Update app.py

app.py

@@ -1,10 +1,9 @@
-import gradio as gr
-
 import logging
 import gradio as gr
 from queue import Queue
 import time
 from prometheus_client import start_http_server, Counter, Histogram
+import threading
 
 # --- Prometheus Metrics Setup ---
 REQUEST_COUNT = Counter('gradio_request_count', 'Total number of requests')
@@ -36,16 +35,31 @@ def chat_function(message, history):
             logging.error(f"Error in chat processing: {e}")
             return "An error occurred. Please try again."
 
-# --- Gradio Interface ---
+# --- Gradio Interface with Metrics Display ---
 with gr.Blocks() as demo:
     gr.Markdown("## Chat with the Bot")
     chatbot = gr.ChatInterface(fn=chat_function)
 
-# --- Start Prometheus Metrics Server ---
-start_http_server(8000)  # Expose metrics on port 8000
+    with gr.Row():
+        request_count_display = gr.Textbox(label="Request Count")
+        avg_latency_display = gr.Textbox(label="Avg. Response Time (s)")
+
+    # --- Update Metrics Display ---
+    def update_metrics():
+        while True:
+            request_count_display.update(REQUEST_COUNT.collect()[0].samples[0].value)
+            avg_latency_display.update(round(REQUEST_LATENCY.collect()[0].samples[0].value, 2))
+            time.sleep(5)  # Update every 5 seconds
+
+    # Start the metrics server in a separate thread
+    threading.Thread(target=start_http_server, args=(8000,), daemon=True).start()
+    demo.load(update_metrics, None, None, every=1)  # Call update_metrics every second after initial page load
+
+demo.launch(share=True)  # For Hugging Face Spaces, set share=True to make the UI public
+
 
 
 
 
 
-gr.load("models/Sevixdd/roberta-base-finetuned-ner").launch()
+#gr.load("models/Sevixdd/roberta-base-finetuned-ner").launch()