Update app.py

app.py

@@ -13,7 +13,7 @@ import googlemaps
 import folium
 import torch
 
-# Suppress TensorFlow's GPU usage and warnings
+# Suppress TensorFlow GPU usage and warnings
 os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
 os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
 
@@ -21,7 +21,7 @@ os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
 nltk.download("punkt")
 stemmer = LancasterStemmer()
 
-# Load intents and chatbot training data
+# Load chatbot training data
 with open("intents.json") as file:
     intents_data = json.load(file)
 
@@ -100,7 +100,7 @@ def detect_emotion(user_input):
     return emotion_map.get(emotion, "Unknown 🤔")
 
 def generate_suggestions(emotion):
-    """Provide suggestions based on the detected emotion."""
+    """Provide suggestions for the detected emotion."""
     suggestions = {
         "joy": [
             ["Relaxation Techniques", '<a href="https://www.helpguide.org/mental-health/meditation" target="_blank">Visit</a>'],
@@ -114,7 +114,7 @@ def generate_suggestions(emotion):
         ],
         "fear": [
             ["Coping with Anxiety", '<a href="https://www.helpguide.org/mental-health/anxiety" target="_blank">Visit</a>'],
-            ["Mindfulness Techniques", '<a href="https://youtu.be/yGKKz185M5o" target="_blank">Watch</a>'],
+            ["Mindfulness Practices", '<a href="https://youtu.be/yGKKz185M5o" target="_blank">Watch</a>'],
         ],
         "sadness": [
             ["Overcoming Sadness", '<a href="https://youtu.be/-e-4Kx5px_I" target="_blank">Watch</a>'],
@@ -151,7 +151,7 @@ def get_health_professionals_and_map(location, query):
     except Exception as e:
         return [f"An error occurred: {str(e)}"], ""
 
-# Main Application Logic
+# Application Logic
 def app_function(user_message, location, query, history):
     chatbot_history, _ = chatbot(user_message, history)
     sentiment = analyze_sentiment(user_message)
@@ -160,58 +160,61 @@ def app_function(user_message, location, query, history):
     professionals, map_html = get_health_professionals_and_map(location, query)
     return chatbot_history, sentiment, emotion, suggestions, professionals, map_html
 
-# Custom CSS for Dark Theme and Gradient Buttons
+# CSS Styling for Centered and Bigger Titles
 custom_css = """
 body {
     background: linear-gradient(135deg, #000000, #ff5722);
     font-family: 'Roboto', sans-serif;
     color: white;
 }
+h1 {
+    font-size: 4rem;
+    font-weight: bold;
+    text-align: center;
+    margin-bottom: 10px;
+    text-shadow: 3px 3px 8px rgba(0, 0, 0, 0.7);
+}
+h3 {
+    font-size: 2rem;
+    text-align: center;
+    margin-bottom: 40px;
+    font-weight: lighter;
+    color: white;
+}
 button {
     background: linear-gradient(45deg, #ff5722, #ff9800) !important;
     border: none;
-    border-radius: 8px;
     padding: 12px 20px;
-    cursor: pointer;
-    color: white;
     font-size: 16px;
+    border-radius: 8px;
+    color: white;
+    cursor: pointer;
     box-shadow: 0 4px 6px rgba(0, 0, 0, 0.3);
 }
-button:hover {
-    background: linear-gradient(45deg, #ff9800, #ff5722) !important;
-}
 textarea, input {
     background: black !important;
     color: white !important;
-    padding: 12px;
-    border: 1px solid #ff5722 !important;
-    border-radius: 8px;
-}
-.gr-dataframe {
-    background-color: black !important;
-    color: white !important;
-    overflow-y: scroll;
-    height: 300px;
     border: 1px solid #ff5722;
+    border-radius: 8px;
 }
 """
 
-# Gradio Interface
+# Gradio Application
 with gr.Blocks(css=custom_css) as app:
-    gr.Markdown("<h1 style='text-align: center;'>🌟 Well-Being Companion</h1>")
-    gr.Markdown("<h3 style='text-align: center;'>Empowering Your Mental Health Journey 💚</h3>")
+    gr.HTML("<h1>🌟 Well-Being Companion</h1>")
+    gr.HTML("<h3>Empowering Your Mental Health Journey 💚</h3>")
 
     with gr.Row():
         user_message = gr.Textbox(label="Your Message", placeholder="Enter your message...")
         location = gr.Textbox(label="Your Location", placeholder="Enter your location...")
-        query = gr.Textbox(label="Health Query", placeholder="Search for health professionals...")
+        query = gr.Textbox(label="Health Query", placeholder="Search for professionals like therapists...")
 
     chatbot_history = gr.Chatbot(label="Chat History")
     sentiment_output = gr.Textbox(label="Detected Sentiment")
     emotion_output = gr.Textbox(label="Detected Emotion")
-    suggestions_table = gr.DataFrame(headers=["Suggestion", "Link"], label="Suggestions")
+    suggestions_table = gr.DataFrame(headers=["Title", "Link"], label="Suggestions")
     professionals_output = gr.Textbox(label="Nearby Health Professionals", lines=5)
-    map_output = gr.HTML(label="Map")
+    map_output = gr.HTML(label="Map of Nearby Professionals")
 
     submit_button = gr.Button("Submit")