Update app.py

app.py

@@ -27,22 +27,23 @@ analytics_data = pd.DataFrame(columns=["Entry", "Clicks"])  # Declare as a globa
 
 def get_random_entry():
     random_row = data.sample()
+    token = random_row['token'].values[0]
     pos = random_row['pos'].values[0]
 
     if pos == "n":
-        entry_str = f"<b>POS:</b> Noun, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Gender:</b> {random_row['gender'].values[0]}, <b>Case:</b> {random_row['case'].values[0]}, <b>Number:</b> {random_row['number'].values[0]}"
+        entry_str = f"<b>Token:</b> {token}, <b>POS:</b> Noun, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Gender:</b> {random_row['gender'].values[0]}, <b>Case:</b> {random_row['case'].values[0]}, <b>Number:</b> {random_row['number'].values[0]}"
     elif pos == "adp":        
-        entry_str = f"<b>POS:</b> Preposition, <b>Lemma:</b> {random_row['lemma'].values[0]}"
+        entry_str = f"<b>Token:</b> {token}, <b>POS:</b> Preposition, <b>Lemma:</b> {random_row['lemma'].values[0]}"
     elif pos == "adi":
-        entry_str = f"<b>POS:</b> Adjective, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Gender:</b> {random_row['gender'].values[0]}, <b>Case:</b> {random_row['case'].values[0]}, <b>Number:</b> {random_row['number'].values[0]}"
+        entry_str = f"<b>Token:</b> {token}, <b>POS:</b> Adjective, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Gender:</b> {random_row['gender'].values[0]}, <b>Case:</b> {random_row['case'].values[0]}, <b>Number:</b> {random_row['number'].values[0]}"
     elif pos == "adv":
-        entry_str = f"<b>POS:</b> Adverb, <b>Lemma:</b> {random_row['lemma'].values[0]}"
+        entry_str = f"<b>Token:</b> {token}, <b>POS:</b> Adverb, <b>Lemma:</b> {random_row['lemma'].values[0]}"
     elif pos == "pron":
-        entry_str = f"<b>POS:</b> Pronoun, <b>Lemma:</b> {random_row['lemma'].values[0]}"
+        entry_str = f"<b>Token:</b> {token}, <b>POS:</b> Pronoun, <b>Lemma:</b> {random_row['lemma'].values[0]}"
     elif pos == "v":
-        entry_str = f"<b>POS:</b> Verb, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Aspect:</b> {random_row['aspect'].values[0]}, <b>Tense:</b> {random_row['tense'].values[0]}, <b>VerbForm:</b> {random_row['verbForm'].values[0]}, <b>Voice:</b> {random_row['voice'].values[0]}, <b>Mood:</b> {random_row['mood'].values[0]}"
+        entry_str = f"<b>Token:</b> {token}, <b>POS:</b> Verb, <b>Lemma:</b> {random_row['lemma'].values[0]}, <b>Aspect:</b> {random_row['aspect'].values[0]}, <b>Tense:</b> {random_row['tense'].values[0]}, <b>VerbForm:</b> {random_row['verbForm'].values[0]}, <b>Voice:</b> {random_row['voice'].values[0]}, <b>Mood:</b> {random_row['mood'].values[0]}"
     else:
-        entry_str = f"POS: {pos}, Lemma: {random_row['lemma'].values[0]},"
+        entry_str = f"<b>Token:</b> {token}, Lemma: {random_row['lemma'].values[0]},"
         if pd.notna(random_row['aspect'].values[0]):
             entry_str += f" Aspect: {random_row['aspect'].values[0]},"
         if pd.notna(random_row['tense'].values[0]):
@@ -65,6 +66,12 @@ def get_random_entry():
     # Remove the trailing comma
     entry_str = entry_str.rstrip(',')
     
+    return entry_str
+
+
+    # Remove the trailing comma
+    entry_str = entry_str.rstrip(',')
+    
 
     return entry_str