app.py

import pandas as pd
import numpy as np
import re
import streamlit as st 
import joblib
import numpy as np
import pandas as pd


html_temp = """
    <div style="background-color:black;padding:10px">
    <h2 style="color:white;text-align:center;">Chat GPT Review Prediction  </h2>
    </div>
    """
st.markdown(html_temp, unsafe_allow_html=True)

image_url="https://storage.googleapis.com/kaggle-datasets-images/6377125/10302664/91e3eb67027ab3122886b971613e7c2f/dataset-cover.jpg?t=2024-12-26-10-34-17"

st.image(image_url, use_container_width=True)



input_txt=st.text_input("Enter the Review")


# preprocess the text

def preprocess_text(text):
    text = text.lower()  
    text = re.sub(r'\d+', '', text)  
    text = re.sub(r'[^\w\s]', '', text)  
    text = re.sub(r'\s+', ' ', text)  

    return text

# loading the models
loaded_tfidf = joblib.load("tfidf_model.joblib")
model = joblib.load("chat_review_model.joblib")

# processing
if input:
    test=preprocess_text(input_txt)
    label=loaded_tfidf.transform([test])

# predict and display
if st.button("Submit"):
    predict=model.predict(label)[0]
        
    if predict==1:
        st.write("Its is a Good Review")
        
    elif predict==0:
        st.write("Its is a Bad Review")