{system_instruction}
""" return html_system_instruction def log_action(user_id, tab_name, action, details): """ Log actions for each tab (stock). """ log_file_dir = os.path.join(LOG_DIR, f"{user_id}") if os.path.exists(log_file_dir) is False: os.makedirs(log_file_dir) log_file = os.path.join(log_file_dir, f"{tab_name}.txt") with open(log_file, "a") as f: f.write(f"Action: {action} | Details: {details}\n") def add_user_profile_to_system_instruction( user_id, system_instruction, user_preference_elicitation_data, summary, terminator ): exp_id = int(user_id.split("_")[-3]) # exp_id = 1 => No personalization if exp_id == 1: return system_instruction if summary: if user_preference_elicitation_data["summary_history"] == "": # Format prompt summarization_prompt = SUMMARIZATION_PROMPT + "\nPrevious Conversations: {}".format( user_preference_elicitation_data["history"] ) summarization_instruction = [{"role": "system", "content": summarization_prompt}] if API_TYPE == "local": summ, _ = generate_response_local_api(summarization_instruction, terminator, 512, API_URL) elif API_TYPE == "together": summ, _ = generate_response_together_api(summarization_instruction, 512, TOGETHER_CLIENT) else: summ, _ = generate_response_debugging(summarization_instruction) user_preference_elicitation_data["summary_history"] = summ # # log_action(user_id, "Prompt", "Preference Elicitation Summarization", summ) # save_feedback( # user_id, # uuid_this_session, # "preference_elicitation_summarization", # {"summarization": summ}, # feedback_file_summarization, # ) system_instruction += f"\nUser Profile collected in the previous conversations: {user_preference_elicitation_data['summary_history']}\n" else: system_instruction += ( f"\nUser Profile collected in the previous conversations: {user_preference_elicitation_data['history']}\n" ) return system_instruction def likert_evaluation(content): return gr.Radio( [1, 2, 3, 4, 5, 6, 7], label=f"{content}", show_label=True, ) def create_demo(): global context_info_list, terminator def tab_creation_exploration_stage(order, comp, context): comp_list = [ "Eli Lilly and Company", "Johnson & Johnson", "Philip Morris International Inc", "Exxon Mobil Corporation", "Amazon.com, Inc.", "JP Morgan Chase & Co.", "Coca-Cola Company", "Walmart Inc.", "Apple Inc.", "Procter & Gamble Company", "Tesla, Inc.", "Bank of America Corporation", ] with gr.Tab(comp_list[order], id=comp): general_instruction = gr.HTML(label="General Instruction") with gr.Row(): # with gr.Column(): # with gr.Row(): # round_instruction = gr.HTML(label="Round Instruction") with gr.Column(): with gr.Row(): chatbot = gr.Chatbot(height=600) with gr.Row(): start_conversation = gr.Button(value="Start Conversation") with gr.Row(): msg = gr.Textbox(scale=2, lines=3, label="User Input", container=False) msg_button = gr.Button(value="Send This Message to Advisor", interactive=False) continue_button = gr.Button(value="Show More of the Advisor’s Answer", interactive=False) with gr.Row(): clear = gr.ClearButton([msg, chatbot]) return { "comp": comp, "system_instruction_context": context, "start_conversation": start_conversation, "msg_button": msg_button, "continue_button": continue_button, "chatbot": chatbot, "msg": msg, "general_instruction": general_instruction, # "round_instruction": round_instruction, } def tab_creation_preference_stage(): # Custom CSS to reduce padding and margin of the textbox with gr.Row(): gr.HTML(value=PREFERENCE_ELICITATION_TASK, label="Preference Elicitation Task") with gr.Row(): # with gr.Column(): # user_narrative = gr.HTML(label="User Narrative") with gr.Column(): with gr.Row(): elicitation_chatbot = gr.Chatbot(height=600) with gr.Row(): start_conversation = gr.Button(value="Start Conversation") with gr.Row(): msg = gr.Textbox(scale=2, lines=3, label="User Input", container=False) msg_button = gr.Button(value="Send This Message to Advisor", interactive=False) continue_button = gr.Button(value="Show More of the Advisor’s Answer", interactive=False) return { "start_conversation": start_conversation, "msg_button": msg_button, "continue_button": continue_button, "msg": msg, "elicitation_chatbot": elicitation_chatbot, # "user_narrative": user_narrative, } def tab_personality_injection(): gr.Markdown("## Choose Your Advisor Personality") # A radio button to choose between Optimist and Pragmatis personality_choice = gr.Radio( choices=[ "Optimist (Friendly, Daring, Confident)", "Pragmatist (Disciplined, Cautious, Practical)", "Misadvisor (Just for fun! Unreliable, Messy, Sarcastic - don't take it seriously!)", ], value="Optimist", label="Select a Personality", interactive=True, ) # An HTML element to display personality details/description personality_description = gr.HTML(value="", label="Personality Details") # A button that, when clicked, confirms the selection personality_submit = gr.Button("Apply Personality") # Return a dict with the UI components for later use return { "personality_choice": personality_choice, "personality_description": personality_description, "personality_submit": personality_submit, } def click_control_personality_injection_stage( tabs, system_description_without_context, system_description_user_elicitation ): def respond_personality(personality_choice): if personality_choice == "Optimist (Friendly, Daring, Confident)": new_sys_desc_no_ctx = SYSTEM_INSTRUCTION_PERSONALITY.format(personality=PERSONALITY_EXT) new_sys_desc_user_elicitation = SYSTEM_INSTRUCTION_PREFERENCE_ELICITATION_PERSONALITY.format( personality=PERSONALITY_EXT ) message = "Optimist advisor personality is successfully applied." elif personality_choice == "Pragmatist (Disciplined, Cautious, Practical)": new_sys_desc_no_ctx = SYSTEM_INSTRUCTION_PERSONALITY.format(personality=PERSONALITY_INT) new_sys_desc_user_elicitation = SYSTEM_INSTRUCTION_PREFERENCE_ELICITATION_PERSONALITY.format( personality=PERSONALITY_INT ) message = "Pragmatist personality is successfully applied." elif ( personality_choice == "Misadvisor (Just for fun! Unreliable, Messy, Sarcastic - don't take it seriously!)" ): new_sys_desc_no_ctx = SYSTEM_INSTRUCTION_PERSONALITY.format(personality=PERSONALITY_MISADVISOR) new_sys_desc_user_elicitation = SYSTEM_INSTRUCTION_PREFERENCE_ELICITATION_PERSONALITY.format( personality=PERSONALITY_MISADVISOR ) message = "Misadvisor personality is successfully applied." else: new_sys_desc_no_ctx = SYSTEM_INSTRUCTION_PERSONALITY.format(personality="None") new_sys_desc_user_elicitation = SYSTEM_INSTRUCTION_PREFERENCE_ELICITATION_PERSONALITY.format( personality="None" ) message = "No personality is applied." return new_sys_desc_no_ctx, new_sys_desc_user_elicitation, message # Only pass the personality_choice as input tabs["personality_submit"].click( fn=respond_personality, inputs=[tabs["personality_choice"]], outputs=[ system_description_without_context, system_description_user_elicitation, tabs["personality_description"], ], ) def click_control_exploration_stage( tabs, user_id, tab_session, user_preference_elicitation_session, system_description_without_context ): ( comp, system_instruction_context, start_conversation, msg_button, continue_button, chatbot, msg, ) = ( tabs["comp"], tabs["system_instruction_context"], tabs["start_conversation"], tabs["msg_button"], tabs["continue_button"], tabs["chatbot"], tabs["msg"], ) system_instruction = "" start_conversation.click( lambda user_id, tab_session, history, comp, user_preference_elicitation_session, system_description_without_context, system_instruction_context: respond_start_conversation( user_id, tab_session, history, system_instruction, comp, user_preference_elicitation_data=user_preference_elicitation_session, system_description_without_context=system_description_without_context, system_instruction_context=system_instruction_context, ), [ user_id, tab_session, chatbot, comp, user_preference_elicitation_session, system_description_without_context, system_instruction_context, ], [tab_session, chatbot, start_conversation, msg_button, continue_button], ) msg_button.click( lambda user_id, tab_session, message, history, comp, user_preference_elicitation_session, system_description_without_context, system_instruction_context: respond( user_id, tab_session, message, tab_session["history"], system_instruction, comp, user_preference_elicitation_data=user_preference_elicitation_session, system_description_without_context=system_description_without_context, system_instruction_context=system_instruction_context, ), [ user_id, tab_session, msg, chatbot, comp, user_preference_elicitation_session, system_description_without_context, system_instruction_context, ], [tab_session, msg, chatbot], ) continue_button.click( lambda user_id, tab_session, history, comp, user_preference_elicitation_session, system_description_without_context, system_instruction_context: respond_continue( user_id, tab_session, tab_session["history"], system_instruction, comp, user_preference_elicitation_data=user_preference_elicitation_session, system_description_without_context=system_description_without_context, system_instruction_context=system_instruction_context, ), [ user_id, tab_session, chatbot, comp, user_preference_elicitation_session, system_description_without_context, system_instruction_context, ], [tab_session, chatbot], ) def click_control_preference_stage( tabs, user_id, user_preference_elicitation_session, system_description_user_elicitation ): ( start_conversation, msg_button, continue_button, elicitation_chatbot, msg, ) = ( tabs["start_conversation"], tabs["msg_button"], tabs["continue_button"], tabs["elicitation_chatbot"], tabs["msg"], ) # nonlocal user_id start_conversation.click( lambda user_id, user_preference_elicitation_data, history, system_description_user_elicitation: respond_start_conversation( user_id, user_preference_elicitation_data, history, system_description_user_elicitation, user_elicitation=True, ), [user_id, user_preference_elicitation_session, elicitation_chatbot, system_description_user_elicitation], [user_preference_elicitation_session, elicitation_chatbot, start_conversation, msg_button, continue_button], ) msg_button.click( lambda user_id, tab_data, message, history, system_description_user_elicitation: respond( user_id, tab_data, message, tab_data["history"], system_description_user_elicitation, user_elicitation=True, ), [ user_id, user_preference_elicitation_session, msg, elicitation_chatbot, system_description_user_elicitation, ], [user_preference_elicitation_session, msg, elicitation_chatbot], ) continue_button.click( lambda user_id, tab_data, history, system_description_user_elicitation: respond_continue( user_id, tab_data, tab_data["history"], system_description_user_elicitation, user_elicitation=True, ), [user_id, user_preference_elicitation_session, elicitation_chatbot, system_description_user_elicitation], [user_preference_elicitation_session, elicitation_chatbot], ) def respond( user_id, tab_data, message, history, system_instruction, tab_name=None, user_elicitation=False, user_preference_elicitation_data=None, system_description_without_context=None, system_instruction_context=None, ): """ Return: msg chat_history retrieved_passage rewritten_query """ assert ( tab_name is not None or user_elicitation is True ), "Tab name is required for the start of the conversation unless it is not preference elicitation." # Add user profile to system instruction if system_description_without_context is not None and system_instruction_context is not None: system_instruction = system_description_without_context + "\n" + system_instruction_context if not user_elicitation: system_instruction = add_user_profile_to_system_instruction( user_id, system_instruction, user_preference_elicitation_data, summary=USER_PREFERENCE_SUMMARY, terminator=terminator, ) # From string to list [{"role":"user", "content": message}, ...] history = gradio_to_huggingface_message(history) # We can implement context window here as we need all the system interaction. We can cut some of the early interactions if needed. history = conversation_window(history, CONV_WINDOW) # Add system instruction to the history history = format_context(system_instruction, history) # Add user message to the history history_with_user_utterance = format_user_message(message, history) # Call API instead of locally handle it if API_TYPE == "local": outputs_text, history = generate_response_local_api(history_with_user_utterance, terminator, 128, API_URL) elif API_TYPE == "together": outputs_text, history = generate_response_together_api(history_with_user_utterance, 128, TOGETHER_CLIENT) else: outputs_text, history = generate_response_debugging(history_with_user_utterance) # exclude system interaction and store the others in the history history = huggingface_to_gradio_message(history) if tab_name is not None: # Log the user message and response # save_feedback( # user_id, # uuid_this_session, # "interaction", # {"type": tab_name, "role": "user", "content": message}, # feedback_file_interaction, # ) # save_feedback( # user_id, # uuid_this_session, # "interaction", # {"type": tab_name, "role": "assistant", "content": outputs_text}, # feedback_file_interaction, # ) # log_action(user_id, tab_name, "User Message", message) # log_action(user_id, tab_name, "Response", outputs_text) # Store the updated history for this tab tab_data["history"] = history if user_elicitation: # save_feedback( # user_id, # uuid_this_session, # "Interaction", # {"type": "user_elicitation", "role": "user", "content": message}, # feedback_file_interaction, # ) # save_feedback( # user_id, # uuid_this_session, # "Interaction", # {"type": "user_elicitation", "role": "assistant", "content": outputs_text}, # feedback_file_interaction, # ) # log_action(user_id, "User_Elicitation", "User Message", message) # log_action(user_id, "User_Elicitation", "Response", outputs_text) tab_data["history"] = history return tab_data, "", history def respond_start_conversation( user_id, tab_data, history, system_instruction, tab_name=None, user_elicitation=False, user_preference_elicitation_data=None, system_description_without_context=None, system_instruction_context=None, ): assert ( tab_name is not None or user_elicitation is True ), "Tab name is required for the start of the conversation unless it is not preference elicitation." if system_description_without_context is not None and system_instruction_context is not None: system_instruction = system_description_without_context + "\n" + system_instruction_context if not user_elicitation: system_instruction = add_user_profile_to_system_instruction( user_id, system_instruction, user_preference_elicitation_data, summary=USER_PREFERENCE_SUMMARY, terminator=terminator, ) history = gradio_to_huggingface_message(history) history = format_context(system_instruction, history) first_message = FIRST_MESSAGE history_with_user_utterance = format_user_message(first_message, history) max_length = 128 if user_elicitation else 256 if API_TYPE == "local": outputs_text, history = generate_response_local_api( history_with_user_utterance, terminator, max_length, API_URL ) elif API_TYPE == "together": outputs_text, history = generate_response_together_api( history_with_user_utterance, max_length, TOGETHER_CLIENT ) else: outputs_text, history = generate_response_debugging(history_with_user_utterance) # Format history = huggingface_to_gradio_message(history) if tab_name is not None: # Log the user message and response # save_feedback( # user_id, # uuid_this_session, # "interaction", # {"type": tab_name, "role": "user", "content": first_message}, # feedback_file_interaction, # ) # save_feedback( # user_id, # uuid_this_session, # "interaction", # {"type": tab_name, "role": "assistant", "content": outputs_text}, # feedback_file_interaction, # ) tab_data["history"] = history if user_elicitation: # save_feedback( # user_id, # uuid_this_session, # "interaction", # {"type": "user_elicitation", "role": "user", "content": first_message}, # feedback_file_interaction, # ) # save_feedback( # user_id, # uuid_this_session, # "Interaction", # {"type": "user_elicitation", "role": "assistant", "content": outputs_text}, # feedback_file_interaction, # ) tab_data["history"] = history return ( tab_data, history, gr.Button(value="Start Conversation", interactive=False), gr.Button(value="Send This Message to Advisor", interactive=True), gr.Button(value="Show More of the Advisor’s Answer", interactive=True), ) def respond_continue( user_id, tab_data, history, system_instruction, tab_name=None, user_elicitation=False, user_preference_elicitation_data=None, system_description_without_context=None, system_instruction_context=None, ): assert ( tab_name is not None or user_elicitation is True ), "Tab name is required for the start of the conversation." # Add user profile to system instruction if system_description_without_context is not None and system_instruction_context is not None: system_instruction = system_description_without_context + "\n" + system_instruction_context if not user_elicitation: system_instruction = add_user_profile_to_system_instruction( user_id, system_instruction, user_preference_elicitation_data, summary=USER_PREFERENCE_SUMMARY, terminator=terminator, ) message = "continue" history = gradio_to_huggingface_message(history) history = conversation_window(history, CONV_WINDOW) history = format_context(system_instruction, history) history_with_user_utterance = format_user_message(message, history) if API_TYPE == "local": outputs_text, history = generate_response_local_api(history_with_user_utterance, terminator, 128, API_URL) elif API_TYPE == "together": outputs_text, history = generate_response_together_api(history_with_user_utterance, 128, TOGETHER_CLIENT) else: outputs_text, history = generate_response_debugging(history_with_user_utterance) history = huggingface_to_gradio_message(history) if tab_name is not None: # save_feedback( # user_id, # uuid_this_session, # "interaction", # { # "type": tab_name, # "role": "user", # "content": message, # }, # feedback_file_interaction, # ) # save_feedback( # user_id, # uuid_this_session, # "interaction", # {"type": tab_name, "role": "assistant", "content": outputs_text}, # feedback_file_interaction, # ) # Update history for this tab tab_data["history"] = history if user_elicitation: # save_feedback( # user_id, # uuid_this_session, # "interaction", # {"type": "user_elicitation", "role": "user", "content": message}, # feedback_file_interaction, # ) # save_feedback( # user_id, # uuid_this_session, # "interaction", # {"type": "user_elicitation", "role": "assistant", "content": outputs_text}, # feedback_file_interaction, # ) tab_data["history"] = history return tab_data, history def get_context(index, raw_context_list, stock_context_list): comp = raw_context_list[index]["short_name"] context = stock_context_list[index] general_instruction, round_instruction = get_task_instruction_for_user(raw_context_list[index]) return comp, context, general_instruction, round_instruction def set_user_id(request: gr.Request): # DEBUG user_id = "user_2_0_0" # user_id = request.username user_in_narrative_id = user_id.split("_")[-1] narrative_id = user_id.split("_")[-2] experiment_id = user_id.split("_")[-3] return user_id, user_in_narrative_id, narrative_id, experiment_id def get_inst_without_context(experiment_id): # experiment_id = 1 => personalization # experiment_id = 2 => no personalization # experiment_id == 3 => ext personality # experiment_id == 4 => int personality if experiment_id == "0": return SYSTEM_INSTRUCTION_PERSONALIZATION elif experiment_id == "1": return SYSTEM_INSTRUCTION_NON_PERSONALIZATION elif experiment_id == "2": return SYSTEM_INSTRUCTION_PERSONALITY.format(personality=PERSONALITY_EXT) elif experiment_id == "3": return SYSTEM_INSTRUCTION_PERSONALITY.format(personality=PERSONALITY_INT) def get_user_preference_elicitation(experiment_id): if experiment_id == "0" or experiment_id == "1": return SYSTEM_INSTRUCTION_PREFERENCE_ELICITATION elif experiment_id == "2": return SYSTEM_INSTRUCTION_PREFERENCE_ELICITATION_PERSONALITY.format(personality=PERSONALITY_EXT) elif experiment_id == "3": return SYSTEM_INSTRUCTION_PREFERENCE_ELICITATION_PERSONALITY.format(personality=PERSONALITY_INT) def get_stock_related_context(narrative_id, user_in_narrative_id): raw_context_list = build_raw_context_list(context_info_list[int(narrative_id)]) stock_context_list = build_context(context_info_list[int(narrative_id)]) return raw_context_list, stock_context_list def set_initial_values(request: gr.Request): # Set user specific information (Session State) user_id, user_in_narrative_id, narrative_id, experiment_id = set_user_id(request) user_id = "user_2_0_0" user_in_narrative_id = "0" experiment_id = "2" system_description_without_context = get_inst_without_context(experiment_id) system_description_user_elicitation = get_user_preference_elicitation(experiment_id) first_raw_context_list, first_stock_context_list = get_stock_related_context(0, user_in_narrative_id) second_raw_context_list, second_stock_context_list = get_stock_related_context(1, user_in_narrative_id) third_raw_context_list, third_stock_context_list = get_stock_related_context(2, user_in_narrative_id) raw_context_list = first_raw_context_list + second_raw_context_list + third_raw_context_list stock_context_list = first_stock_context_list + second_stock_context_list + third_stock_context_list # Tab Context first_comp, first_context, first_general_instruction, first_round_instruction = get_context( 0, raw_context_list, stock_context_list ) second_comp, second_context, second_general_instruction, second_round_instruction = get_context( 1, raw_context_list, stock_context_list ) third_comp, third_context, third_general_instruction, third_round_instruction = get_context( 2, raw_context_list, stock_context_list ) fourth_comp, fourth_context, fourth_general_instruction, fourth_round_instruction = get_context( 3, raw_context_list, stock_context_list ) fifth_comp, fifth_context, fifth_general_instruction, fifth_round_instruction = get_context( 4, raw_context_list, stock_context_list ) sixth_comp, sixth_context, sixth_general_instruction, sixth_round_instruction = get_context( 5, raw_context_list, stock_context_list ) seventh_comp, seventh_context, seventh_general_instruction, seventh_round_instruction = get_context( 6, raw_context_list, stock_context_list ) eighth_comp, eighth_context, eighth_general_instruction, eighth_round_instruction = get_context( 7, raw_context_list, stock_context_list ) ninth_comp, ninth_context, ninth_general_instruction, ninth_round_instruction = get_context( 8, raw_context_list, stock_context_list ) tenth_comp, tenth_context, tenth_general_instruction, tenth_round_instruction = get_context( 9, raw_context_list, stock_context_list ) eleventh_comp, eleventh_context, eleventh_general_instruction, eleventh_round_instruction = get_context( 10, raw_context_list, stock_context_list ) twelfth_comp, twelfth_context, twelfth_general_instruction, twelfth_round_instruction = get_context( 11, raw_context_list, stock_context_list ) return ( user_id, user_in_narrative_id, narrative_id, experiment_id, system_description_without_context, system_description_user_elicitation, raw_context_list, stock_context_list, # user_narrative, first_comp, first_context, first_general_instruction, # first_round_instruction, second_comp, second_context, second_general_instruction, # second_round_instruction, third_comp, third_context, third_general_instruction, # third_round_instruction, fourth_comp, fourth_context, fourth_general_instruction, # fourth_round_instruction, fifth_comp, fifth_context, fifth_general_instruction, # fifth_round_instruction, sixth_comp, sixth_context, sixth_general_instruction, # sixth_round_instruction, seventh_comp, seventh_context, seventh_general_instruction, # seventh_round_instruction, eighth_comp, eighth_context, eighth_general_instruction, # eighth_round_instruction, ninth_comp, ninth_context, ninth_general_instruction, # ninth_round_instruction, tenth_comp, tenth_context, tenth_general_instruction, # tenth_round_instruction, eleventh_comp, eleventh_context, eleventh_general_instruction, # eleventh_round_instruction, twelfth_comp, twelfth_context, twelfth_general_instruction, # twelfth_round_instruction, ) with gr.Blocks(title="RAG Chatbot Q&A", theme="Soft") as demo: # Set user specific information (Session State) user_id = gr.State() user_in_narrative_id = gr.State() narrative_id = gr.State() experiment_id = gr.State() system_description_without_context = gr.State() system_description_user_elicitation = gr.State() # Context data raw_context_list = gr.State() stock_context_list = gr.State() first_comp = gr.State() first_context = gr.State() second_comp = gr.State() second_context = gr.State() third_comp = gr.State() third_context = gr.State() fourth_comp = gr.State() fourth_context = gr.State() fifth_comp = gr.State() fifth_context = gr.State() sixth_comp = gr.State() sixth_context = gr.State() seventh_comp = gr.State() seventh_context = gr.State() eighth_comp = gr.State() eighth_context = gr.State() ninth_comp = gr.State() ninth_context = gr.State() tenth_comp = gr.State() tenth_context = gr.State() eleventh_comp = gr.State() eleventh_context = gr.State() twelfth_comp = gr.State() twelfth_context = gr.State() # Tab data if DEBUG: user_preference_elicitation_session = gr.State( value={ "history": "", "summary_history": """User Profile collected in the previous conversations: Based on our previous conversation, here's a summary of your investment preferences: # 1. **Preferred Industries:** You're interested in investing in the healthcare sector, without a specific preference for sub-industries such as pharmaceuticals, medical devices, biotechnology, or healthcare services. # 2. **Value vs. Growth Stocks:** You prefer growth stocks, which have the potential for high returns but may be riskier. # 3. **Dividend vs. Non-Dividend Stocks:** You're open to both dividend and non-dividend growth stocks, focusing on reinvesting profits for future growth. # 4. **Cyclical vs. Non-Cyclical Stocks:** You're interested in cyclical stocks, which are sensitive to economic fluctuations and tend to perform well during economic expansions.""", } ) else: user_preference_elicitation_session = gr.State(value={"history": "", "summary_history": ""}) first_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) second_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) third_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) fourth_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) fifth_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) sixth_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) seventh_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) eighth_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) ninth_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) tenth_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) eleventh_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) twelfth_comp_session = gr.State(value={"history": [], "selection": "", "reason": ""}) # Demonstration Instruction with gr.Tab("Demonstration Instruction") as instruction_tab: gr.HTML(value=INSTRUCTION_PAGE, label="Demonstration Instruction") # User Preference Elicitation Tab with gr.Tab("Personality Injection") as personality_injection_tab: personality_injection_tab = tab_personality_injection() click_control_personality_injection_stage( personality_injection_tab, system_description_without_context, system_description_user_elicitation ) with gr.Tab("User Preference Elicitation") as preference_elicitation_tab: user_preference_elicitation_tab = tab_creation_preference_stage() # user_narrative = user_preference_elicitation_tab["user_narrative"] click_control_preference_stage( user_preference_elicitation_tab, user_id, user_preference_elicitation_session, system_description_user_elicitation, ) with gr.Tab("Personalized Stock Assessment") as financial_decision: # Experiment Tag first_tab = tab_creation_exploration_stage(0, first_comp, first_context) click_control_exploration_stage( first_tab, user_id, first_comp_session, user_preference_elicitation_session, system_description_without_context, ) second_tab = tab_creation_exploration_stage(1, second_comp, second_context) click_control_exploration_stage( second_tab, user_id, second_comp_session, user_preference_elicitation_session, system_description_without_context, ) third_tab = tab_creation_exploration_stage(2, third_comp, third_context) click_control_exploration_stage( third_tab, user_id, third_comp_session, user_preference_elicitation_session, system_description_without_context, ) fourth_tab = tab_creation_exploration_stage(3, fourth_comp, fourth_context) click_control_exploration_stage( fourth_tab, user_id, fourth_comp_session, user_preference_elicitation_session, system_description_without_context, ) fifth_tab = tab_creation_exploration_stage(4, fifth_comp, fifth_context) click_control_exploration_stage( fifth_tab, user_id, fifth_comp_session, user_preference_elicitation_session, system_description_without_context, ) sixth_tab = tab_creation_exploration_stage(5, sixth_comp, sixth_context) click_control_exploration_stage( sixth_tab, user_id, sixth_comp_session, user_preference_elicitation_session, system_description_without_context, ) seventh_tab = tab_creation_exploration_stage(6, seventh_comp, seventh_context) click_control_exploration_stage( seventh_tab, user_id, seventh_comp_session, user_preference_elicitation_session, system_description_without_context, ) eighth_tab = tab_creation_exploration_stage(7, eighth_comp, eighth_context) click_control_exploration_stage( eighth_tab, user_id, eighth_comp_session, user_preference_elicitation_session, system_description_without_context, ) ninth_tab = tab_creation_exploration_stage(8, ninth_comp, ninth_context) click_control_exploration_stage( ninth_tab, user_id, ninth_comp_session, user_preference_elicitation_session, system_description_without_context, ) tenth_tab = tab_creation_exploration_stage(9, tenth_comp, tenth_context) click_control_exploration_stage( tenth_tab, user_id, tenth_comp_session, user_preference_elicitation_session, system_description_without_context, ) eleventh_tab = tab_creation_exploration_stage(10, eleventh_comp, eleventh_context) click_control_exploration_stage( eleventh_tab, user_id, eleventh_comp_session, user_preference_elicitation_session, system_description_without_context, ) twelfth_tab = tab_creation_exploration_stage(11, twelfth_comp, twelfth_context) click_control_exploration_stage( twelfth_tab, user_id, twelfth_comp_session, user_preference_elicitation_session, system_description_without_context, ) ( first_general_instruction, second_general_instruction, third_general_instruction, fourth_general_instruction, fifth_general_instruction, sixth_general_instruction, seventh_general_instruction, eighth_general_instruction, ninth_general_instruction, tenth_general_instruction, eleventh_general_instruction, twelfth_general_instruction, ) = ( first_tab["general_instruction"], second_tab["general_instruction"], third_tab["general_instruction"], fourth_tab["general_instruction"], fifth_tab["general_instruction"], sixth_tab["general_instruction"], seventh_tab["general_instruction"], eighth_tab["general_instruction"], ninth_tab["general_instruction"], tenth_tab["general_instruction"], eleventh_tab["general_instruction"], twelfth_tab["general_instruction"], ) demo.load( set_initial_values, inputs=None, outputs=[ user_id, user_in_narrative_id, narrative_id, experiment_id, system_description_without_context, system_description_user_elicitation, raw_context_list, stock_context_list, # user_narrative, first_comp, first_context, first_general_instruction, # first_round_instruction, second_comp, second_context, second_general_instruction, # second_round_instruction, third_comp, third_context, third_general_instruction, # third_round_instruction, fourth_comp, fourth_context, fourth_general_instruction, # fourth_round_instruction, fifth_comp, fifth_context, fifth_general_instruction, # fifth_round_instruction, sixth_comp, sixth_context, sixth_general_instruction, # sixth_round_instruction, seventh_comp, seventh_context, seventh_general_instruction, # seventh_round_instruction, eighth_comp, eighth_context, eighth_general_instruction, # eighth_round_instruction, ninth_comp, ninth_context, ninth_general_instruction, # ninth_round_instruction, tenth_comp, tenth_context, tenth_general_instruction, # tenth_round_instruction, eleventh_comp, eleventh_context, eleventh_general_instruction, # eleventh_round_instruction, twelfth_comp, twelfth_context, twelfth_general_instruction, # twelfth_round_instruction, ], ) return demo if __name__ == "__main__": file_path = os.path.join(ROOT_FILE, "./data/single_stock_data/experiment_processed_data.jsonl") topics = [ "healthcare_growth_defensive", "dividend_value_defensive", "nondividend_value_cyclical", ] context_info_list = get_context_list(file_path) # str to List of Dict # system instruction consist of Task, Personality, and Context """ Personality ["extroverted", "introverted"] ["agreeable", "antagonistic"] ["conscientious", "unconscientious"] ["neurotic", "emotionally stable"] ["open to experience", "closed to experience"]] """ # Global variables terminator = ["