Update app.py

app.py

@@ -1,66 +1,5 @@
-'''import gradio as gr
-from inference import get_evo_response, get_gpt_response
-import os
-from logger import log_feedback
-
-LOG_PATH = "feedback_log.csv"
-os.makedirs(os.path.dirname(LOG_PATH), exist_ok=True) if os.path.dirname(LOG_PATH) else None
-
-def process_inputs(query, option_1, option_2, user_context):
-    options = [option_1, option_2]
-    evo_answer, reasoning, confidence, evo_context = get_evo_response(query, options, user_context)
-    gpt_answer = get_gpt_response(query, user_context)
-    return (
-        evo_answer,
-        reasoning,
-        f"Context used by Evo:\n{evo_context}",
-        gpt_answer
-    )
-
-def feedback_submit(question, context, evo_answer, feedback):
-    log_feedback(question, context, evo_answer, feedback)
-    return "✅ Feedback submitted. Thank you!"
 
-with gr.Blocks(title="🧠 EvoRAG – General-Purpose Adaptive AI with Web Reasoning") as demo:
-    gr.Markdown("## 🧠 EvoRAG – General-Purpose Adaptive AI with Web Reasoning")
-
-    with gr.Row():
-        with gr.Column():
-            query = gr.Textbox(label="📝 Ask anything", placeholder="e.g. Who is the current president of the US?")
-            user_context = gr.Textbox(label="📂 Optional Context or Notes", placeholder="Paste extra info or leave blank")
-            option_1 = gr.Textbox(label="🔹 Option 1", placeholder="e.g. Donald Trump")
-            option_2 = gr.Textbox(label="🔸 Option 2", placeholder="e.g. Joe Biden")
-            run_btn = gr.Button("🔍 Get Answers")
-
-        with gr.Column():
-            gr.Markdown("### 🧠 EvoRAG Suggestion")
-            evo_out = gr.Textbox(label="Answer (Evo)", interactive=False)
-            evo_reason = gr.Textbox(label="Reasoning", interactive=False)
-            evo_context_used = gr.Textbox(label="Context Used", lines=4, interactive=False)
-
-            gr.Markdown("### 🤖 GPT-3.5 Suggestion")
-            gpt_out = gr.Textbox(label="Answer (GPT-3.5)", interactive=False)
-
-    run_btn.click(
-        fn=process_inputs,
-        inputs=[query, option_1, option_2, user_context],
-        outputs=[evo_out, evo_reason, evo_context_used, gpt_out]
-    )
-
-    gr.Markdown("### 🗳️ Feedback")
-    with gr.Row():
-        feedback = gr.Radio(["👍 Helpful", "👎 Not Helpful"], label="Was Evo’s answer useful?")
-    submit_btn = gr.Button("📬 Submit Feedback")
-    feedback_result = gr.Textbox(visible=False)
-
-    submit_btn.click(
-        fn=feedback_submit,
-        inputs=[query, user_context, evo_out, feedback],
-        outputs=[feedback_result]
-    )
-
-demo.launch()'''
-import gradio as gr
+'''import gradio as gr
 from inference import get_evo_response, get_gpt_response
 from logger import log_feedback
 
@@ -117,4 +56,86 @@ with gr.Blocks(theme=gr.themes.Base(), title="EvoRAG - Smarter Than GPT?") as de
         outputs=[feedback_status]
     )
 
-demo.launch()
+demo.launch()'''
+
+import gradio as gr
+import torch
+import os
+from inference import get_evo_response, get_gpt_response
+from logger import log_feedback
+
+# ⬇️ Evo Model Stats
+EVO_PARAMS = "~28M Parameters"
+EVO_HARDWARE = "Running on CPU (Colab/Space)"
+EVO_VERSION = "EvoRAG v2.2 – Adaptive Reasoning"
+
+# ⬇️ Feedback Logger Wrapper
+FEEDBACK_LOG_PATH = "feedback_log.csv"
+os.makedirs(os.path.dirname(FEEDBACK_LOG_PATH), exist_ok=True) if os.path.dirname(FEEDBACK_LOG_PATH) else None
+
+def handle_feedback(is_correct, question, option1, option2, context, evo_output):
+    feedback = "👍" if is_correct else "👎"
+    log_feedback(question, context, evo_output, feedback)
+    return "✅ Feedback recorded. Evo will learn from this." if is_correct else "✅ Feedback noted."
+
+def run_comparison(question, option1, option2, context):
+    options = [option1.strip(), option2.strip()]
+    evo_ans, evo_reason, evo_conf, evo_ctx = get_evo_response(question, options, context)
+    gpt_ans = get_gpt_response(question, context)
+
+    evo_output = f"Evo's Suggestion: ✅ {evo_ans}\n\nWhy? {evo_reason}\n\nContext Used: {evo_ctx[:400]}..."
+    gpt_output = f"GPT-3.5's Suggestion: {gpt_ans}"
+    return evo_output, gpt_output, evo_ans
+
+# ⬇️ Interface
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as demo:
+    with gr.Column():
+        gr.Markdown(f"""
+        <div style='padding: 1em; border-radius: 12px; background: linear-gradient(90deg, #f0f4ff, #eef2fa); border: 1px solid #ccc;'>
+            <h1 style='font-size: 2em; font-weight: 800;'>🧠 EvoRAG – General-Purpose Adaptive AI</h1>
+            <p><b>{EVO_VERSION}</b></p>
+            <p>Trained on reasoning tasks. Live learning from feedback. Combines architecture evolution and retrieval-augmented generation.</p>
+            <ul>
+                <li><b>Parameters:</b> {EVO_PARAMS}</li>
+                <li><b>Hardware:</b> {EVO_HARDWARE}</li>
+                <li><b>Live Feedback:</b> Logs every correction to evolve smarter.</li>
+                <li><b>Compare:</b> Evo vs GPT-3.5 on the same question.</li>
+            </ul>
+            <p style='font-style: italic; font-size: 0.9em;'>Built for ethical, explainable, and adaptive intelligence.</p>
+        </div>
+        """)
+
+    with gr.Row():
+        question = gr.Textbox(label="📝 Ask a Question", placeholder="e.g., What should you do in case of a fire?", lines=2)
+    with gr.Row():
+        option1 = gr.Textbox(label="Option A", placeholder="e.g., Hide inside")
+        option2 = gr.Textbox(label="Option B", placeholder="e.g., Run for dear life")
+    context = gr.Textbox(label="📂 Optional Context or Notes", placeholder="Paste any extra info here", lines=2)
+
+    with gr.Row():
+        evo_out = gr.Textbox(label="🧬 EvoRAG's Reasoned Answer")
+        gpt_out = gr.Textbox(label="🤖 GPT-3.5's Suggestion")
+
+    evo_choice = gr.State()
+
+    with gr.Row():
+        run_btn = gr.Button("🔍 Run Comparison")
+
+    with gr.Row():
+        feedback = gr.Radio(
+            ["👍 Evo was correct. Retrain from this.", "👎 Evo was wrong. Improve it."],
+            label="Was Evo’s answer useful?"
+        )
+        submit_feedback = gr.Button("📬 Submit Feedback")
+        feedback_output = gr.Textbox(label="Feedback Status")
+
+    run_btn.click(fn=run_comparison, inputs=[question, option1, option2, context], outputs=[evo_out, gpt_out, evo_choice])
+
+    submit_feedback.click(
+        fn=lambda fb, q, o1, o2, ctx, eo: handle_feedback(fb == "👍 Evo was correct. Retrain from this.", q, o1, o2, ctx, eo),
+        inputs=[feedback, question, option1, option2, context, evo_choice],
+        outputs=[feedback_output]
+    )
+
+demo.launch(ssr=True)
+