Update app.py

app.py

@@ -2,17 +2,11 @@ import streamlit as st
 import pandas as pd
 import torch
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
-import csv
 import random as r
 import gradio as gr
 
 gr.Interface.load("models/APJ23/MultiHeaded_Sentiment_Analysis_Model").launch()
 
-with open('test.csv','r') as f:
-    read = csv.reader(f)
-    data = [row for row in read]
-df = pd.DataFrame(data[1:],columns=data[0])
-tweet = df['comment_text'][r.randint(0,1000)]
 tokenizer = AutoTokenizer.from_pretrained("APJ23/MultiHeaded_Sentiment_Analysis_Model", local_files_only=True)
 model = AutoModelForSequenceClassification.from_pretrained("APJ23/MultiHeaded_Sentiment_Analysis_Model")
 
@@ -43,7 +37,7 @@ def create_table(predictions):
     return df
 
 st.title('Toxicity Prediction App')
-st.write(f'The random tweet select is {tweet}',tweet)
+tweet=st.text_input('Enter a tweet to check for toxicity')
 if st.button('Predict'):
     predicted_class_label, predicted_prob = predict_toxicity(tweet, model, tokenizer)
     prediction_text = f'Prediction: {predicted_class_label} ({predicted_prob:.2f})'