I'm trying to store the user inputs in a gsheet file through my Streamlit webapp but getting this error

Here’s the code

import nltk
import toml
# GSheets lib
from streamlit_gsheets import GSheetsConnection

import streamlit as st
import pickle
import string
import pandas as pd
from pandas import *


from nltk import *
from nltk.corpus import *
from string import *

# Establishing Google sheets connection

conn = st.connection("gsheets", type=GSheetsConnection )



# fetching exist data ue cols = no of cols , ttl = time to live
existing_data = conn.read(worksheet="User Data", usecols=list(range(2)), ttl=5)

existing_data = existing_data.dropna(how="all")  # droping empty vals

st.dataframe(existing_data)




nltk.download('stopwords')
nltk.download('punkt')

ps = PorterStemmer()


def transform_text(text):
    text = text.lower()
    text = nltk.word_tokenize(text)
    y = []
    # Removing Special Characters ; text is a array now
    for i in text:
        if i.isalnum():
            y.append(i)

    # copying values of y to text and emptying y
    text = y[:]
    y.clear()

    # Removing stop words & punctutations
    for i in text:
        if i not in stopwords.words('english') and i not in string.punctuation:
            y.append(i)

    text = y[:]
    y.clear()

    for i in text:
        y.append(ps.stem(i))

    return " ".join(y)


# rb - read

tfidf = pickle.load(open('vectorizer.pkl', 'rb'))
model = pickle.load(open('model.pkl', 'rb'))

st.title("Email/Sms Classifier")
input_sms = st.text_area("Enter the message")  # takes input message

prediction = ""

# If button is pressed
if st.button('Predict'):

    if not input_sms:
        st.warning("Write a message first .")
        st.stop()

    # 1 pre-process

    transformed_sms = transform_text(input_sms)

    # 2 vectorizevector input
    vector_input = tfidf.transform([transformed_sms])

    # 3 predict - extracting 0th item since spam are in 1 , 0
    result = model.predict(vector_input)[0]

    # 4 Display
    if result == 1:
        st.header("Spam")
        prediction = "Spam"

    else:
        st.header("Not spam")
        prediction = "Not spam"

    input_data = pd.DataFrame(
        [
            {
                "Input Sentence": input_sms,
                "Output": prediction
            }
        ]
    )
    #add inputdata to existing data
    updated_df= pd.concat([existing_data,input_data],ignore_index=True)

    #update goggle sheets
    conn.update(worksheet="User Data",data = updated_df)



theme_bg_color = st.get_option("theme.backgroundColor")

# Footer
st.markdown(f"""
    <style>
        .footer {{
            position: fixed;
            bottom: 0;
            left: 0;
            width: 100%;
            background-color: {theme_bg_color};
            text-align: center;
            padding: 10px;
        }}
    </style>
    <div class="footer">
        <p style="font-size: 16px;">Created by Suvroneel Nathak</p>
    </div>
""", unsafe_allow_html=True)


I also have my secrets.toml in my .streamlit folder
any help?