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

st.markdown(f"""
    <style>
        /* Set the background image for the entire app */
        .stApp {{
            background-color: #BA944E;
            background-size: 100px;
            background-repeat:no;
            background-attachment: auto;
            background-position:full;
        }}
    </style>
    """, unsafe_allow_html=True)
    

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 the result
if st.button("Submit"):
    try:
        # Get prediction from the model
        prediction = model.predict(label)[0]

        # Define messages and colors
        review_status = {
            1: ("✅ It is a Good Review!", "#32CD32"),  # Green
            0: ("❌ It is a Bad Review!", "#FF4500")   # Red-Orange
        }

        # Get message and color based on prediction
        message, color = review_status.get(prediction, ("❓ Unknown Prediction", "#808080"))

        # Display styled result
        st.markdown(f"""
            <div style="
                padding: 15px; 
                background-color: {color}; 
                border-radius: 10px; 
                text-align: center; 
                font-size: 18px; 
                font-weight: bold; 
                color: white;">
                {message}
            </div>
        """, unsafe_allow_html=True)

    except Exception as e:
        st.error(f"⚠️ Error in prediction: {e}")

    st.write("")