Update app.py

app.py

@@ -13,24 +13,24 @@ import googlemaps
 import folium
 import torch
 
-# Disable GPU usage for TensorFlow
+# Disable GPU usage for TensorFlow and suppress logs
 os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
-# Download necessary NLTK resources
+# Ensure necessary NLTK resources are downloaded
 nltk.download("punkt")
 
 # Initialize Lancaster Stemmer
 stemmer = LancasterStemmer()
 
-# Load chatbot training data and intents
+# Load intents.json and chatbot training data
 with open("intents.json") as file:
     intents_data = json.load(file)
 
 with open("data.pickle", "rb") as f:
     words, labels, training, output = pickle.load(f)
 
-# Build the chatbot's neural network model
+# Build Chatbot Model
 net = tflearn.input_data(shape=[None, len(training[0])])
 net = tflearn.fully_connected(net, 8)
 net = tflearn.fully_connected(net, 8)
@@ -39,18 +39,19 @@ net = tflearn.regression(net)
 chatbot_model = tflearn.DNN(net)
 chatbot_model.load("MentalHealthChatBotmodel.tflearn")
 
-# Hugging Face models for sentiment and emotion detection
+# Hugging Face sentiment and emotion detection models
 tokenizer_sentiment = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
 model_sentiment = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
 
 tokenizer_emotion = AutoTokenizer.from_pretrained("j-hartmann/emotion-english-distilroberta-base")
 model_emotion = AutoModelForSequenceClassification.from_pretrained("j-hartmann/emotion-english-distilroberta-base")
 
-# Google Maps API Client
+# Google Maps API client
 gmaps = googlemaps.Client(key=os.getenv('GOOGLE_API_KEY'))
 
-# Function to process text input into a bag-of-words format
+# Helper Functions
 def bag_of_words(s, words):
+    """Convert user input into bag-of-words vector for use in chatbot model."""
     bag = [0] * len(words)
     s_words = word_tokenize(s)
     s_words = [stemmer.stem(word.lower()) for word in s_words if word.isalnum()]
@@ -60,7 +61,6 @@ def bag_of_words(s, words):
                 bag[i] = 1
     return np.array(bag)
 
-# Chatbot Logic
 def chatbot(message, history):
     """Generate chatbot response and append to history."""
     history = history or []
@@ -77,8 +77,8 @@ def chatbot(message, history):
     history.append((message, response))
     return history, response
 
-# Sentiment Analysis
 def analyze_sentiment(user_input):
+    """Analyze sentiment with emojis."""
     inputs = tokenizer_sentiment(user_input, return_tensors="pt")
     with torch.no_grad():
         outputs = model_sentiment(**inputs)
@@ -86,125 +86,143 @@ def analyze_sentiment(user_input):
     sentiment_map = ["Negative 😔", "Neutral 😐", "Positive 😊"]
     return sentiment_map[sentiment_class]
 
-# Emotion Detection
 def detect_emotion(user_input):
+    """Detect user emotion with emojis."""
     pipe = pipeline("text-classification", model=model_emotion, tokenizer=tokenizer_emotion)
     result = pipe(user_input)
     emotion = result[0]['label']
-    return emotion
+    emotion_map = {
+        "joy": "😊 Joy",
+        "anger": "😠 Anger",
+        "sadness": "😢 Sadness",
+        "fear": "😨 Fear",
+        "surprise": "😲 Surprise",
+        "neutral": "😐 Neutral"
+    }
+    return emotion_map.get(emotion, "Unknown Emotion 🤔")
 
-# Generate Suggestions
 def generate_suggestions(emotion):
-    """Return suggestions aligned with the detected emotion."""
+    """Return suggestions based on detected emotion."""
     suggestions = {
         "joy": [
             ["Relaxation Techniques", '<a href="https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation" target="_blank">Visit</a>'],
             ["Dealing with Stress", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Visit</a>'],
             ["Emotional Wellness Toolkit", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Visit</a>'],
-            ["Relaxation Videos", '<a href="https://youtu.be/m1vaUGtyo-A" target="_blank">Watch</a>']
+            ["Relaxation Video", '<a href="https://youtu.be/m1vaUGtyo-A" target="_blank">Watch</a>']
         ],
         "anger": [
             ["Emotional Wellness Toolkit", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Visit</a>'],
-            ["Stress Management Tips", '<a href="https://www.health.harvard.edu" target="_blank">Visit</a>'],
-            ["Dealing with Anger", '<a href="https://www.helpguide.org/mental-health/anger-management" target="_blank">Visit</a>'],
-            ["Relaxation Videos", '<a href="https://youtu.be/MIc299Flibs" target="_blank">Watch</a>']
+            ["Stress Management Tips", '<a href="https://www.health.harvard.edu/health-a-to-z" target="_blank">Visit</a>'],
+            ["Dealing with Anger", '<a href="https://www.helpguide.org/mental-health/anger-management.htm" target="_blank">Visit</a>'],
+            ["Relaxation Video", '<a href="https://youtu.be/MIc299Flibs" target="_blank">Watch</a>']
         ],
         "fear": [
             ["Mindfulness Practices", '<a href="https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation" target="_blank">Visit</a>'],
             ["Coping with Anxiety", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Visit</a>'],
-            ["Relaxation Videos", '<a href="https://youtu.be/yGKKz185M5o" target="_blank">Watch</a>']
+            ["Emotional Wellness Toolkit", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Visit</a>'],
+            ["Relaxation Video", '<a href="https://youtu.be/yGKKz185M5o" target="_blank">Watch</a>']
         ],
         "sadness": [
             ["Emotional Wellness Toolkit", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Visit</a>'],
             ["Dealing with Anxiety", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Visit</a>'],
-            ["Relaxation Videos", '<a href="https://youtu.be/-e-4Kx5px_I" target="_blank">Watch</a>']
+            ["Relaxation Video", '<a href="https://youtu.be/-e-4Kx5px_I" target="_blank">Watch</a>']
         ],
         "surprise": [
-            ["Managing Stress", '<a href="https://www.health.harvard.edu" target="_blank">Visit</a>'],
+            ["Managing Stress", '<a href="https://www.health.harvard.edu/health-a-to-z" target="_blank">Visit</a>'],
             ["Coping Strategies", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Visit</a>'],
-            ["Relaxation Videos", '<a href="https://youtu.be/m1vaUGtyo-A" target="_blank">Watch</a>']
+            ["Relaxation Video", '<a href="https://youtu.be/m1vaUGtyo-A" target="_blank">Watch</a>']
         ],
     }
     return suggestions.get(emotion.lower(), [["No suggestions available", ""]])
 
-# Get Health Professionals and Generate Map
 def get_health_professionals_and_map(location, query):
-    """Search professionals and return details + map as HTML."""
+    """Search for nearby professionals and generate interactive map."""
     try:
         geo_location = gmaps.geocode(location)
         if geo_location:
             lat, lng = geo_location[0]["geometry"]["location"].values()
+            map_ = folium.Map(location=(lat, lng), zoom_start=13)
             places_result = gmaps.places_nearby(location=(lat, lng), radius=10000, keyword=query)["results"]
 
-            map_ = folium.Map(location=(lat, lng), zoom_start=13)
             professionals = []
             for place in places_result:
                 professionals.append(f"{place['name']} - {place.get('vicinity', '')}")
-                folium.Marker([place["geometry"]["location"]["lat"], place["geometry"]["location"]["lng"]],
-                              popup=place["name"]).add_to(map_)
+                folium.Marker(
+                    location=[place["geometry"]["location"]["lat"], place["geometry"]["location"]["lng"]],
+                    popup=place["name"]
+                ).add_to(map_)
             return professionals, map_._repr_html_()
-        return ["No professionals found"], ""
+        return ["No professionals found nearby."], ""
     except Exception as e:
-        return [f"Error: {e}"], ""
+        return [f"Error: {str(e)}"], ""
 
-# Main Application Logic
+# Application Logic
 def app_function(user_input, location, query, history):
-    chatbot_history, response = chatbot(user_input, history)
+    chatbot_history, _ = chatbot(user_input, history)
+    sentiment = analyze_sentiment(user_input)
     emotion = detect_emotion(user_input)
     suggestions = generate_suggestions(emotion)
     professionals, map_html = get_health_professionals_and_map(location, query)
-    return chatbot_history, emotion, suggestions, professionals, map_html
+    return chatbot_history, sentiment, emotion, suggestions, professionals, map_html
 
-# Enhanced CSS for Custom UI
+# Custom CSS for Styling Submit Button and UI
 custom_css = """
-body {
-    background: linear-gradient(135deg, #000000, #ff5722);
-    color: white;
-    font-family: 'Roboto', sans-serif;
+body { 
+    background: linear-gradient(135deg, #000000, #ff5722); 
+    color: white; 
+    font-family: 'Roboto', sans-serif; 
+}
+button { 
+    background: linear-gradient(45deg, #ff5722, #ff9800) !important; 
+    color: white !important; 
+    border: none; 
+    border-radius: 8px; 
+    padding: 12px 20px; 
+    cursor: pointer; 
+    font-size: 16px; 
+    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.3); 
 }
-textarea, input[type="text"], .gr-chatbot {
-    background: #000000 !important;
-    color: white !important;
-    border: 2px solid #ff5722 !important;
-    border-radius: 5px;
-    padding: 12px !important;
+button:hover { 
+    background: linear-gradient(45deg, #ff9800, #ff5722) !important; 
 }
-.gr-dataframe {
-    background: #000000 !important;
-    color: white !important;
-    height: 350px !important;
-    border: 2px solid #ff5722 !important;
-    overflow-y: auto;
+textarea, input { 
+    background: #000000 !important; 
+    color: white !important; 
+    border: 1px solid #ff5722 !important; 
+    padding: 12px; 
+    font-size: 14px; 
+    border-radius: 8px; 
 }
-h1, h2, h3 {
-    color: white;
-    text-align: center;
-    font-weight: bold;
+.gr-chatbot, .gr-textbox, .gr-html, .gr-dataframe { 
+    background-color: #000 !important; 
+    border: 1px solid #ff5722 !important; 
+    color: white !important; 
 }
 """
 
 # Gradio Application
 with gr.Blocks(css=custom_css) as app:
-    gr.Markdown("<h1>🌟 Well-Being Companion</h1>")
-    gr.Markdown("<h2>Empowering Your Well-Being Journey 💚</h2>")
+    gr.Markdown("<h1 style='text-align: center;'>🌟 Well-Being Companion</h1>")
+    gr.Markdown("<h3 style='text-align: center;'>Empowering Your Well-Being Journey 💚</h3>")
 
     with gr.Row():
-        user_input = gr.Textbox(label="Your Message", placeholder="Enter your message...")
+        user_message = gr.Textbox(label="Your Message", placeholder="Type your message...")
         location = gr.Textbox(label="Your Location", placeholder="Enter your location...")
-        query = gr.Textbox(label="Query (e.g., therapists)", placeholder="Search...")
+        query = gr.Textbox(label="Search Query", placeholder="e.g., therapist, doctor")
 
-    chatbot_history = gr.Chatbot(label="Chat History")
-    emotion_box = gr.Textbox(label="Detected Emotion")
-    suggestions_table = gr.DataFrame(headers=["Suggestion", "Link"])
-    map_box = gr.HTML(label="Map of Health Professionals")
-    professionals_list = gr.Textbox(label="Health Professionals Nearby", lines=5)
+    chatbot_output = gr.Chatbot(label="Chat History")
+    sentiment_output = gr.Textbox(label="Detected Sentiment")
+    emotion_output = gr.Textbox(label="Detected Emotion")
+    suggestion_table = gr.DataFrame(headers=["Suggestion Title", "Link"], label="Well-Being Suggestions")
+    professionals_output = gr.Textbox(label="Health Professionals Nearby", lines=5)
+    map_html = gr.HTML(label="Interactive Map")
 
-    submit_button = gr.Button("Submit")
+    submit_btn = gr.Button("Submit")
 
-    submit_button.click(
+    submit_btn.click(
         app_function,
-        inputs=[user_input, location, query, chatbot_history],
-        outputs=[chatbot_history, emotion_box, suggestions_table, professionals_list, map_box],
+        inputs=[user_message, location, query, chatbot_output],
+        outputs=[chatbot_output, sentiment_output, emotion_output, suggestion_table, professionals_output, map_html]
     )
 
 app.launch()