Update app.py

app.py

@@ -11,7 +11,6 @@ from nltk.stem.lancaster import LancasterStemmer
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 import googlemaps
 import folium
-import pandas as pd
 import torch
 
 # Disable GPU usage for TensorFlow
@@ -32,7 +31,7 @@ with open("data.pickle", "rb") as f:
     words, labels, training, output = pickle.load(f)
 
 # Build the model structure for Well-Being Chatbot
-net = tflearn.input_data(shape=[None, len(training[0])])
+net = tflearn.input_data(shape=[None, len(training[0])], dtype=tf.float32)  # Fix for dtype
 net = tflearn.fully_connected(net, 8)
 net = tflearn.fully_connected(net, 8)
 net = tflearn.fully_connected(net, len(output[0]), activation="softmax")
@@ -152,99 +151,45 @@ def generate_suggestions(emotion):
         ],
         'anger': [
             {"Title": "Emotional Wellness Toolkit 💡", "Subject": "Wellness", "Link": '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Emotional Wellness Toolkit</a>'},
-            {"Title": "Stress Management Tips 🧘", "Subject": "Stress Management", "Link": '<a href="https://www.health.harvard.edu/health-a-to-z" target="_blank">Harvard Health: Stress Management</a>'},
-            {"Title": "Dealing with Anger 💥", "Subject": "Anger Management", "Link": '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Tips for Dealing with Anger</a>'},
-            {"Title": "Relaxation Video 🎬", "Subject": "Video", "Link": '<a href="https://youtu.be/MIc299Flibs" target="_blank">Watch Video</a>'}
+            {"Title": "Managing Anger 🌿", "Subject": "Anger Management", "Link": '<a href="https://www.helpguide.org/mental-health/anger-management.htm" target="_blank">HelpGuide on Anger Management</a>'},
+            {"Title": "Relaxation Techniques 💆", "Subject": "Relaxation", "Link": '<a href="https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation" target="_blank">Mindful Breathing Meditation</a>'},
+            {"Title": "Dealing with Stress 💡", "Subject": "Stress Management", "Link": '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Tips for Dealing with Anxiety</a>'}
         ],
-        # Add more suggestions for other emotions as required...
+        'sadness': [
+            {"Title": "Overcoming Sadness 🌈", "Subject": "Well-being", "Link": '<a href="https://www.helpguide.org/mental-health/depression.htm" target="_blank">Overcoming Sadness</a>'},
+            {"Title": "Self-care Practices 🌿", "Subject": "Self-care", "Link": '<a href="https://www.psychologytoday.com/us/blog/pieces-mind/201908/self-care-for-your-mental-health" target="_blank">Self-Care for Mental Health</a>'},
+            {"Title": "Managing Grief 💐", "Subject": "Grief Management", "Link": '<a href="https://www.helpguide.org/mental-health/grief.htm" target="_blank">HelpGuide on Grief</a>'},
+            {"Title": "Mindfulness & Meditation 💆", "Subject": "Meditation", "Link": '<a href="https://www.meditationandmindfulness.com" target="_blank">Mindfulness & Meditation</a>'}
+        ],
+        'fear': [
+            {"Title": "Managing Fear & Anxiety 💡", "Subject": "Mental Health", "Link": '<a href="https://www.psychologytoday.com/us/articles/anxiety" target="_blank">Psychology Today on Anxiety</a>'},
+            {"Title": "Building Confidence 💪", "Subject": "Self-Confidence", "Link": '<a href="https://www.helpguide.org/mental-health/self-confidence.htm" target="_blank">Self-Confidence Guide</a>'},
+            {"Title": "Breathing Exercises 🧘‍♀️", "Subject": "Breathing", "Link": '<a href="https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation" target="_blank">Mindful Breathing Meditation</a>'},
+            {"Title": "Relaxation Tips 🌿", "Subject": "Relaxation", "Link": '<a href="https://www.helpguide.org/mental-health/stress-relief.htm" target="_blank">Stress Relief Tips</a>'}
+        ]
     }
-
-    return suggestions.get(emotion, [])
-
-# Custom CSS for green gradient background and button
-custom_css = """
-/* Gradient Background */
-body {
-    background: linear-gradient(135deg, #00b894, #1dd1a1);
-    font-family: Arial, sans-serif;
-    color: white;
-    box-shadow: inset 0 0 50px rgba(0, 0, 0, 0.1), 0 0 30px rgba(0, 0, 0, 0.1);
-}
-
-/* Green gradient submit button */
-.gradio-button {
-    background: linear-gradient(45deg, #00b894, #1dd1a1);
-    border: none;
-    color: white;
-    font-weight: bold;
-    font-size: 16px;
-    padding: 10px 20px;
-    border-radius: 10px;
-    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-    transition: background 0.3s ease, box-shadow 0.3s ease;
-}
-
-/* Hover effect for the submit button */
-.gradio-button:hover {
-    background: linear-gradient(45deg, #1dd1a1, #00b894);
-    box-shadow: 0 6px 10px rgba(0, 0, 0, 0.2);
-}
-
-/* Styling for the input box and other components */
-.gradio-input, .gradio-output, .gradio-chatbot {
-    background: rgba(255, 255, 255, 0.1);
-    border-radius: 8px;
-    border: none;
-    padding: 10px;
-    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-}
-
-.gradio-input:focus {
-    outline: none;
-    background: rgba(255, 255, 255, 0.2);
-}
-
-/* Shadow effect on components */
-.gradio-box {
-    box-shadow: 0 4px 10px rgba(0, 0, 0, 0.15);
-}
-"""
-
-# Gradio app code (as before)
-def gradio_app(message, location, health_query, history, state):
-    # Chatbot interaction
-    history, _ = chatbot(message, history)
-    
-    # Sentiment analysis
-    sentiment_response = analyze_sentiment(message)
-    
-    # Emotion detection
-    emotion_response = detect_emotion(message)
     
-    # Health professional search and map display
-    route_info, map_html = get_health_professionals_and_map(location, health_query)
+    # Return suggestions based on emotion
+    return suggestions.get(emotion.lower(), [])
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            message_input = gr.Textbox(label="Your Message", placeholder="Type a message here...", lines=4)
+            location_input = gr.Textbox(label="Your Location", placeholder="Enter your location (e.g., Pune, India)...", lines=2)
+            health_query_input = gr.Textbox(label="Health Professional Search", placeholder="Type a health professional type (e.g., therapist, doctor)...", lines=1)
+            history_output = gr.Chatbot(label="Chat History").style(height=500)
+            sentiment_output = gr.Textbox(label="Sentiment Analysis")
+            emotion_output = gr.Textbox(label="Emotion Detection")
+            suggestions_output = gr.Dataframe(label="Suggestions", headers=["Title", "Subject", "Link"], interactive=True)
+            map_output = gr.HTML(label="Map")
+            route_info_output = gr.Textbox(label="Nearby Health Professionals Info")
     
-    # Generate suggestions based on the detected emotion
-    suggestions = generate_suggestions(emotion_response.split(': ')[1])
-    
-    # Create a DataFrame for displaying suggestions
-    suggestions_df = pd.DataFrame(suggestions)
-    
-    return history, sentiment_response, emotion_response, route_info, map_html, gr.DataFrame(suggestions_df, headers=["Title", "Subject", "Link"]), state
-
-# Gradio UI components
-message_input = gr.Textbox(lines=1, label="💬 Message")
-location_input = gr.Textbox(value="Honolulu, HI", lines=1, label="📍 Your Location")
-health_query_input = gr.Textbox(value="psychologist", lines=1, label="👩‍⚕️ Health Professional Query")
-history_output = gr.Chatbot()
-sentiment_output = gr.Textbox()
-emotion_output = gr.Textbox()
-route_info_output = gr.Textbox()
-map_output = gr.HTML()
-suggestions_output = gr.DataFrame()
-
-# Interface with custom CSS
-gr.Interface(fn=gradio_app, inputs=[message_input, location_input, health_query_input, history_output, gr.State()],
-             outputs=[history_output, sentiment_output, emotion_output, route_info_output, map_output, suggestions_output],
-             live=True, 
-             css=custom_css).launch()
+    message_input.submit(chatbot, [message_input, history_output], [history_output, history_output])
+    message_input.submit(analyze_sentiment, message_input, sentiment_output)
+    message_input.submit(detect_emotion, message_input, emotion_output)
+    message_input.submit(generate_suggestions, emotion_output, suggestions_output)
+    location_input.submit(get_health_professionals_and_map, [location_input, health_query_input], [route_info_output, map_output])
+
+demo.launch()