Update app.py

app.py

@@ -1,3 +1,58 @@
 import gradio as gr
+import logging
+import gradio as gr
+from queue import Queue
+import time
+
+
+gr.load("models/Sevixdd/roberta-base-finetuned-ner").launch()
+
+# --- Logging Setup ---
+logging.basicConfig(filename="chat_log.txt", level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+# --- Queue and Metrics ---
+chat_queue = Queue()
+response_times = []
+
+# --- Chat Function ---
+def chat_function(message, history):
+    try:
+        start_time = time.time()  # Record start time for metrics
+        chat_queue.put(message)  # Add message to queue
+        logging.info(f"User: {message}")
+    
+        # ... (Your chatbot processing logic here) ...
+        # Simulate processing delay
+        time.sleep(2)  # Replace with actual processing
+        response = chat_queue.get()
+        logging.info(f"Bot: {response}")
+
+        # --- Metrics Calculation ---
+        end_time = time.time()
+        response_time = end_time - start_time
+        response_times.append(response_time)
+        avg_response_time = sum(response_times) / len(response_times) if response_times else 0
+
+        logging.info(f"Response Time: {response_time:.2f} seconds, Avg: {avg_response_time:.2f} seconds")
+        return response
+    except Exception as e:
+        logging.error(f"Error in chat processing: {e}")
+        return "An error occurred. Please try again."
+
+# --- Gradio Interface ---
+with gr.Blocks() as demo:
+    gr.Markdown("## Chat with the Bot")
+    chatbot = gr.ChatInterface(fn=chat_function)
+
+demo.launch()
+
+# --- Additional Monitoring (Optional) ---
+def monitor_queue():
+    while True:
+        queue_size = chat_queue.qsize()
+        logging.info(f"Queue Size: {queue_size}")
+        time.sleep(60)  # Check every 60 seconds
 
-gr.load("models/Sevixdd/roberta-base-finetuned-ner").launch()
+# Uncomment to enable queue monitoring
+# import threading
+# threading.Thread(target=monitor_queue, daemon=True).start()