app.py

import gradio as gr
from utils import *
from save_data import add_new_data, get_sheet_service
from instructions import *
from constants import SDG_DETAILS, GPT_PROMPT_parallel, GPT_PROMPT_sequential, GPT_PROMPT_reverse_sequential

class SessionManager:
    def __init__(self):
        self.sessions = []

    def add_session(self, cooperate_style, task):
        if cooperate_style == "sequential":
            session = {
                "user_identification_code": None,
                "task": task,
                "cooperate_style": cooperate_style,
                "human_initial_answer": None,
                "ai_modificated_output": None,
                "evaluation": None
            }
        elif cooperate_style == "reverse_sequential":
            session = {
                "user_identification_code": None,
                "task": task,
                "cooperate_style": cooperate_style,
                "ai_initial_answer": None,
                "human_modifications": None,
                "final_answer": None,
                "evaluation": None
            }
        elif cooperate_style == "parallel":
            session = {                
                "user_identification_code": None,
                "task": task,
                "cooperate_style": cooperate_style,
                "ai_initial_answer": None,
                "human_initial_answer": None,
                "merged_final_answer": None,
                "evaluation": None
            }
        self.sessions.append(session)
        return len(self.sessions) - 1

    def update(self, index, output_content, key='final_output'):
        self.sessions[index][key] = output_content

    def get_session(self, index):
        return self.sessions[index]

    def save_session_to_sheet(self, index, service, SHEET_ID):
        session = self.sessions[index]
        new_row = list(session.values())
        add_new_data(new_row, service, SHEET_ID, num_of_columns=len(new_row))  # 动态列数



def handle_create_sequential(task, human_input, session_manager, api_key, identification_code):
    cooperate_style = "sequential"
    session_index = session_manager.add_session(task=task, cooperate_style=cooperate_style)
    session_manager.update(session_index, human_input, 'human_initial_answer')
    output = merge_texts_sequential(task, human_input, api_key)
    session_manager.update(session_index, output, 'ai_modificated_output')
    session_manager.update(session_index, identification_code, 'user_identification_code')
    return output, session_index


def handle_create_parallel(task, human_input, session_manager, api_key, identification_code):
    cooperate_style = "parallel"
    session_index = session_manager.add_session(task=task, cooperate_style=cooperate_style)
    ai_initial_answer = generate_ai_initial_answer(task, api_key)
    session_manager.update(session_index, human_input, 'human_initial_answer')
    session_manager.update(session_index, ai_initial_answer, 'ai_initial_answer')
    final_answer = merge_texts_parallel(task, human_input, ai_initial_answer, api_key)
    session_manager.update(session_index, final_answer, 'merged_final_answer')
    session_manager.update(session_index, identification_code, 'user_identification_code')
    return ai_initial_answer, final_answer, session_index

def handle_create_reverse_sequential(task, session_manager, api_key, identification_code):
    cooperate_style = "reverse_sequential"
    session_index = session_manager.add_session(task=task, cooperate_style=cooperate_style)
    ai_initial_answer = generate_ai_initial_answer(task, api_key)
    session_manager.update(session_index, ai_initial_answer, 'ai_initial_answer')
    session_manager.update(session_index, identification_code, 'user_identification_code')
    return ai_initial_answer, session_index


def handle_modify_reverse_sequential(session_index, modification_suggestions, session_manager, api_key):
    session = session_manager.get_session(session_index)
    session_manager.update(session_index, modification_suggestions, 'human_modifications')
    final_answer = modify_with_suggestion(session['task'], modification_suggestions, api_key)
    session_manager.update(session_index, final_answer, 'final_answer')
    return final_answer, session_index



def evaluate_interaction(session_index, session_manager, api_key):
    session = session_manager.get_session(session_index)
    if session['cooperate_style'] == "sequential":
        evaluation = get_evaluation_with_gpt(session['task'], session['ai_modificated_output'], api_key)
    elif session['cooperate_style'] == "reverse_sequential":
        evaluation = get_evaluation_with_gpt(session['task'], session['final_answer'], api_key)
    elif session['cooperate_style'] == "parallel":
        evaluation = get_evaluation_with_gpt(session['task'], session['merged_final_answer'], api_key)
    session['evaluation'] = evaluation
    return evaluation

def save_data(session_index, session_manager, service, SHEET_ID):
    session_manager.save_session_to_sheet(session_index, service, SHEET_ID)
    return "Data has been saved to Google Sheets."

def login(identification_code):
    groups = ["A", "B", "C"]
    if not identification_code:
        return update_content(None)
    
    user_group_id = int(identification_code)//1000 
    if user_group_id in range(3):
        return update_content(groups[user_group_id])
    else:
        return update_content(None)


if __name__ == "__main__":
    api_key = get_api_key(local=False)
    service, SHEET_IDs = get_sheet_service(local=False)
    SHEET_ID1, SHEET_ID2, SHEET_ID3 = SHEET_IDs

    session_manager = SessionManager()

    with gr.Blocks() as app:
        with gr.Row():
            identification_code = gr.Textbox(label="Enter your identification code")
            login_button = gr.Button("Login")
        login_status = gr.Textbox(label="Next Tasks", interactive=False)
        group = gr.State()

        with gr.Column(visible=False) as task:
            description = gr.Textbox(label="Task Description", 
                            value = default_task_discription(), 
                            lines=10)
        
            with gr.Accordion(label = "17 Sustainable Development Goals", 
                              open=False):
                gr.Markdown(SDG_DETAILS)
        # initialization of different group contents
        group_a_content = gr.Group(visible=False)
        group_b_content = gr.Group(visible=False)
        group_c_content = gr.Group(visible=False)

        
        
        
        def update_content(group):
            if group == "A":
                return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), group_a_instructions()
            elif group == "B":
                return gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), group_b_instructions()
            elif group == "C":
                return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), group_c_instructions()
            else:
                return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), invalid_group()

        login_button.click(login, inputs=identification_code, outputs=[task, group_a_content, group_b_content, group_c_content, login_status])
        
        
        
        with group_a_content:
            with gr.Row():
                human_input = gr.Textbox(label="Human Input")
            with gr.Row():
                submit_btn = gr.Button("Create")
            with gr.Row():
                ai_output = gr.Textbox(label="AI modified output")
                session_index = gr.Number(label="Session Index", visible=False)

            submit_btn.click(
                fn=lambda task, human_input, id: handle_create_sequential(task, human_input, session_manager, api_key, id),
                inputs=[task, human_input, identification_code],
                outputs=[ai_output, session_index]
            )

            # evaluate same for every group
            evaluate_btn = gr.Button("Evaluate")
            evaluation_result = gr.Textbox(label="Evaluation Result")

            evaluate_btn.click(
                fn=lambda session_index: evaluate_interaction(session_index, session_manager, api_key),
                inputs=[session_index],
                outputs=[evaluation_result]
            )

            save_btn = gr.Button("Save Data")
            save_result = gr.Label()

            save_btn.click(
                fn=lambda session_index: save_data(session_index, session_manager, service, SHEET_ID1),
                inputs=[session_index],
                outputs=[save_result]
            )
            
            with gr.Accordion(label="Appendix: AI instructions", open=False):
                gr.Markdown(GPT_PROMPT_sequential)

        with group_b_content:
            with gr.Row():
                human_input = gr.Textbox(label="Human Input")
            with gr.Row():
                create_btn = gr.Button("Create")
            with gr.Row(): 
                ai_initial_output = gr.Textbox(label="AI Initial Output")
                final_output = gr.Textbox(label="Final Merged Output")
                session_index = gr.Number(label="Session Index", visible=False)

            create_btn.click(
                fn=lambda task, human_input, id: handle_create_parallel(task, human_input, session_manager, api_key, id),
                inputs=[task, human_input, identification_code],
                outputs=[ai_initial_output, final_output, session_index]
            )


            evaluate_btn = gr.Button("Evaluate")
            evaluation_result = gr.Textbox(label="Evaluation Result")

            evaluate_btn.click(
                fn=lambda session_index: evaluate_interaction(session_index, session_manager, api_key),
                inputs=[session_index],
                outputs=[evaluation_result]
            )

            save_btn = gr.Button("Save Data")
            save_result = gr.Label()

            save_btn.click(
                fn=lambda session_index: save_data(session_index, session_manager, service, SHEET_ID2),
                inputs=[session_index],
                outputs=[save_result]
            )

            with gr.Accordion(label="Appendix: AI instructions", open=False):
                gr.Markdown(GPT_PROMPT_parallel)

        with group_c_content:
            with gr.Row():
                create_initial_btn = gr.Button("Create")
            with gr.Row():
                initial_answer = gr.Textbox(label="AI Initial Answer")
                modification_suggestions = gr.Textbox(label="Modification Suggestions")
            with gr.Row():
                create_final_btn = gr.Button("Modify")
            with gr.Row():
                final_answer = gr.Textbox(label="Final Answer")
                session_index = gr.Number(label="Session Index", visible=False)
            

            create_initial_btn.click(
                fn=lambda task, id: handle_create_reverse_sequential(task, session_manager, api_key, id),
                inputs=[task, identification_code],
                outputs=[initial_answer, session_index]
            )

            create_final_btn.click(
                fn=lambda session_index, modification_suggestions: handle_modify_reverse_sequential(session_index, modification_suggestions, session_manager, api_key),
                inputs=[session_index, modification_suggestions],
                outputs=[final_answer, session_index]
            )

            evaluate_btn = gr.Button("Evaluate")
            evaluation_result = gr.Textbox(label="Evaluation Result")

            evaluate_btn.click(
                fn=lambda session_index: evaluate_interaction(session_index, session_manager, api_key),
                inputs=[session_index],
                outputs=[evaluation_result]
            )

            save_btn = gr.Button("Save Data")
            save_result = gr.Label()

            save_btn.click(
                fn=lambda session_index: save_data(session_index, session_manager, service, SHEET_ID3),
                inputs=[session_index],
                outputs=[save_result]
            )

            with gr.Accordion(label="Appendix: AI instructions", open=False):
                gr.Markdown(GPT_PROMPT_reverse_sequential)

        app.launch(share=True)