Update app.py

app.py

@@ -1,98 +1,62 @@
 import gradio as gr
 from inference import get_evo_response, get_gpt_response
-import csv
 import os
+from logger import log_feedback
 
 LOG_PATH = "feedback_log.csv"
-if LOG_PATH:
-    os.makedirs(os.path.dirname(LOG_PATH) or ".", exist_ok=True)
-    if not os.path.exists(LOG_PATH):
-        with open(LOG_PATH, "w", newline="") as f:
-            writer = csv.writer(f)
-            writer.writerow(["question", "context", "evo_answer", "gpt_answer", "feedback"])
+os.makedirs(os.path.dirname(LOG_PATH), exist_ok=True) if os.path.dirname(LOG_PATH) else None
 
-history = []
-
-def run_advisors(query, options_input, context_input):
-    options = [opt.strip() for opt in options_input.strip().split("\n") if opt.strip()]
-    if len(options) != 2:
-        return "Please enter exactly two options (one per line).", "", "", "", "", history
-
-    evo_ans, reasoning, confidence, evo_context = get_evo_response(query, options, context_input)
-    gpt_ans = get_gpt_response(query, context_input)
-
-    entry = {
-        "Question": query,
-        "Context": context_input,
-        "Options": options,
-        "Evo Answer": evo_ans,
-        "Evo Score": reasoning,
-        "Confidence": f"{confidence:.2f}",
-        "Context Used": evo_context,
-        "GPT Answer": gpt_ans
-    }
-
-    history.insert(0, entry)
+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 (
-        f"✅ Answer: **{evo_ans}**  (Confidence: {confidence:.2f})",
+        evo_answer,
         reasoning,
-        evo_context,
-        gpt_ans,
-        "",  # feedback placeholder
-        history
+        f"Context used by Evo:\n{evo_context}",
+        gpt_answer
     )
 
-def log_feedback(feedback, question, context, evo_answer, gpt_answer):
-    with open(LOG_PATH, "a", newline="") as f:
-        writer = csv.writer(f)
-        writer.writerow([question, context, evo_answer, gpt_answer, feedback])
-    return "✅ Feedback submitted."
-
-def render_history(history):
-    if not history:
-        return "No previous questions."
-    html = ""
-    for h in history[:5]:
-        html += f"<b>Q:</b> {h['Question']}<br>"
-        html += f"<b>Options:</b> {', '.join(h['Options'])}<br>"
-        html += f"<b>Evo:</b> {h['Evo Answer']} ({h['Evo Score']})<br>"
-        html += f"<b>GPT:</b> {h['GPT Answer']}<br><hr>"
-    return html
+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")
-    gr.Markdown("Ask any question and compare Evo’s evolved reasoning with GPT-3.5. Evo uses online context + live evolution.")
 
     with gr.Row():
-        query = gr.Textbox(label="📝 Ask anything", placeholder="e.g. Who is the president of France?")
-        options_input = gr.Textbox(lines=2, label="🧠 Options (2 lines)", placeholder="Option 1\nOption 2")
-    context_input = gr.Textbox(lines=2, label="📂 Optional Context or Notes", placeholder="Paste extra info or leave blank")
-
-    run_btn = gr.Button("🔍 Run Advisors")
-
-    evo_output = gr.Markdown()
-    reasoning_output = gr.Textbox(label="📊 Evo Reasoning")
-    evo_context = gr.Textbox(label="🌐 Web Context Used", lines=4)
-
-    gpt_output = gr.Textbox(label="🤖 GPT-3.5 Suggestion")
-
-    with gr.Row():
-        feedback_radio = gr.Radio(["👍 Helpful", "👎 Not Helpful"], label="Was Evo’s answer useful?")
-        submit_btn = gr.Button("📬 Submit Feedback")
-
-    feedback_status = gr.Markdown()
-    history_display = gr.HTML(label="📜 Recent History")
+        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(
-        run_advisors,
-        inputs=[query, options_input, context_input],
-        outputs=[evo_output, reasoning_output, evo_context, gpt_output, feedback_radio, history_display]
+        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(
-        log_feedback,
-        inputs=[feedback_radio, query, context_input, evo_output, gpt_output],
-        outputs=feedback_status
+        fn=feedback_submit,
+        inputs=[query, user_context, evo_out, feedback],
+        outputs=[feedback_result]
     )
 
 demo.launch()