Update app.py

app.py

@@ -1,6 +1,5 @@
 import os
 import glob
-import math
 from typing import List, Tuple
 
 import gradio as gr
@@ -179,26 +178,15 @@ def build_answer(query: str) -> str:
 
 
 def chat_respond(message: str, history):
-    answer = build_answer(message)
-
-    # Normalize history into the format ChatInterface expects
-    normalized = []
-
-    if isinstance(history, list):
-        for item in history:
-            if isinstance(item, dict):
-                normalized.append(item)
-            elif isinstance(item, tuple) and len(item) == 2:
-                normalized.append({"role": "user", "content": item[0]})
-                normalized.append({"role": "assistant", "content": item[1]})
-
-    # Append new messages
-    normalized.append({"role": "user", "content": message})
-    normalized.append({"role": "assistant", "content": answer})
-
-    # MUST return: (string_answer, list_of_dict_messages)
-    return answer, normalized
+    """
+    Gradio ChatInterface (type='messages') calls this with:
+      - message: latest user message (str)
+      - history: list of previous messages (handled internally by Gradio)
 
+    We only need to return the assistant's reply as a string.
+    """
+    answer = build_answer(message)
+    return answer
 
 
 # -----------------------------
@@ -207,7 +195,6 @@ def chat_respond(message: str, history):
 
 description = """
 Ask questions as if you were talking to a knowledge base assistant.
-
 In a real scenario, this assistant would be connected to your own
 help center or internal documentation. Here, it's using a small demo
 knowledge base to show how retrieval-based self-service can work.
@@ -217,21 +204,15 @@ chat = gr.ChatInterface(
     fn=chat_respond,
     title="Self-Service KB Assistant",
     description=description,
-    chatbot=gr.Chatbot(
-        height=420,
-        show_copy_button=True,
-        type="messages"
-    ),
+    type="messages",  # use new-style message format
     examples=[
         "What makes a good knowledge base article?",
         "How could a KB assistant help agents?",
         "Why is self-service important for customer support?",
     ],
-    cache_examples=False,   
+    cache_examples=False,  # avoid example pre-caching issues on HF Spaces
 )
 
 
 if __name__ == "__main__":
-    # On Hugging Face Spaces, you don't need to specify server_name/port,
-    # but it's harmless if you do.
     chat.launch()