Update app.py

app.py

@@ -5,13 +5,14 @@ import retrain
 import pandas as pd
 import os
 
-def advisor_interface(query, context, feedback_choice):
-    evo_output, evo_reasoning = get_evo_response(query, context)
-    gpt_output = get_gpt_response(query, context)
+def advisor_interface(question, context, options_text, feedback_choice):
+    options = [opt.strip() for opt in options_text.split("\n") if opt.strip()]
+    evo_output, evo_reasoning = get_evo_response(question, context, options)
+    gpt_output = get_gpt_response(question, context, options)
 
     if feedback_choice != "No feedback":
         label = 1 if feedback_choice == "👍 Helpful" else 0
-        log_feedback(query, context, evo_output, label)
+        log_feedback(question, context, evo_output, label)
 
     return evo_reasoning, gpt_output, load_history()
 
@@ -22,32 +23,36 @@ def retrain_evo():
 def load_history():
     if os.path.exists("feedback_log.csv"):
         df = pd.read_csv("feedback_log.csv")
-        return df.tail(10).to_markdown(index=False)
+        try:
+            return df.tail(10).to_markdown(index=False)
+        except ImportError:
+            return "📜 History available, but markdown rendering failed. Install `tabulate` for full view."
     return "No history available yet."
 
 with gr.Blocks() as demo:
     gr.Markdown("## 🧠 EvoRAG – General-Purpose Adaptive AI with RAG + Web Search")
 
     with gr.Row():
-        query = gr.Textbox(label="📝 Ask anything", placeholder="e.g. What are the latest trends in AI regulation?")
-        context = gr.Textbox(label="📂 Optional Context or Notes", placeholder="Paste any relevant information or leave blank.")
-
+        question = gr.Textbox(label="📝 Ask anything", placeholder="e.g. Who is the current president of the US?")
+    with gr.Row():
+        options_text = gr.Textbox(label="🔢 Options (one per line)", placeholder="Option 1\nOption 2\nOption 3", lines=4)
     with gr.Row():
-        feedback = gr.Radio(["👍 Helpful", "👎 Not Helpful", "No feedback"], label="Was Evo’s answer useful?", value="No feedback")
+        context = gr.Textbox(label="📂 Optional Context or Notes", placeholder="Paste memo, article, or info here...", lines=4)
+
+    feedback = gr.Radio(["👍 Helpful", "👎 Not Helpful", "No feedback"], label="Was Evo’s answer useful?", value="No feedback")
 
     with gr.Row():
         evo_out = gr.Textbox(label="🔬 EvoRAG Suggestion (with reasoning)")
         gpt_out = gr.Textbox(label="🤖 GPT-3.5 Suggestion")
 
     run_button = gr.Button("Run Advisors")
-    run_button.click(fn=advisor_interface, inputs=[query, context, feedback], outputs=[evo_out, gpt_out, gr.Textbox(label="📜 Recent History")])
+    run_button.click(fn=advisor_interface, inputs=[question, context, options_text, feedback], outputs=[evo_out, gpt_out, gr.Textbox(label="📜 Recent History")])
 
     gr.Markdown("---")
     gr.Markdown("### 🔁 Retrain Evo from Feedback")
     retrain_button = gr.Button("📚 Retrain Evo")
     retrain_output = gr.Textbox(label="🛠️ Retrain Status")
     history_output = gr.Textbox(label="📜 Recent History")
-
     retrain_button.click(fn=retrain_evo, inputs=[], outputs=[retrain_output, history_output])
 
 demo.launch()