app.py

import gradio as gr
import pandas as pd
import gspread
from google.auth import default
import requests
import time 
import json

# Authenticate and authorize with Google Sheets
#creds, _ = default()
#gc = gspread.authorize(creds)
gc = gspread.service_account(filename='botresponse-6f1a8c749aa0.json')
    
# Specify your Google Sheets credentials, sheet_id, and worksheet_name
sheet_id = "18hnoTsEaGMWMael42MXubb-FzAe5jJB5RpaSolIXyb0"
worksheet_name = "Sheet1"

# Function to get the initial response
def get_initial_response(input_message):
    url = "https://itell-api.learlab.vanderbilt.edu/chat"

    payload = {
        "textbook_name": "think-python-2e",
        "message": input_message
    }
    headers = {"Content-Type": "application/json"}

    # Measure the start time
    start_time = time.time()

    response = requests.post(url, json=payload, headers=headers)
    data = json.loads(response.text)
    message = data['message']

    # Calculate the elapsed time
    elapsed_time = time.time() - start_time
    elapsed_time = round(elapsed_time, 2)
    response_time_message = f"Response time: {elapsed_time} seconds"

    return message, response_time_message  # Return the initial_response and elapsed_time

# Function to collect feedback and update the spreadsheet
def feedback_response(input_message, feedback, comments):
    # Get the initial response and elapsed_time
    initial_response, elapsed_time = get_initial_response(input_message)

    # Collect feedback
    response = ''
    if feedback == 'Informative':
        response = 'Informative'
    elif feedback == 'Inaccurate':
        response = 'Inaccurate'
    elif feedback == 'Nonsense':
        response = 'Nonsense'
    else:
        response = 'NA'

    # Update Google Sheets
    sh = gc.open_by_key(sheet_id)
    worksheet = sh.worksheet(worksheet_name)
    
    thankyou = "Thank you for your feedback. Your response and feedback has been recorded!"
    # Append the data to the worksheet only if comments have a value
    if comments:
        # Create a DataFrame from the response and additional comments
        df = pd.DataFrame({'Input Message': [input_message], 'Output': [initial_response], 'Time took in Seconds': [elapsed_time],'Feedback': [response], 'Additional Comments': [comments]})

        # Append the data to the worksheet
        worksheet.append_rows(df.values.tolist())
        initial_response = thankyou

    
    return initial_response, elapsed_time  # Return the initial_response and elapsed_time

# Set up the Gradio Interface
feedback_interface = gr.Interface(
    fn=feedback_response,
    inputs=[
        gr.Textbox(label="Input Message"),
        gr.Radio(
            choices=[
                "Informative",
                "Inaccurate",
                "Nonsense"
            ],
            label="Feedback"
        ),
        gr.Textbox(label="Additional Comments")
    ],
    outputs=[
        gr.Textbox(label="Output", type="text"),
        gr.Textbox(label="Elapsed Time (s)", type="text")  # Change the type to "text" for two decimal places
    ],
    title="Beta: Itell Guide Response Bot",
    description="""
    # Introduction
    This is an interface to test iTELL's guide on the side. Please be aware that responses can take up to 20 seconds

    # Step by Step Introduction
    1. Place a educational python-related question in the input message textbox
    2. Wait roughly 10 ~ 20 seconds for the response and elapsed time to come out on the right
    3. After looking at the results, click on the feedback options that best describes the output: Informative, Inaccurate, Nonsense
    4. After choosing the best option, write down additional comments for more feedback
    5. Press submit again and wait for the output to come out again for your feedback to be submitted
    6. Once the "Thank you for your feedback. Your response and feedback has been recorded!" message is shown, you are done

    ** DISCLAIMER: You have to type a input message, click on the feedback buttons, and type in additional comments for your responses to be recorded

    ** For further questions contact LEAR Labs!
    """
)

# Launch the interface
feedback_interface.launch()