Update app.py

app.py

@@ -5,6 +5,7 @@ from sklearn.metrics.pairwise import cosine_similarity
 import random
 from sentence_transformers import SentenceTransformer
 import gradio as gr
+import time
 
 # Load datasets
 lecturer_data = pd.read_csv('lecturers.csv', dtype={"phone_number": str}).astype(str)
@@ -160,7 +161,7 @@ def answer_doc_link_query(query):
                 return f"I'm sorry, I can't find any study smarter study set for that course."
 
     elif max_score < 1:
-        return "Sure! To assist you better, please provide the name or code of the course you are referring to."
+        return "Sure! To assist you better, please provide the name or code of the course you are referring to, along with the entire query."
 
     else:
         answer_general_query(query)
@@ -207,18 +208,19 @@ def get_response(query):
 
     return response
 
-# Function to handle Gradio interface
-def chatty(query):
-    response = get_response(query)
 
-    # Update previous query and response
-    previous_query = query
-    previous_response = response
+with gr.Blocks() as iface:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.ClearButton([msg, chatbot])
 
-    if previous_response.lower() == "Sure! To assist you better, please provide the name or code of the course you are referring to.":
-        # Append the previous query to the current one
-        query = previous_query + " " + query
-    return response
+    def respond(message, chat_history):
+        bot_message = get_response(message)
+        chat_history.append((message, bot_message))
+        time.sleep(2)
+        return "", chat_history
+
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
 
-iface = gr.Interface(chatty)
-iface.launch()
+if __name__ == "__main__":
+    iface.launch()