added the integrated routes ✅✅

app.py

@@ -1,11 +1,22 @@
 import gradio as gr
-from transformers import pipeline
+import requests
+from urllib.parse import parse_qs, urlparse
+
+# Backend API endpoints
+BACKEND_BASE_URL = "http://127.0.0.1:5000"  # Local development  # Flask backend URL
+COMPLETE_APPOINTMENT_ENDPOINT = f"{BACKEND_BASE_URL}/complete_appointment"
+
+# Function to extract `appointment_id` from query parameters
+def get_appointment_id():
+    query_params = parse_qs(urlparse(gr.Request().url).query)
+    return query_params.get("appointment_id", ["Unknown"])[0]
 
 # Load Hugging Face pipelines
-ner_pipeline = pipeline("ner", model="dslim/bert-base-NER")
-sentiment_pipeline = pipeline("sentiment-analysis")
-summarization_pipeline = pipeline("summarization", model="facebook/bart-large-cnn")
-conversation_pipeline = pipeline("text-generation", model="microsoft/DialoGPT-medium")
+from transformers import pipeline
+ner_pipeline = pipeline("ner", model="dslim/bert-base-NER")  # Named Entity Recognition
+sentiment_pipeline = pipeline("sentiment-analysis")  # Sentiment Analysis
+summarization_pipeline = pipeline("summarization", model="facebook/bart-large-cnn")  # Summarization
+conversation_pipeline = pipeline("text-generation", model="microsoft/DialoGPT-medium")  # Conversational AI
 
 # Function to process user input
 def ai_doctor_interaction(user_input, chat_history=[]):
@@ -34,6 +45,19 @@ def ai_doctor_interaction(user_input, chat_history=[]):
     chat_history.append(("AI Doctor", response))
     return chat_history, chat_history
 
+# Function to handle "End Call" button
+def end_call():
+    appointment_id = get_appointment_id()
+    if appointment_id == "Unknown":
+        return "Error: Appointment ID not found. Please try again."
+
+    # Send a request to the backend to mark the appointment as completed
+    response = requests.post(COMPLETE_APPOINTMENT_ENDPOINT, json={"appointment_id": appointment_id})
+    if response.status_code == 200:
+        return "Appointment marked as completed. Redirecting to the doctors' page..."
+    else:
+        return f"Error: {response.json().get('message', 'Failed to complete the appointment')}"
+
 # Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("<h1 style='text-align: center;'>AI Doctor Avatar</h1>")
@@ -61,5 +85,10 @@ with gr.Blocks() as demo:
     submit_button.click(ai_doctor_interaction, inputs=[user_input, chatbot], outputs=[chatbot, chatbot])
     clear_button.click(lambda: [], inputs=[], outputs=[chatbot])
 
+    # Add "End Call" button
+    end_call_button = gr.Button("End Call", variant="stop")
+    end_call_message = gr.Textbox(label="End Call Status", interactive=False)
+    end_call_button.click(end_call, outputs=[end_call_message])
+
 # Launch the Gradio app
 demo.launch()