Update app.py

app.py

@@ -2,23 +2,23 @@ import streamlit as st
 import transformers
 import torch
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from predict_function import detect_fake_news
 
 # Load the model and tokenizer
 model_name = AutoModelForSequenceClassification.from_pretrained("ikoghoemmanuell/finetuned_fake_news_roberta")
 tokenizer_name = AutoTokenizer.from_pretrained("ikoghoemmanuell/finetuned_fake_news_roberta")
 
-# Define the function for detecting fake news
-@st.cache_resource
-def detect_fake_news(text):
-    # Load the pipeline.
-    pipeline = transformers.pipeline("text-classification", model=model_name, tokenizer=tokenizer_name)
+# # Set Page Configurations
+# st.set_page_config(page_title="Fake News Detection App", page_icon="fas fa-exclamation-triangle", layout="wide", initial_sidebar_state="auto")
 
-    # Predict the sentiment.
-    prediction = pipeline(text)
-    sentiment = prediction[0]["label"]
-    score = prediction[0]["score"]
+# # Loading GIF
+# gif_url = "https://raw.githubusercontent.com/Gilbert-B/Forecasting-Sales/main/app/salesgif.gif"
+
+# # Set up sidebar
+# st.sidebar.header('Navigation')
+# menu = ['Home', 'About']
+# choice = st.sidebar.selectbox("Select an option", menu)
 
-    return sentiment, score
 
 # Setting the page configurations
 st.set_page_config(