Update app.py

app.py

@@ -1,129 +1,140 @@
 import streamlit as st
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-import torch
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
 
-# Set page config for a clean interface
-st.set_page_config(page_title="Emotion Prediction & Well-being Suggestions", page_icon="🌺", layout="centered")
+# Load the emotion prediction model
+@st.cache_resource
+def load_model():
+    try:
+        # Use Hugging Face's pipeline for text classification
+        emotion_classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base")
+        return emotion_classifier
+    except Exception as e:
+        st.error(f"Error loading model: {str(e)}")
+        return None
 
-# Title and Introduction
-st.title("Emotion Prediction & Well-being Suggestions")
-st.markdown("""
-This app uses AI to understand your emotions based on your responses. Afterward, you'll receive well-being suggestions to improve your mood, tailored specifically for you and your cultural context in Hawaii.
-""")
+emotion_classifier = load_model()
 
-# Load the tokenizer and model
-tokenizer = AutoTokenizer.from_pretrained("j-hartmann/emotion-english-distilroberta-base")
-model = AutoModelForSequenceClassification.from_pretrained("j-hartmann/emotion-english-distilroberta-base")
-
-# Define well-being suggestions with URLs for articles and videos based on the emotion
-def get_wellbeing_suggestions(emotion):
+# Well-being suggestions based on emotions
+def get_well_being_suggestions(emotion):
     suggestions = {
-        "joy": [
-            "Keep enjoying life! Consider a walk on the beach, or some hula dancing to feel the rhythm of the island.",
-            "Articles and Resources: [Emotional Wellness Toolkit - NIH](https://www.nih.gov/health-information/emotional-wellness-toolkit)",
-            "Videos: [Hula Dance for Well-being](https://youtu.be/m1vaUGtyo-A)"
-        ],
-        "anger": [
-            "Practice deep breathing and mindfulness exercises. Perhaps try surfing or a peaceful walk in nature.",
-            "Articles and Resources: [Tips for Dealing with Anxiety - HelpGuide](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)",
-            "Videos: [Mindful Breathing Meditation](https://www.youtube.com/shorts/Tq49ajl7c8Q?feature=share)"
-        ],
-        "sadness": [
-            "Try a short meditation session or call a friend to chat. Hawaii offers stunning sunsets perfect for reflection.",
-            "Articles and Resources: [Health A-Z - Harvard Health](https://www.health.harvard.edu/health-a-to-z)",
-            "Videos: [Mindful Breathing Meditation](https://youtu.be/MIc299Flibs)"
-        ],
-        "fear": [
-            "Take a calming breath and practice grounding techniques. Explore Hawaiian mindfulness practices to feel centered.",
-            "Articles and Resources: [Mindful Breathing Meditation - HelpGuide](https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation)",
-            "Videos: [Relaxing Mindfulness Exercise](https://www.youtube.com/shorts/fwH8Ygb0K60?feature=share)"
-        ],
-        "surprise": [
-            "Embrace the feeling and explore new activities like paddleboarding or hiking.",
-            "Articles and Resources: [Emotional Wellness Toolkit - NIH](https://www.nih.gov/health-information/emotional-wellness-toolkit)",
-            "Videos: [Surprising Relaxation Tips](https://youtu.be/yGKKz185M5o)"
-        ],
-        "disgust": [
-            "Do something relaxing, like yoga or watching the waves crash against the shore.",
-            "Articles and Resources: [Tips for Dealing with Anxiety - HelpGuide](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)",
-            "Videos: [Hawaiian Mindfulness Practice](https://www.youtube.com/shorts/hTXMi7ZBKdM?feature=share)"
-        ]
+        "joy": {
+            "text": "You're feeling joyful! Keep the positivity going.",
+            "links": [
+                "https://www.nih.gov/health-information/emotional-wellness-toolkit",
+                "https://www.health.harvard.edu/health-a-to-z",
+                "https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation"
+            ],
+            "videos": [
+                "https://youtu.be/m1vaUGtyo-A",
+                "https://youtu.be/MIc299Flibs"
+            ]
+        },
+        "anger": {
+            "text": "You're feeling angry. Take a moment to calm down.",
+            "links": [
+                "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety",
+                "https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation"
+            ],
+            "videos": [
+                "https://youtu.be/m1vaUGtyo-A",
+                "https://www.youtube.com/shorts/fwH8Ygb0K60?feature=share"
+            ]
+        },
+        "sadness": {
+            "text": "You're feeling sad. It's okay to take a break.",
+            "links": [
+                "https://www.nih.gov/health-information/emotional-wellness-toolkit",
+                "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety"
+            ],
+            "videos": [
+                "https://youtu.be/-e-4Kx5px_I",
+                "https://youtu.be/Y8HIFRPU6pM"
+            ]
+        },
+        "fear": {
+            "text": "You're feeling fearful. Try some relaxation techniques.",
+            "links": [
+                "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety",
+                "https://www.health.harvard.edu/health-a-to-z"
+            ],
+            "videos": [
+                "https://www.youtube.com/shorts/Tq49ajl7c8Q?feature=share",
+                "https://youtu.be/yGKKz185M5o"
+            ]
+        },
+        "disgust": {
+            "text": "You're feeling disgusted. Take a deep breath and refocus.",
+            "links": [
+                "https://www.health.harvard.edu/health-a-to-z",
+                "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety"
+            ],
+            "videos": [
+                "https://youtu.be/MIc299Flibs",
+                "https://youtu.be/-e-4Kx5px_I"
+            ]
+        },
     }
-    return suggestions.get(emotion, [
-        "Try some breathing exercises and give yourself time to relax.",
-        "Articles and Resources: [Health A-Z - Harvard Health](https://www.health.harvard.edu/health-a-to-z)",
-        "Videos: [Calming Breath Exercises](https://youtu.be/Y8HIFRPU6pM)"
-    ])
-
-# Emotional Health Questions
-questions = [
-    "How would you describe your mood today? (e.g., happy, stressed, calm)",
-    "Are there any recent events that might be affecting your emotional state?",
-    "How do you generally cope with stress or emotional challenges?"
-]
-
-responses = []
-for question in questions:
-    response = st.text_input(question)
-    responses.append(response)
+    return suggestions.get(emotion, {
+        "text": "Feeling neutral? That's okay! Take care of your mental health.",
+        "links": [],
+        "videos": []
+    })
 
-# Process the responses
-if all(responses):
-    user_input = " ".join(responses)
-    
-    # Tokenize the user input and make predictions
-    inputs = tokenizer(user_input, return_tensors="pt", truncation=True, padding=True)
-    outputs = model(**inputs)
-    predictions = torch.argmax(outputs.logits, dim=-1)  # Get the index of the predicted class
-    emotion_label = model.config.id2label[predictions.item()]  # Get the label of the predicted class
-    
-    # Show emotion and well-being suggestions
-    st.subheader(f"Your Predicted Emotion: {emotion_label.capitalize()}")
-    st.write(f"Based on your responses, we suggest the following to improve your well-being:")
-    
-    wellbeing_suggestions = get_wellbeing_suggestions(emotion_label.lower())
-    for suggestion in wellbeing_suggestions:
-        st.write(f"- {suggestion}")
-    
-    # Show Summary Button
-    if st.button("Show Summary"):
-        st.subheader("Summary of Well-being Suggestions")
-        for suggestion in wellbeing_suggestions:
-            st.write(f"- {suggestion}")
-    
-    st.markdown("---")
-    st.write("For more well-being tips and resources, explore the following links:")
-    st.markdown("[Hawaii Mindfulness Practice](https://www.hawaiimindfulness.org)")
-    st.markdown("[Hula Dance for Well-being](https://hulahealsthesoul.com)")
-
-else:
-    st.warning("Please answer all the questions to receive emotional health suggestions.")
-
-# Add custom background image to make it visually appealing
-st.markdown("""
+# Streamlit UI
+def main():
+    # Set the background image
+    st.markdown("""
     <style>
     .stApp {
-        background-image: url('https://images.unsplash.com/photo-1602231353203-b1e5e2191b68');
+        background-image: url('https://www.example.com/your-image.jpg');
         background-size: cover;
         background-position: center;
     }
-    .stButton > button {
-        background-color: #F57F17; 
-        color: white;
-        font-size: 18px;
-        padding: 10px;
-    }
-    .stButton > button:hover {
-        background-color: #FF6F00;
-    }
-    .stTextInput > div > input {
-        background-color: rgba(255, 255, 255, 0.7);
-        font-size: 16px;
-        color: #333;
-    }
-    .stMarkdown p {
-        font-size: 16px;
-        color: white;
-    }
     </style>
-""", unsafe_allow_html=True)
+    """, unsafe_allow_html=True)
+    
+    # Title of the app
+    st.title("Emotion Prediction and Well-being Suggestions")
+    
+    # User input for emotional state
+    st.header("Tell us how you're feeling today!")
+    
+    user_input = st.text_area("Enter a short sentence about your current mood:", "")
+    
+    if user_input:
+        # Use the model to predict emotion
+        try:
+            result = emotion_classifier(user_input)
+            emotion = result[0]['label'].lower()
+
+            st.subheader(f"Emotion Detected: {emotion.capitalize()}")
+            
+            # Get well-being suggestions based on emotion
+            suggestions = get_well_being_suggestions(emotion)
+            
+            # Display text suggestions
+            st.write(suggestions["text"])
+
+            # Display links
+            if suggestions["links"]:
+                st.write("Useful Resources:")
+                for link in suggestions["links"]:
+                    st.markdown(f"[{link}]({link})")
+
+            # Display video links
+            if suggestions["videos"]:
+                st.write("Relaxation Videos:")
+                for video in suggestions["videos"]:
+                    st.markdown(f"[Watch here]({video})")
+            
+            # Add a button for a summary
+            if st.button('Summary'):
+                st.write(f"Emotion detected: {emotion.capitalize()}. Here are your well-being suggestions to enhance your mood.")
+                st.write("Explore the links and videos to improve your emotional health!")
+            
+        except Exception as e:
+            st.error(f"Error predicting emotion: {str(e)}")
+
+# Run the Streamlit app
+if __name__ == "__main__":
+    main()