csv"]})
-    else:
-        return pd.DataFrame({"error": ["No genome_log.csv found"]})
-
-
-# 🖼️ UI
+# 🖼️ UI Layout
 with gr.Blocks(title="🧠 Evo – Reasoning AI") as demo:
-    gr.Markdown("## Why Evo? 🚀 Evo is not just another AI. It evolves. It learns from you. It adapts its architecture live based on feedback.\n\nNo retraining labs, no frozen weights. This is live reasoning meets evolution. Built to outperform, built to survive.")
+    gr.Markdown("## 🚀 Evo is not just another AI. It evolves. It learns from you. It mutates based on feedback.\n\nNo retraining labs. No frozen weights. This is live reasoning meets evolution.")
 
     with gr.Row():
         question = gr.Textbox(label="🧠 Your Question", placeholder="e.g. Why is the sky blue?")
@@ -222,9 +218,10 @@ with gr.Blocks(title="🧠 Evo – Reasoning AI") as demo:
 
     with gr.Row():
         stats = gr.Textbox(label="📊 Evo Stats")
-        system = gr.Textbox(label="🔵 Status")
+        system = gr.Textbox(label="🔵 System Status")
+
+    evo_radio = gr.Radio(["Evo", "GPT"], label="🧠 Who was better?", info="Optional – leave blank if both were wrong")
 
-    evo_radio = gr.Radio(["Evo", "GPT"], label="🧠 Who was better?", info="Optional – fuels evolution")
     history = gr.State([])
 
     with gr.Row():
@@ -234,13 +231,27 @@ with gr.Blocks(title="🧠 Evo – Reasoning AI") as demo:
         export_btn = gr.Button("📤 Export Feedback CSV")
 
     export_table = gr.Dataframe(label="📜 Conversation History")
-    genome_table = gr.Dataframe(label="🏆 Hall of Fame – Top Genomes")
+    genome_table = gr.Dataframe(label="🧬 Top Genomes")
+
+    ask_btn.click(
+        fn=ask_evo,
+        inputs=[question, option1, option2, history, evo_radio],
+        outputs=[evo_ans, gpt_ans, stats, system, history, genome_table]
+    )
 
-    ask_btn.click(fn=ask_evo, inputs=[question, option1, option2, history, evo_radio],
-                  outputs=[evo_ans, gpt_ans, stats, system, history, genome_table])
     retrain_btn.click(fn=retrain_evo, inputs=[], outputs=[stats])
-    clear_btn.click(fn=clear_all, inputs=[], outputs=[question, option1, option2, evo_ans, gpt_ans, stats, system, history, genome_table])
+
+    clear_btn.click(
+        fn=clear_all,
+        inputs=[],
+        outputs=[
+            question, option1, option2, evo_ans, gpt_ans,
+            stats, export_table, system, genome_table
+        ]
+    )
+
     export_btn.click(fn=export_feedback, inputs=[], outputs=[export_table])
 
 if __name__ == "__main__":
     demo.launch()
+