Update app.py

app.py

@@ -1,134 +1,10 @@
 import streamlit as st
-import json
-import requests
-import time
-from newspaper import Article
-import nltk
-nltk.download('punkt')
 
-# Page title layout
-c1, c2 = st.columns([0.32, 2])
 
-with c1:
-     st.image("images/newspaper.png", width=85)
-
-with c2:
-    st.title("Website Article Summarize")
-st.markdown("**Generate summaries of articles from websites using abstractive summarization with Language Model and Library NewsPaper.**")
-st.caption("Created by Bayhaqy.")
-
-# Sidebar content
-st.sidebar.subheader("About the app")
-st.sidebar.info("This app uses optional 🤗HuggingFace's Model [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) \
-or [pegasus_indonesian_base-finetune](https://huggingface.co/pegasus_indonesian_base-finetune) model and Library NewsPaper.")
-st.sidebar.write("\n\n")
-st.sidebar.markdown("**Get a free API key from HuggingFace:**")
-st.sidebar.markdown("* Create a [free account](https://huggingface.co/join) or [login](https://huggingface.co/login)")
-st.sidebar.markdown("* Go to **Settings** and then **Access Tokens**")
-st.sidebar.markdown("* Create a new Token (select 'read' role)")
-st.sidebar.markdown("* Paste your API key in the text box")
-st.sidebar.divider()
-st.sidebar.write("Please make sure you choose the correct model and is not behind a paywall.")
-st.sidebar.write("\n\n")
-st.sidebar.divider()
-
-# Inputs 
-st.subheader("Enter the URL of the article you want to summarize")
-default_url = "https://"
-url = st.text_input("URL:", default_url)
-
-headers_ = {
-        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.82 Safari/537.36'
-    }
-
-fetch_button = st.button("Fetch article")
-
-if fetch_button:
-    article_url = url
-    session = requests.Session()
-
-    try:
-        response_ = session.get(article_url, headers=headers_, timeout=10)
-    
-        if response_.status_code == 200:
-
-            with st.spinner('Fetching your article...'):
-                time.sleep(3)
-                st.success('Your article is ready for summarization!')     
-
-                article = Article(url)
-                article.download()
-                article.parse()
-                
-                title = article.title
-                text = article.text
-                
-                st.divider()
-                st.subheader("Real Article")
-                st.markdown(f"Your article: **{title}**")
-                st.markdown(f"**{text}**")
-                st.divider()
-
-        else:
-            st.write("Error occurred while fetching article.")
-
-    except Exception as e:
-        st.write(f"Error occurred while fetching article: {e}")
-
-# HuggingFace API KEY input
-API_KEY = st.text_input("Enter your HuggingFace API key", type="password")
-
-headers = {"Authorization": f"Bearer {API_KEY}"}
-
-
-# Selectbox to choose between API URLs
-selected_api_url = st.selectbox("Select Model", options=["bart-large-cnn", "pegasus_indonesian_base-finetune"])
-
-# Determine the selected Model
-if selected_api_url == "bart-large-cnn":
-    API_URL = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"
-else:
-    API_URL = "https://api-inference.huggingface.co/models/thonyyy/pegasus_indonesian_base-finetune"
-
-submit_button = st.button("Submit to Summarize")
-
-# Download and parse the article
-if submit_button:
-    article = Article(url)
-    article.download()
-    article.parse()
-    article.nlp()
-    
-    title = article.title
-    text = article.text
-    html = article.html
-    summ = article.summary
-
-    # HuggingFace API request function summary
-    def query_sum(payload):
-        response = requests.post(API_URL, headers=headers, json=payload)
-        return response.json()
-
-    with st.spinner('Doing some AI magic, please wait...'):
-        time.sleep(1)
-
-        # Query the API Summary
-        output_sum = query_sum({"inputs": text, })
-
-        # Display the results
-        summary = output_sum[0]['summary_text'].replace('<n>', " ") 
-
-        st.divider()
-        st.subheader("Summary AI")
-        st.markdown(f"Your article: **{title}**")
-        st.markdown(f"**{summary}**")
-
-        st.divider()
-        st.subheader("Summary Library NewsPaper")
-        st.markdown(f"Your article: **{title}**")
-        st.markdown(f"**{summ}**")
-
-        st.divider()
-        st.subheader("Real Article")
-        st.markdown(f"Your article: **{title}**")
-        st.markdown(f"**{text}**")
+st.set_page_config(page_title='Classification - News Analysis and Prediction',  layout='wide', page_icon='📃')
+st.title("📃 Classification - News Analysis and Prediction")
+st.write(
+  """
+  Welcome to the **📃 Classification - News Analysis and Prediction App**!
+  """
+  )