Update app.py

app.py

@@ -137,7 +137,7 @@ def get_health_professionals_and_map(location, query):
     """Search nearby healthcare professionals using Google Maps API."""
     try:
         if not location or not query:
-            return ["Please provide both location and query."], ""
+            return [], "Please provide both location and query.", ""
 
         geo_location = gmaps.geocode(location)
         if geo_location:
@@ -146,31 +146,40 @@ def get_health_professionals_and_map(location, query):
             professionals = []
             map_ = folium.Map(location=(lat, lng), zoom_start=13)
             for place in places_result:
-                professionals.append(f"{place['name']} - {place.get('vicinity', 'No address provided')}")
+                professionals.append({
+                    "Name": place['name'],
+                    "Address": place.get('vicinity', 'No address provided'),
+                })
                 folium.Marker(
                     location=[place["geometry"]["location"]["lat"], place["geometry"]["location"]["lng"]],
                     popup=f"{place['name']}"
                 ).add_to(map_)
-            return professionals, map_._repr_html_()
+            return professionals, "", map_._repr_html_()
 
-        return ["No professionals found for the given location."], ""
+        return [], "No professionals found for the given location.", ""
     except Exception as e:
-        return [f"An error occurred: {e}"], ""
+        return [], f"An error occurred: {e}", ""
 
-# Main Application Logic
 def app_function(user_input, location, query, history):
+    """Main application function to process inputs and return outputs."""
     chatbot_history, _ = generate_chatbot_response(user_input, history)
     sentiment_result = analyze_sentiment(user_input)
     emotion_result, cleaned_emotion = detect_emotion(user_input)
     suggestions = generate_suggestions(cleaned_emotion)
-    professionals, map_html = get_health_professionals_and_map(location, query)
-    return chatbot_history, sentiment_result, emotion_result, suggestions, professionals, map_html
+
+    # Fetch professionals dynamically
+    professionals_data, error_message, map_html = get_health_professionals_and_map(location, query)
+
+    if error_message:
+        professionals_data = [{"Name": "Error", "Address": error_message}]
+
+    return chatbot_history, sentiment_result, emotion_result, suggestions, professionals_data, map_html
 
 # CSS Styling
 custom_css = """
 body {
     font-family: 'Roboto', sans-serif;
-    background: linear-gradient(135deg, #0d0d0d, #ff5722);
+    background: linear-gradient(135deg, #0f9d58, #34a853);
     color: white;
 }
 
@@ -240,11 +249,9 @@ with gr.Blocks(css=custom_css) as app:
     sentiment = gr.Textbox(label="Detected Sentiment")
     emotion = gr.Textbox(label="Detected Emotion")
     
-    # Adding Suggestions Title with Styled Markdown (Centered and Bold)
     gr.Markdown("Suggestions", elem_id="suggestions-title")
-    
     suggestions = gr.DataFrame(headers=["Title", "Link"])  # Table for suggestions
-    professionals = gr.Textbox(label="Nearby Professionals", lines=6)
+    professionals = gr.DataFrame(headers=["Name", "Address"])  # Table for professionals
     map_html = gr.HTML(label="Interactive Map")
     submit = gr.Button(value="Submit", variant="primary")
 
@@ -254,4 +261,4 @@ with gr.Blocks(css=custom_css) as app:
         outputs=[chatbot, sentiment, emotion, suggestions, professionals, map_html],
     )
 
-app.launch()
+app.launch()