Update app.py

app.py

@@ -42,7 +42,12 @@ def initialize_chat(initial_question):
     chat_history = [(None, initial_question)]
     response, follow_up_questions, token_info = generate_response(initial_question, 0)
     chat_history.append((None, response))
-    return chat_history, follow_up_questions, token_info
+    
+    # Extract follow-up questions as examples
+    follow_up_questions_formatted = [q.strip() for q in follow_up_questions.split('\n') if q.strip()]
+    examples_state = [[q] for q in follow_up_questions_formatted]
+    
+    return chat_history, follow_up_questions, token_info, examples_state
 
 def generate_response(prompt, token_count=0):
     print(f"Received prompt: {prompt}")
@@ -160,15 +165,18 @@ css = """
 
 # Initialize the chat history and suggested questionsw
 # Initialize the chat history and suggested questions
-chat_history, follow_up_questions, initial_token_info = initialize_chat("I'm 14 years old female and want to become a graphic designer. I'm living in Uttar Pradesh in India. How can I start?")
+#chat_history, follow_up_questions, initial_token_info = initialize_chat("I'm 14 years old female and want to become a graphic designer. I'm living in Uttar Pradesh in India. How can I start?")
 
 
 # Initial example questions from the initialization
-formatted_questions = [q.strip() for q in follow_up_questions.split('\n')[:3]]
-initial_examples = [[q] for q in formatted_questions]
+
 
 with gr.Blocks(css=css) as demo:
-    examples_state = gr.State(initial_examples)
+    examples_state = gr.State([])
+    chat_history = gr.State([])
+    token_info = gr.State("")
+    follow_up_questions_md = gr.State("")
+    
     with gr.Row():
         with gr.Column(scale=1):
             gr.Markdown(
@@ -177,22 +185,24 @@ with gr.Blocks(css=css) as demo:
                 In the realm of digital communication, the development of an advanced chatbot that incorporates topic modeling represents a significant leap towards enhancing user interaction and maintaining focus during conversations. This innovative chatbot design is specifically engineered to streamline discussions by guiding users to select from a curated list of suggested questions. This approach is crafted to mitigate the risk of diverging into off-topic dialogues, which are common pitfalls in conventional chatbot systems.
                 """
             )
-            token_info = gr.Markdown(
-                value=initial_token_info,
+            token_info_display = gr.Markdown(
+                value="",
                 elem_id="token-info"
             )
-            follow_up_questions_md = gr.Markdown(
-                value=follow_up_questions,
+            follow_up_questions_display = gr.Markdown(
+                value="",
                 elem_id="follow-up-questions",
-                label="Follow up Quiestions"
+                label="Follow up Questions"
             )
             initial_question_input = gr.Textbox(
                 placeholder="Type your initial question here...", 
                 label="Initial Question"
             )
+            initialize_button = gr.Button("Initialize Chat")
+        
         with gr.Column(scale=1, elem_id="chat-container"):
             chatbot = gr.Chatbot(
-                value=chat_history,
+                value=[],
                 elem_id="chatbot",
                 bubble_full_width=False,
                 label="Safe Chatbot v1"
@@ -204,22 +214,23 @@ with gr.Blocks(css=css) as demo:
 
                 btn.click(
                     fn=process_response,
-                    inputs=[txt, gr.State(chat_history), gr.State(initial_examples), gr.State(examples_state.value)],
-                    outputs=[chatbot, token_info, follow_up_questions_md, examples_state]
-
+                    inputs=[txt, chat_history, gr.State(0), examples_state],
+                    outputs=[chatbot, token_info_display, follow_up_questions_display, examples_state]
                 )
                 examples_component = gr.Examples(
-                examples=examples_state.value,
-                inputs=[txt],
-                label="Questions"
-            )
-            initial_question_input.submit(
-                fn=initialize_chat,
-                inputs=[initial_question_input],
-                outputs=[chatbot, follow_up_questions_md, token_info]
-            )
+                    examples=examples_state.value,
+                    inputs=[txt],
+                    label="Questions"
+                )
             
             chatbot.like(print_like_dislike, None, None)
 
+    initialize_button.click(
+        fn=initialize_chat,
+        inputs=[initial_question_input],
+        outputs=[chat_history, follow_up_questions_display, token_info_display, examples_state]
+    )
+    chatbot.set(chat_history)
+
 if __name__ == "__main__":
     demo.launch(share=False)