app.py

import gradio as gr
from transformers import pipeline
import pandas as pd

# Load dataset
DATASET_PATH = "spam.csv"
df = pd.read_csv(DATASET_PATH, encoding="latin1")

# Load a spam classification model
classifier = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-sms-spam-detection")

def spam_detector(text):
    result = classifier(text)
    return "Spam" if result[0]['label'].lower() == "Spam" else "Not Spam"

# Create Gradio UI
app = gr.Interface(
    fn=spam_detector,
    inputs=gr.Textbox(label="Enter a message"),
    outputs=gr.Textbox(label="Prediction"),
    title="Spam Detector",
    description="Enter a message to check if it's spam or not."
)

# Run the app
if __name__ == "__main__":
    print("Loaded dataset preview:")
    print(df.head())
    app.launch()