Update app.py

app.py

@@ -5,8 +5,8 @@ import retrain
 import pandas as pd
 import os
 
-def advisor_interface(query, context, file, feedback_choice):
-    evo_output, evo_reasoning = get_evo_response(query, context, file)
+def advisor_interface(query, context, feedback_choice):
+    evo_output, evo_reasoning = get_evo_response(query, context)
     gpt_output = get_gpt_response(query, context)
 
     if feedback_choice != "No feedback":
@@ -26,32 +26,28 @@ def load_history():
     return "No history available yet."
 
 with gr.Blocks() as demo:
-    gr.Markdown("## 🧠 EvoRAG – Retrieval-Augmented Adaptive AI (General Purpose)")
+    gr.Markdown("## 🧠 EvoRAG – General-Purpose Adaptive AI with RAG + Web Search")
 
     with gr.Row():
-        query = gr.Textbox(label="📝 Ask any question", placeholder="e.g. What are the effects of inflation?")
-        context = gr.Textbox(label="📂 Optional background notes or memos", placeholder="Paste policy, notes, or ideas...")
-
-    with gr.Row():
-        file = gr.File(label="📎 Upload optional file (.txt or .pdf)", file_types=[".txt", ".pdf"])
+        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.")
 
     with gr.Row():
         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)", lines=6)
-        gpt_out = gr.Textbox(label="🤖 GPT-3.5 Suggestion", lines=6)
+        evo_out = gr.Textbox(label="🔬 EvoRAG Suggestion (with reasoning)")
+        gpt_out = gr.Textbox(label="🤖 GPT-3.5 Suggestion")
 
     run_button = gr.Button("Run Advisors")
-    history_output = gr.Textbox(label="📜 Recent History")
-
-    run_button.click(fn=advisor_interface, inputs=[query, context, file, feedback], outputs=[evo_out, gpt_out, history_output])
+    run_button.click(fn=advisor_interface, inputs=[query, context, feedback], outputs=[evo_out, gpt_out, gr.Textbox(label="📜 Recent History")])
 
     gr.Markdown("---")
-    gr.Markdown("### 🔁 Retrain Evo on Feedback")
+    gr.Markdown("### 🔁 Retrain Evo from Feedback")
     retrain_button = gr.Button("📚 Retrain Evo")
-    retrain_status = gr.Textbox(label="🛠️ Retrain Status")
+    retrain_output = gr.Textbox(label="🛠️ Retrain Status")
+    history_output = gr.Textbox(label="📜 Recent History")
 
-    retrain_button.click(fn=retrain_evo, inputs=[], outputs=[retrain_status, history_output])
+    retrain_button.click(fn=retrain_evo, inputs=[], outputs=[retrain_output, history_output])
 
 demo.launch()