app.py

import gradio as gr
import re
import string
import pickle

# Load trained model and vectorizer
with open("svm_model.pkl", "rb") as model_file:
    svm_model = pickle.load(model_file)

with open("vectorizer.pkl", "rb") as vectorizer_file:
    vectorizer = pickle.load(vectorizer_file)

# Preprocessing function
def preprocess_text(text):
    text = text.lower()
    text = re.sub(f"[{string.punctuation}]", "", text)  # Remove punctuation
    text = re.sub(r"\d+", "", text)  # Remove numbers
    return text

# Function to predict news authenticity
def predict_news(news_text):
    processed_text = preprocess_text(news_text)
    text_tfidf = vectorizer.transform([processed_text])
    prediction = svm_model.predict(text_tfidf)
    return "Real" if prediction[0] == 1 else "Fake"

# Gradio UI
iface = gr.Interface(
    fn=predict_news,
    inputs=gr.Textbox(lines=5, placeholder="Enter news here..."),
    outputs="text",
    title="Fake News Detection",
    description="Enter a news article and check if it's real or fake."
)

iface.launch()