Made summary button customizable

demos/virtual_ai_assistant_demo/agribot_personality.yaml

@@ -15,7 +15,8 @@ greet_the_user_prompt: >
   Welcome them to the agricultural tech assistance session and ask how you can assist them with their farming technology needs.
   Ensure the greeting is professional and friendly, appropriate for a tech support role in the agriculture industry.
 
-summarize_the_user_prompt: >
+extra_action_name: Summarize
+extra_action_prompt: >
   You are now required to summarize the user’s technology-related inquiry for further analysis.
   Strictly do not mention any personal data like age, name, contact, etc. when summarizing.
   Summarize the agriculture technology concerns or inquiries mentioned by the user, focusing only on the provided details without adding assumptions or unrelated information.

demos/virtual_ai_assistant_demo/bartender_personality.yaml

@@ -14,18 +14,19 @@ system_configuration: >
   Ask at most 3 questions, then say you are ready to take the order and suggest a drink. 
   Remember, your role is to assist customers in choosing drinks while maintaining a responsible, respectful, and fun atmosphere. 
   Your responses should encourage the customer to explore their drink preferences while remaining neutral, responsible, and in line with legal and ethical standards.
-  Drinks are free
+  Drinks are free, so don't provide prices.
 
 greet_the_user_prompt: >
   Please introduce yourself and greet the customer.
   Welcome them to the bar and ask how you can assist them with their drink order today.
   Ensure the greeting is friendly, responsible, and appropriate for a bartender setting.
 
-summarize_the_user_prompt: >
+extra_action_name: Summarize
+extra_action_prompt: >
   You are now required to summarize the customer's exact drink preferences for order processing. 
+  Summarize the drink-related preferences mentioned by the customer in this conversation, focusing only on the information explicitly provided, without adding any assumptions or suggestions unrelated to their drink order.
   Strictly do not mention any personal data like age, name, contact, or non-drink related information when summarizing.
   Politely remind the customer to enjoy their drinks responsibly and to seek assistance if they feel unwell or overindulge. 
-  Summarize the drink-related preferences mentioned by the customer in this conversation, focusing only on the information explicitly provided, without adding any assumptions or suggestions unrelated to their drink order.
 
 instructions: |
   # Leonardo: Your Friendly Virtual Bartender

demos/virtual_ai_assistant_demo/culinara_personality.yaml

@@ -14,7 +14,8 @@ greet_the_user_prompt: >
   Welcome them to the virtual kitchen and ask how you can assist them with their cooking or meal planning today.
   Ensure the greeting is friendly, creative, and appropriate for a kitchen assistant.
 
-summarize_the_user_prompt: >
+extra_action_name: Summarize
+extra_action_prompt: >
   You are now required to summarize the user’s cooking-related inquiry for further assistance.
   Strictly do not mention any personal data like age, name, contact, etc. when summarizing.
   Summarize the recipe or cooking-related preferences mentioned by the user, focusing only on the information provided without making assumptions or adding unrelated suggestions.

demos/virtual_ai_assistant_demo/healthcare_personality.yaml

@@ -19,7 +19,8 @@ system_configuration: >
 greet_the_user_prompt: >
   Please introduce yourself and greet the patient
 
-summarize_the_user_prompt: >
+extra_action_name: Summarize
+extra_action_prompt: >
   You are now required to summarize the patient's provided context and symptoms for the doctor's review.
   Strictly do not mention any personal data like age, name, gender, contact, non-health information etc. when summarizing.
   Summarize the health-related concerns mentioned by the patient in this conversation or in the provided context.

demos/virtual_ai_assistant_demo/main.py

@@ -18,8 +18,7 @@
 from llama_index.llms.openvino import OpenVINOLLM
 from openvino.runtime import opset10 as ops
 from openvino.runtime import passes
-from optimum.intel import OVModelForCausalLM, OVModelForFeatureExtraction, OVWeightQuantizationConfig, OVConfig, \
-    OVQuantizer
+from optimum.intel import OVModelForCausalLM, OVModelForFeatureExtraction, OVWeightQuantizationConfig, OVConfig, OVQuantizer
 from transformers import AutoTokenizer
 
 # Global variables initialization
@@ -191,13 +190,13 @@ def transcribe(prompt: str, conversation: List[List[str]]) -> List[List[str]]:
     return conversation
 
 
-def summarize(conversation: List) -> str:
-    conversation.append([chatbot_config["summarize_the_user_prompt"], None])
+def extra_action(conversation: List) -> str:
+    conversation.append([chatbot_config["extra_action_prompt"], None])
     for partial_summary in chat(conversation):
         yield partial_summary[-1][1]
 
 
-def create_UI(initial_message: str) -> gr.Blocks:
+def create_UI(initial_message: str, action_name: str) -> gr.Blocks:
     with gr.Blocks(title="Your Virtual AI Assistant") as demo:
         gr.Markdown(chatbot_config["instructions"])
 
@@ -210,8 +209,8 @@ def create_UI(initial_message: str) -> gr.Blocks:
                     submit_btn = gr.Button("Submit", variant="primary", interactive=False, scale=1)
                     clear_btn = gr.Button("Start over", variant="secondary", scale=1)
 
-        summarize_button = gr.Button("Summarize", variant="primary", interactive=False)
-        summary_ui = gr.Textbox(label="Summary (Click 'Summarize' to trigger)", interactive=False)
+        extra_action_button = gr.Button(action_name, variant="primary", interactive=False)
+        summary_ui = gr.Textbox(label=f"Summary (Click '{action_name}' to trigger)", interactive=False)
 
         # events
         # block submit button when no audio or text input
@@ -223,24 +222,24 @@ def create_UI(initial_message: str) -> gr.Blocks:
 
         clear_btn.click(lambda: ([[None, initial_message]], None), outputs=[chatbot_ui, summary_ui]) \
             .then(load_context, inputs=file_uploader_ui) \
-            .then(lambda: gr.Button(interactive=False), outputs=summarize_button)
+            .then(lambda: gr.Button(interactive=False), outputs=extra_action_button)
 
         # block buttons, do the transcription and conversation, clear audio, unblock buttons
         gr.on(triggers=[submit_btn.click, input_text_ui.submit], fn=lambda: gr.Button(interactive=False), outputs=submit_btn) \
-            .then(lambda: gr.Button(interactive=False), outputs=summarize_button) \
+            .then(lambda: gr.Button(interactive=False), outputs=extra_action_button) \
             .then(lambda: gr.Button(interactive=False), outputs=clear_btn) \
             .then(transcribe, inputs=[input_text_ui, chatbot_ui], outputs=chatbot_ui) \
             .then(lambda: None, outputs=input_text_ui) \
             .then(chat, chatbot_ui, chatbot_ui) \
             .then(lambda: gr.Button(interactive=True), outputs=clear_btn) \
-            .then(lambda: gr.Button(interactive=True), outputs=summarize_button)
+            .then(lambda: gr.Button(interactive=True), outputs=extra_action_button)
 
-        # block button, do the summarization, unblock button
-        summarize_button.click(lambda: gr.Button(interactive=False), outputs=summarize_button) \
+        # block button, do the action, unblock button
+        extra_action_button.click(lambda: gr.Button(interactive=False), outputs=extra_action_button) \
             .then(lambda: gr.Button(interactive=False), outputs=clear_btn) \
-            .then(summarize, inputs=chatbot_ui, outputs=summary_ui) \
+            .then(extra_action, inputs=chatbot_ui, outputs=summary_ui) \
             .then(lambda: gr.Button(interactive=True), outputs=clear_btn) \
-            .then(lambda: gr.Button(interactive=True), outputs=summarize_button)
+            .then(lambda: gr.Button(interactive=True), outputs=extra_action_button)
 
         return demo
 
@@ -256,7 +255,7 @@ def run(chat_model_name: str, embedding_model_name: str, personality_file_path:
     initial_message = generate_initial_greeting()
 
     # create user interface
-    demo = create_UI(initial_message)
+    demo = create_UI(initial_message, chatbot_config["extra_action_name"])
     # launch demo
     demo.queue().launch(share=public_interface)