Update app.py

app.py

@@ -1,62 +1,106 @@
-# Install necessary libraries (if not already installed)
-# pip install streamlit transformers datasets
-
 import streamlit as st
 from transformers import pipeline
-from datasets import load_dataset
-
-# Load the pre-trained model for sentiment analysis (using a valid model from Hugging Face)
-emotion_analyzer = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2")
-
-# Load a dataset from Hugging Face (Sentiment Analysis - SST-2)
-dataset = load_dataset("glue", "sst2")
-
-# Example of how to use a dataset (showing the first few examples)
-st.write("Dataset Sample (SST-2):")
-st.write(dataset["train"][0:3])  # Display the first 3 samples
-
-# Define the function to analyze emotions and suggest strategies
-def analyze_and_suggest(responses):
-    suggestions = []
-    for response in responses:
-        # Get the sentiment analysis result
-        result = emotion_analyzer(response)[0]
-        label = result['label']
-
-        # Suggest strategies based on sentiment
-        if label == "NEGATIVE":
-            suggestions.append("Try deep breathing exercises or mindfulness activities.")
-        elif label == "POSITIVE":
-            suggestions.append("Great! Keep the positivity going with a walk or some light exercise.")
-        else:
-            suggestions.append("Consider focusing on better sleep or reflecting on your priorities.")
-    
-    return suggestions
 
-# Streamlit App UI
-st.title("Personalized Self-Care Strategy App")
-st.markdown("### Answer the following questions to get personalized self-care suggestions.")
+# Load the emotion analysis pipeline using an open-access model
+emotion_analyzer = pipeline(
+    "text-classification", 
+    model="j-hartmann/emotion-english-distilroberta-base"
+)
+
+# App title and description
+st.set_page_config(page_title="Hawaii Emotion Wellness", layout="centered", page_icon="🌴")
+st.markdown(
+    """
+    <style>
+        body {
+            background-color: #E0F7FA;
+            color: #004D40;
+        }
+        .main-header {
+            font-size: 36px;
+            font-weight: bold;
+            text-align: center;
+            margin-bottom: 10px;
+        }
+        .sub-header {
+            font-size: 18px;
+            text-align: center;
+            margin-bottom: 20px;
+        }
+        .suggestion-card {
+            background-color: #B2EBF2;
+            padding: 15px;
+            border-radius: 8px;
+            margin-bottom: 15px;
+        }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
 
-# List of questions for user to answer
+st.markdown('<div class="main-header">🌺 Hawaii Emotion Wellness App 🌴</div>', unsafe_allow_html=True)
+st.markdown('<div class="sub-header">Understand your emotions and find the right balance in paradise.</div>', unsafe_allow_html=True)
+
+# Step 1: Collect user's responses
+st.markdown("### Answer these three questions to get started:")
 questions = [
-    "1. How do you feel about your overall health today?",
-    "2. How have you been sleeping recently?",
-    "3. Do you feel overwhelmed with tasks or emotions?",
-    "4. What are your energy levels like today?",
-    "5. How often do you exercise or engage in physical activity?"
+    "How are you feeling right now? (e.g., stressed, happy, sad)",
+    "What is the most pressing issue on your mind currently?",
+    "On a scale of 1-10, how motivated do you feel to take care of yourself today?",
 ]
 
-# Collect user responses
 responses = []
 for question in questions:
-    responses.append(st.text_input(question, placeholder="Type your response here..."))
-
-# Button to analyze and provide self-care suggestions
-if st.button("Get Self-Care Suggestions"):
-    if all(responses):  # Ensure all questions are answered
-        suggestions = analyze_and_suggest(responses)
-        st.markdown("### **Your Personalized Suggestions**")
-        for i, suggestion in enumerate(suggestions, 1):
-            st.write(f"**{i}.** {suggestion}")
+    response = st.text_input(question)
+    responses.append(response)
+
+# Analyze the emotions if the user has answered all questions
+if st.button("Analyze Emotions"):
+    if all(responses):
+        # Aggregate responses into a single input for emotion analysis
+        aggregated_response = " ".join(responses)
+        emotion_results = emotion_analyzer(aggregated_response)
+
+        # Get the most likely emotion
+        predicted_emotion = emotion_results[0]["label"]
+        st.markdown(f"### Your Predicted Emotion: **{predicted_emotion}** 🎭")
+
+        # Provide well-being suggestions
+        st.markdown("### Here's what we recommend for you:")
+        suggestions = {
+            "joy": [
+                {"activity": "Go for a walk on the beach", "url": "https://www.hawaiibeachwalks.com"},
+                {"activity": "Try a short surfing session", "url": "https://www.learnsurf.com"},
+                {"activity": "Join a hula dancing class", "url": "https://www.hulahawaii.com"},
+            ],
+            "sadness": [
+                {"activity": "Practice deep breathing for 5 minutes", "url": "https://www.breathingexercise.com"},
+                {"activity": "Watch a calming ocean video", "url": "https://www.youtube.com/watch?v=lM02vNMRRB0"},
+                {"activity": "Do a quick yoga session", "url": "https://www.doyogawithme.com"},
+            ],
+            # Add more emotions as needed
+        }
+
+        user_suggestions = suggestions.get(predicted_emotion.lower(), [])
+        if user_suggestions:
+            for suggestion in user_suggestions:
+                st.markdown(
+                    f"""
+                    <div class="suggestion-card">
+                        <strong>{suggestion['activity']}</strong>
+                        <br>
+                        <a href="{suggestion['url']}" target="_blank">Learn More</a>
+                    </div>
+                    """,
+                    unsafe_allow_html=True,
+                )
+        else:
+            st.markdown("Stay positive! Enjoy the aloha spirit and take a deep breath.")
     else:
-        st.error("Please answer all the questions before proceeding.")
+        st.warning("Please answer all the questions to analyze your emotions.")
+
+# Footer
+st.markdown("---")
+st.markdown(
+    "Built with ❤️ for the Hawaii Hackathon 2024 by [Your Team Name]. Deployed on Hugging Face Spaces."
+)