Update app.py

app.py

@@ -1,6 +1,6 @@
 # app.py
 
-import gradio as gr
+'''import gradio as gr
 import pandas as pd
 from inference import (
     evo_chat_predict,
@@ -111,3 +111,130 @@ with gr.Blocks(title="🧠 Evo – Reasoning AI") as demo:
 
 if __name__ == "__main__":
     demo.launch()
+'''
+
+# app.py
+
+import gradio as gr
+import pandas as pd
+import os
+import csv
+
+from inference import (
+    evo_chat_predict,
+    get_gpt_response,
+    get_model_config,
+    get_system_stats,
+    retrain_from_feedback_csv,
+    load_model,
+)
+
+FEEDBACK_LOG = "feedback_log.csv"
+GENOME_LOG = "genome_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
+    if not os.path.exists(FEEDBACK_LOG):
+        with open(FEEDBACK_LOG, "w", encoding="utf-8", newline="") as f:
+            writer = csv.writer(f)
+            writer.writerow(["question", "option1", "option2", "evo_answer", "confidence", "reasoning", "context", "vote"])
+
+    row = {
+        "question": question.strip(),
+        "option1": option1.strip(),
+        "option2": option2.strip(),
+        "evo_answer": result["answer"],
+        "confidence": result["confidence"],
+        "reasoning": result["reasoning"],
+        "context": result["context_used"],
+        "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)
+
+    stats = get_model_config()
+    sys_stats = get_system_stats()
+
+    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()
+
+
+# 🔁 Manual retrain button
+def retrain_evo():
+    msg = retrain_from_feedback_csv()
+    load_model(force_reload=True)
+    return msg
+
+# 📤 Export feedback
+def export_feedback():
+    if not os.path.exists(FEEDBACK_LOG):
+        return pd.DataFrame()
+    return pd.read_csv(FEEDBACK_LOG)
+
+# 🧹 Clear
+def clear_all():
+    return "", "", "", "", [], None, pd.DataFrame()
+
+# 🏆 Load top genomes
+def get_top_genomes(n=5):
+    if os.path.exists(GENOME_LOG):
+        df = pd.read_csv(GENOME_LOG)
+        df = df.sort_values(by="score", ascending=False).head(n)
+        return df.reset_index(drop=True)
+    else:
+        return pd.DataFrame()
+
+# 🖼️ UI
+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.")
+
+    with gr.Row():
+        question = gr.Textbox(label="🧠 Your Question", placeholder="e.g. Why is the sky blue?")
+    with gr.Row():
+        option1 = gr.Textbox(label="❌ Option 1")
+        option2 = gr.Textbox(label="❌ Option 2")
+
+    with gr.Row():
+        with gr.Column():
+            evo_ans = gr.Textbox(label="🧠 Evo", lines=6)
+        with gr.Column():
+            gpt_ans = gr.Textbox(label="🤖 GPT-3.5", lines=6)
+
+    with gr.Row():
+        stats = gr.Textbox(label="📊 Evo Stats")
+        system = gr.Textbox(label="🔵 Status")
+
+    evo_radio = gr.Radio(["Evo", "GPT"], label="🧠 Who was better?", info="Optional – fuels evolution")
+    history = gr.State([])
+
+    with gr.Row():
+        ask_btn = gr.Button("⚡ Ask Evo")
+        retrain_btn = gr.Button("🔁 Retrain Evo")
+        clear_btn = gr.Button("🧹 Clear")
+        export_btn = gr.Button("📤 Export Feedback CSV")
+
+    export_table = gr.Dataframe(label="📜 Conversation History")
+    genome_table = gr.Dataframe(label="🏆 Hall of Fame – 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])
+    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])
+    export_btn.click(fn=export_feedback, inputs=[], outputs=[export_table])
+
+if __name__ == "__main__":
+    demo.launch()