Update app.py

app.py

@@ -1,67 +1,98 @@
-import os
 import gradio as gr
-import pandas as pd
 from inference import get_evo_response, get_gpt_response
+import csv
+import os
 
 LOG_PATH = "feedback_log.csv"
-if os.path.dirname(LOG_PATH):
-    os.makedirs(os.path.dirname(LOG_PATH), exist_ok=True)
-
-def log_feedback(question, context, evo_answer, feedback):
-    df = pd.DataFrame([[question, context, evo_answer, feedback]],
-                      columns=["question", "context", "evo_answer", "feedback"])
-    if os.path.exists(LOG_PATH):
-        df.to_csv(LOG_PATH, mode="a", header=False, index=False)
-    else:
-        df.to_csv(LOG_PATH, index=False)
-
-def load_history():
+if LOG_PATH:
+    os.makedirs(os.path.dirname(LOG_PATH) or ".", exist_ok=True)
     if not os.path.exists(LOG_PATH):
-        return "No feedback yet."
-    df = pd.read_csv(LOG_PATH)
-    return df.tail(10).to_markdown(index=False)
+        with open(LOG_PATH, "w", newline="") as f:
+            writer = csv.writer(f)
+            writer.writerow(["question", "context", "evo_answer", "gpt_answer", "feedback"])
+
+history = []
 
-def advisor_interface(query, context, options_input):
+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).", "", ""
+        return "Please enter exactly two options (one per line).", "", "", "", "", history
 
-    evo_answer, evo_reasoning, evo_conf, evo_context = get_evo_response(query, options, context)
-    gpt_answer = get_gpt_response(query, context)
-    history = load_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)
     return (
-        f"### Evo Suggestion\n**Answer**: {evo_answer} (Confidence: {evo_conf:.2f})\n\n**Reasoning**: {evo_reasoning}\n\n_Context used:_\n{evo_context}",
-        f"### GPT-3.5 Suggestion\n{gpt_answer}",
+        f"✅ Answer: **{evo_ans}**  (Confidence: {confidence:.2f})",
+        reasoning,
+        evo_context,
+        gpt_ans,
+        "",  # feedback placeholder
         history
     )
 
-def feedback_interface(question, context, evo_answer, feedback):
-    log_feedback(question, context, evo_answer, feedback)
-    return "✅ Feedback logged."
+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
 
-with gr.Blocks(title="EvoRAG – General-Purpose Adaptive AI with Web Reasoning") as demo:
+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():
-        with gr.Column():
-            query = gr.Textbox(label="📝 Ask anything", placeholder="e.g. Who is the president of the US?")
-            context = gr.Textbox(label="📂 Optional Context or Notes", lines=3, placeholder="Paste extra info or leave blank")
-            options = gr.Textbox(label="🧠 Options (2 lines)", lines=2, placeholder="Option 1\nOption 2")
-            submit = gr.Button("🔍 Run Advisors")
+        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")
 
-        with gr.Column():
-            evo_output = gr.Markdown()
-            gpt_output = gr.Markdown()
+    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 = gr.Radio(["👍 Helpful", "👎 Not Helpful"], label="Was Evo’s answer useful?")
-        submit_feedback = gr.Button("📬 Submit Feedback")
-        feedback_status = gr.Textbox(interactive=False)
+        feedback_radio = gr.Radio(["👍 Helpful", "👎 Not Helpful"], label="Was Evo’s answer useful?")
+        submit_btn = gr.Button("📬 Submit Feedback")
 
-    with gr.Accordion("📜 Recent History", open=False):
-        history_display = gr.Markdown()
+    feedback_status = gr.Markdown()
+    history_display = gr.HTML(label="📜 Recent History")
 
-    submit.click(fn=advisor_interface, inputs=[query, context, options], outputs=[evo_output, gpt_output, history_display])
-    submit_feedback.click(fn=feedback_interface, inputs=[query, context, evo_output, feedback], outputs=[feedback_status])
+    run_btn.click(
+        run_advisors,
+        inputs=[query, options_input, context_input],
+        outputs=[evo_output, reasoning_output, evo_context, gpt_output, feedback_radio, history_display]
+    )
+
+    submit_btn.click(
+        log_feedback,
+        inputs=[feedback_radio, query, context_input, evo_output, gpt_output],
+        outputs=feedback_status
+    )
 
 demo.launch()