Update app.py

app.py

@@ -65,10 +65,15 @@ if st.button("Sentiment Analysis", type="secondary"):
                 progress_bar.empty()
                 try:
                     wait.until(EC.presence_of_element_located((By.CSS_SELECTOR, "#contents #contents")))
-                    comments = driver.find_elements(By.CSS_SELECTOR, "#content #content-text") #Corrected CSS Selector
+                    comments = driver.find_elements(By.CSS_SELECTOR, "#content #content-text")
                     user_id = 1
                     for comment in comments:
-                        timestamp = datetime.now().strftime("%Y-%m-%d")
+                        timestamp = None
+                        try:
+                            timestamp_element = comment.find_element(By.XPATH, './ancestor::ytd-comment-renderer//yt-formatted-string[@class="published-time-text style-scope ytd-comment-renderer"]')
+                            timestamp = timestamp_element.text
+                        except Exception as e:
+                            print(f"Date not found for comment: {comment.text}. Error: {e}")
                         data.append({"User ID": user_id, "Comment": comment.text, "comment_date": timestamp})
                         user_id += 1
                     data = [dict(t) for t in {tuple(d.items()) for d in data}]
@@ -78,7 +83,7 @@ if st.button("Sentiment Analysis", type="secondary"):
                 df = pd.DataFrame(data, columns=["User ID", "Comment", "comment_date"])
                 st.dataframe(df)
 
-                if not df.empty and 'Comment' in df.columns and not df['Comment'].empty: #Added checks.
+                if not df.empty and 'Comment' in df.columns and not df['Comment'].empty:
                     inputs = tokenizer(df['Comment'].tolist(), return_tensors="pt", padding=True, truncation=True)
                     with torch.no_grad():
                         logits = model(**inputs).logits