Update app.py

app.py

@@ -169,6 +169,43 @@ def get_wellness_professionals(location):
     # Fallback to scraping if API is not available or fails
     return scrape_wellness_professionals(query, location)
 
+# Emotion detection function with suggestions
+def detect_emotion(user_input):
+    pipe = pipeline("text-classification", model=model_emotion, tokenizer=tokenizer_emotion)
+    result = pipe(user_input)
+    emotion = result[0]['label']
+    
+    # Provide suggestions based on the detected emotion
+    if emotion == 'joy':
+        return ("You're feeling happy! Keep up the great mood!", 
+                [("Relaxation Techniques", "https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation"),
+                 ("Dealing with Stress", "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety"),
+                 ("Emotional Wellness Toolkit", "https://www.nih.gov/health-information/emotional-wellness-toolkit")],
+                "Watch on YouTube: https://youtu.be/m1vaUGtyo-A")
+    elif emotion == 'anger':
+        return ("You're feeling angry. It's okay to feel this way. Let's try to calm down.", 
+                [("Emotional Wellness Toolkit", "https://www.nih.gov/health-information/emotional-wellness-toolkit"),
+                 ("Stress Management Tips", "https://www.health.harvard.edu/health-a-to-z"),
+                 ("Dealing with Anger", "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety")],
+                "Watch on YouTube: https://youtu.be/MIc299Flibs")
+    elif emotion == 'fear':
+        return ("You're feeling fearful. Take a moment to breathe and relax.", 
+                [("Mindfulness Practices", "https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation"),
+                 ("Coping with Anxiety", "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety"),
+                 ("Emotional Wellness Toolkit", "https://www.nih.gov/health-information/emotional-wellness-toolkit")],
+                "Watch on YouTube: https://youtu.be/yGKKz185M5o")
+    elif emotion == 'sadness':
+        return ("You're feeling sad. It's okay to take a break.", 
+                [("Emotional Wellness Toolkit", "https://www.nih.gov/health-information/emotional-wellness-toolkit"),
+                 ("Dealing with Anxiety", "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety")],
+                "Watch on YouTube: https://youtu.be/-e-4Kx5px_I")
+    elif emotion == 'surprise':
+        return ("You're feeling surprised. It's okay to feel neutral!", 
+                [("Managing Stress", "https://www.health.harvard.edu/health-a-to-z"),
+                 ("Coping Strategies", "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety")],
+                "Watch on YouTube: https://youtu.be/m1vaUGtyo-A")
+    return ("Could not detect emotion.", [], "")
+
 # Gradio interface setup for user interaction
 def user_interface(message, location, history):
     history, history = chat(message, history)
@@ -179,14 +216,15 @@ def user_interface(message, location, history):
     sentiment = ["Negative", "Neutral", "Positive"][torch.argmax(outputs.logits, dim=1).item()]
     
     # Emotion detection
-    pipe = pipeline("text-classification", model=model_emotion, tokenizer=tokenizer_emotion)
-    emotion_result = pipe(message)
-    emotion = emotion_result[0]['label']
+    emotion_msg, resources, video_link = detect_emotion(message)
     
     # Get wellness professionals
     wellness_data = get_wellness_professionals(location)
     
-    return history, history, sentiment, emotion, wellness_data
+    # Display wellness professionals in a table format
+    wellness_df = pd.DataFrame(wellness_data, columns=["Name", "Address", "Latitude", "Longitude"])
+    
+    return history, history, sentiment, emotion_msg, resources, video_link, wellness_df.to_html(escape=False)
 
 # Gradio chatbot interface
 chatbot = gr.Chatbot(label="Mental Health Chatbot")
@@ -196,7 +234,7 @@ location_input = gr.Textbox(label="Enter your location (latitude,longitude)", pl
 demo = gr.Interface(
     user_interface,
     [gr.Textbox(label="Message"), location_input, "state"],
-    [chatbot, "state", "text", "text", "json"],
+    [chatbot, "state", "text", "text", "json", "text", "html"],
     allow_flagging="never",
     title="Mental Health & Well-being Assistant"
 )