Update app.py

app.py

@@ -11,11 +11,17 @@ from sklearn.metrics import precision_score, recall_score, f1_score
 import requests
 from datasets import load_dataset
 
+# --- Logging Setup ---
+logging.basicConfig(filename="chat_log.txt", level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
+logging.debug("Logging setup complete.")
+
 # Load the model
 ner_pipeline = pipeline("ner", model="Sevixdd/roberta-base-finetuned-ner")
+logging.debug("NER pipeline loaded.")
 
 # Load the dataset
 dataset = load_dataset("surrey-nlp/PLOD-filtered")
+logging.debug("Dataset loaded.")
 
 # --- Prometheus Metrics Setup ---
 REQUEST_COUNT = Counter('gradio_request_count', 'Total number of requests')
@@ -25,9 +31,7 @@ RESPONSE_SIZE = Histogram('gradio_response_size_bytes', 'Size of responses in by
 CPU_USAGE = Gauge('system_cpu_usage_percent', 'System CPU usage in percent')
 MEM_USAGE = Gauge('system_memory_usage_percent', 'System memory usage in percent')
 QUEUE_LENGTH = Gauge('chat_queue_length', 'Length of the chat queue')
-
-# --- Logging Setup ---
-logging.basicConfig(filename="chat_log.txt", level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
+logging.debug("Prometheus metrics setup complete.")
 
 # --- Queue and Metrics ---
 chat_queue = Queue()  # Define chat_queue globally
@@ -89,7 +93,7 @@ def chat_function(index):
             return full_response
         except Exception as e:
             ERROR_COUNT.inc()
-            logging.error(f"Error in chat processing: {e}")
+            logging.error(f"Error in chat processing: {e}", exc_info=True)
             return f"An error occurred. Please try again. Error: {e}"
 
 # Function to simulate stress test