Update app.py

app.py

@@ -25,7 +25,12 @@ def init_salesforce():
 # Cache Hugging Face model
 @st.cache_resource
 def init_anomaly_detector():
-    return pipeline("text-classification", model="distilbert-base-uncased", tokenizer="distilbert-base-uncased")
+    return pipeline(
+        "text-classification",
+        model="distilbert-base-uncased",
+        tokenizer="distilbert-base-uncased",
+        clean_up_tokenization_spaces=True
+    )
 
 # Initialize connections
 sf = init_salesforce()
@@ -79,11 +84,15 @@ def main():
     
     df = pd.DataFrame(data)
     df["Log_Timestamp__c"] = pd.to_datetime(df["Log_Timestamp__c"])
-    df["Anomaly"] = df["Status__c"].apply(lambda x: detect_anomalies(str(x), anomaly_detector))
+    df["Anomaly"] = df.apply(
+        lambda row: detect_anomalies(f"{row['Status__c']} Usage:{row['Usage_Count__c']}", anomaly_detector),
+        axis=1
+    )
 
     # Pagination
     page_size = 10
-    page = st.number_input("Page", min_value=1, value=1, step=1)
+    total_pages = max(1, len(df) // page_size + (1 if len(df) % page_size else 0))
+    page = st.number_input("Page", min_value=1, max_value=total_pages, value=1, step=1)
     start_idx = (page - 1) * page_size
     end_idx = start_idx + page_size
     paginated_df = df[start_idx:end_idx]