app.py

import warnings
warnings.filterwarnings("ignore")

import os, json
import gradio as gr
import pandas as pd

from backend import Backend

QUESTIONS = [
    "Animal Type",
    "Exposure Age",
    "Behavior Test",
    "Intervention 1",
    "Intervention 2",
    "Genetic Chain",
    "Issues or Challenge Resolved",
    "Innovations in Methodology",
    "Impact of Findings",
    "limitations",
    "Potential Applications",

]

with gr.Blocks(theme="dark") as demo:
    backend = Backend()
    with gr.Row():
            gr.Markdown(f'<center> <h1> <b> DAN_AI </b> </h1> </center>\

                        <center> <h4> Please follow the Instruction <a href="https://huggingface.co/spaces/oliverwang15/DAN_AI/blob/main/README.md">HERE</a> </h4> </center>')
    
    with gr.Row():
        with gr.Row():
            
            # Update
            with gr.Group():
                gr.Markdown(f'<center><h1>Input</h1></center>')
                gr.Markdown(f'<center><p>Please First Upload the File</p></center>')
                
                with gr.Group():
                    gr.Markdown(f'<center><h2>Request Online</h2></center>')
                    openai_key = gr.Textbox(
                        label='Enter your OpenAI API key here', 
                        type='password')

                    model_selection = gr.Radio(choices = ["ChatGPT", "GPT4"], label="Model Selection", info="Please select the model you want to use")

                    file = gr.File(label='Upload your .txt or .pdf file here', file_types=['.txt', '.pdf'], file_count = 'multiple')
                    btn_submit_txt_online = gr.Button(value='Submit')
                    # btn_submit_txt.style(full_width=True)

                with gr.Group():
                    gr.Markdown(f'<center><h2>Or Load Offline</h2></center>')
                    questions = gr.CheckboxGroup(choices = QUESTIONS, value = QUESTIONS, label="Questions", info="Please select the question you want to ask")
                    answer_type = gr.Radio(choices = ["ChatGPT_txt", "GPT4_txt", 'New_GPT_4_pdf', 'Exp_training', 'Exp_Group_A', 'Exp_Group_B'], label="Answer_type", info="Please select the type of answer you want to show")
                    btn_submit_txt_offline = gr.Button(value='Show Answers')
                    # btn_submit_txt.style(full_width=True)

            # Output
            with gr.Group():
                gr.Markdown(f'<center><h1>Output</h1></center>')
                gr.Markdown(f'<center><p>The answer to your question is :</p></center>')
                filename_box = gr.Textbox(label = "File")
                question_box = gr.Textbox(label='Question')
                answer_box = gr.Textbox(label='Answer')
                reference_box = gr.Textbox(label='Reference')

                
                with gr.Group():
                    gr.Markdown("<center><h4>Please select different questions</h4></center>")
                    with gr.Row():
                        btn_last_question = gr.Button(value='Last Question')
                        btn_next_question = gr.Button(value='Next Question')

                with gr.Group():
                    gr.Markdown("<center><h4>Please select different passages</h4></center>")
                    with gr.Row():
                        btn_last_passage = gr.Button(value='Last Passage')
                        btn_next_passage = gr.Button(value='Next Passage')
            
            # Correctness
            with gr.Group():
                gr.Markdown(f'<center><h1>Correct the Result</h1></center>')
                gr.Markdown(f'<center><p>Please Correct the Results</p></center>')

                with gr.Row():
                    save_results = gr.Textbox(placeholder = "Still need to click the button above to save the results", label = 'Save Results')
                with gr.Group():
                    gr.Markdown(f'<center><p>Please Choose: </p></center>')
                    answer_correct = gr.Radio(choices = ["Correct", "Incorrect"], label='Is the Generated Answer Correct?', info="Pease select whether the generated text is correct")
                    correct_answer = gr.Textbox(placeholder = "Please judge on the generated answer", label = 'Correct Answer', interactive = True)
        
                    reference_correct = gr.Radio(choices = ["Correct", "Incorrect"], label="Is the Reference Correct?", info="Pease select whether the reference is correct")
                    correct_reference = gr.Textbox(placeholder = "Please judge on the generated answer", label = 'Correct Reference', interactive = True)
                
                    btn_submit_correctness = gr.Button(value='Submit Correctness')
                    # btn_submit_correctness.style(full_width=True)
            
            # Download
            with gr.Group():
                gr.Markdown(f'<center><h1>Download</h1></center>')
                gr.Markdown(f'<center><p>Download the original LLM answers and corrected LLM answers</p></center>')
                answer_file = gr.File(label='Download original LLM answers', file_types=['.xlsx'])
                btn_download_answer = gr.Button(value='Download original LLM answers')
                # btn_download_answer.style(full_width=True)
                corrected_file = gr.File(label='Download corrected data', file_types=['.xlsx'])
                btn_download_corrected = gr.Button(value='Download corrected LLM answers')
                # btn_download_corrected.style(full_width=True)
                   
    with gr.Row():
        highlighted_text = gr.HTML(label="Highlighted Text")
        # reset = gr.Button(value='Reset')
        # reset.style(full_width=True)

    # Answer change
    answer_correct.input(
        backend.change_correct_answer,
        inputs = [answer_correct],
        outputs = [correct_answer],
    )

    reference_correct.input(
        backend.change_correct_reference,
        inputs = [reference_correct],
        outputs = [correct_reference],
    )
    
    # Submit button
    btn_submit_txt_online.click(  
            backend.process_file_online,
            inputs=[file, questions, openai_key, model_selection],
            outputs=[filename_box, question_box, answer_box, reference_box, highlighted_text, correct_answer, correct_reference],
    )

    btn_submit_txt_offline.click(
            backend.process_file_offline,
            inputs=[questions, answer_type],
            outputs=[filename_box, question_box, answer_box, reference_box, highlighted_text, correct_answer, correct_reference],
        )
    
    btn_submit_correctness.click(   # TODO
            backend.process_results,
            inputs=[answer_correct, correct_answer, reference_correct, correct_reference],
            outputs=[save_results],
        )
    
    # Switch question button
    btn_last_question.click(
        backend.process_last,
        outputs=[filename_box, question_box, answer_box, reference_box, highlighted_text, correct_answer, correct_reference, save_results, answer_correct, reference_correct],
    )

    btn_next_question.click(
            backend.process_next,
            outputs=[filename_box, question_box, answer_box, reference_box, highlighted_text, correct_answer, correct_reference, save_results, answer_correct, reference_correct],
        )
    
    # Switch passwage button
    btn_last_passage.click(
        backend.switch_last_passage,
        outputs=[filename_box, question_box, answer_box, reference_box, highlighted_text, correct_answer, correct_reference, save_results, answer_correct, reference_correct],
    )

    btn_next_passage.click(
        backend.switch_next_passage,
        outputs=[filename_box, question_box, answer_box, reference_box, highlighted_text, correct_answer, correct_reference, save_results, answer_correct, reference_correct],
    )

    # Download button
    btn_download_answer.click(
            backend.download_answer,
            outputs=[answer_file],
        )
    
    btn_download_corrected.click(
            backend.download_corrected,
            outputs=[corrected_file],
        )

demo.queue()
demo.launch(show_error=True)