Update app.py

app.py

@@ -34,32 +34,88 @@ import torch
 
 
 
+with st.sidebar:
+    st.button("DEMO APP", type="primary")
+   
 
+    expander = st.expander("**Important notes on the YouTube Comments Sentiment Analysis App**")
+    expander.write('''
+    
+    
+    **How to Use**
+    This app works with the YouTube URL.  Paste the URL and press the 'Sentiment Analysis' button to perform sentiment analysis on your YouTube Comments.
+    
+    
+    **Usage Limits**
+    You can perform sentiment analysis on YouTube Comments up to 5 times.
+    
+    
+    **Subscription Management**
+    This demo app offers a one-day subscription, expiring after 24 hours. If you are interested in building your own YouTube Comments Sentiment Analysis Web App, we invite you to explore our NLP Web App Store on our website. You can select your desired features, place your order, and we will deliver your custom app in five business days. If you wish to delete your Account with us, please contact us at [email protected]
+    
+    
+    **Customization**
+    To change the app's background color to white or black, click the three-dot menu on the right-hand side of your app, go to Settings and then Choose app theme, colors and fonts.
+    
+    
+    **Charts**
+    Hover to interact with and download the charts.
+    
+    
+    **File Handling and Errors**
+    The pie and bar charts are based only on reviews containing text. For any errors or inquiries, please contact us at [email protected]
+   
+    
+    
+''')
 
 
-
+st.subheader("YouTube Comments Sentiment Analysis", divider = "red")
 
 tokenizer = transformers.DistilBertTokenizer.from_pretrained("tabularisai/robust-sentiment-analysis")
 model = transformers.DistilBertForSequenceClassification.from_pretrained("tabularisai/robust-sentiment-analysis")
 
+
+if 'url_count' not in st.session_state:
+    st.session_state['url_count'] = 0
+
+max_attempts = 2
+
+def update_url_count():
+    st.session_state['url_count'] += 1
+
 def clear_question():
-    st.session_state["youtube_video_url"] = ""
+    st.session_state["url"] = ""
 
-youtube_video_url = st.text_input("Enter Google Maps URL:", key="youtube_video_url")
+url = st.text_input("Enter YouTube URL:", key="url")
 st.button("Clear question", on_click=clear_question)
 
-if st.button("Scrape Reviews"):
-    options = Options()
-    options.add_argument("--headless")
-    options.add_argument("--disable-gpu")
-    options.add_argument("--no-sandbox")
-    options.add_argument("--disable-dev-shm-usage")
-    options.add_argument("--start-maximized")
-    service = Service(ChromeDriverManager(chrome_type=ChromeType.CHROMIUM).install())
-    driver = webdriver.Chrome(service=service, options=options)
-    data = []
-    wait = WebDriverWait(driver, 30) 
-    driver.get(youtube_video_url)
+if st.button("Sentiment Analysis", type="secondary"):
+    if st.session_state['url_count'] < max_attempts:
+        if url:
+            with st.spinner("Wait for it...", show_time=True):
+                options = Options()
+                options.add_argument("--headless")
+                options.add_argument("--disable-gpu")
+                options.add_argument("--no-sandbox")
+                options.add_argument("--disable-dev-shm-usage")
+                options.add_argument("--start-maximized")
+                service = Service(ChromeDriverManager(chrome_type=ChromeType.CHROMIUM).install())
+                driver = webdriver.Chrome(service=service, options=options)
+                data = []
+                wait = WebDriverWait(driver, 30)
+                driver.get(url)
+                
+                st.warning("Failed to scrape reviews.")
+                update_url_count() # Correctly indented
+        else:
+            st.warning("Please enter a URL.")
+    else:
+        st.warning(f"You have reached the maximum URL attempts ({max_attempts}).")
+
+st.write(f"URL pasted {st.session_state['url_count']} times.")
+
+
     
    
     placeholder = st.empty()  # Create an empty placeholder for dynamic text
@@ -114,7 +170,7 @@ if st.button("Scrape Reviews"):
             value_counts1 = sentiment_df['Sentiment'].value_counts().rename_axis('Sentiment').reset_index(name='count')
             final_df = value_counts1
 
-            tab1, tab2 = st.tabs(["Cat", "Dog"])
+            tab1, tab2 = st.tabs(["Pie Chart", "Bar Chart"])
             with tab1:
                 fig1 = px.pie(final_df, values='count', names='Sentiment', hover_data=['count'], labels={'count': 'count'})
                 fig1.update_traces(textposition='inside', textinfo='percent+label')
@@ -133,7 +189,7 @@ if st.button("Scrape Reviews"):
             st.download_button(
             label="Download data as CSV",
             data=csv,
-            file_name='review_analysis_result.csv',
+            file_name='Summary of the results.csv',
             mime='text/csv',
         )