app.py

import random
import streamlit as st
from transformers import pipeline

# Emotion classifier (use a pre-trained model from Hugging Face)
emotion_analyzer = pipeline("text-classification", model="distilbert-base-uncased")

# Updated Question Database (Doctor-prescribed questions)
questions = [
    "How are you feeling emotionally right now?",
    "What physical sensations or discomfort are you experiencing?",
    "Is there something specific that's been troubling your thoughts?"
]

# Expanded Mood States
moods = [
    "Happy", "Excited", "Relaxed", "Grateful", "Calm",
    "Dull", "Neutral", "Tired", "Bored", "Lonely",
    "Angry", "Frustrated", "Anxious", "Stressed", "Overwhelmed",
    "Hopeful", "Confused", "Motivated", "Curious", "Peaceful"
]

# Suggestion Database
suggestion_database = {
    "POSITIVE": {
        "suggestions": ["Celebrate your success!", "Share your happiness with someone.", "Reflect on what makes you feel this way."],
        "articles": [
            {"title": "Emotional Wellness Toolkit", "url": "https://www.nih.gov/health-information/emotional-wellness-toolkit"},
            {"title": "Health A to Z", "url": "https://www.health.harvard.edu/health-a-to-z"},
        ],
        "videos": [
            {"title": "Boosting Happiness", "url": "https://youtu.be/m1vaUGtyo-A"},
            {"title": "Motivational Short Video", "url": "https://www.youtube.com/shorts/Tq49ajl7c8Q?feature=share"},
        ],
    },
    "NEGATIVE": {
        "suggestions": ["Take a break to relax.", "Talk to someone you trust.", "Try mindfulness exercises."],
        "articles": [
            {"title": "Tips for Dealing with Anxiety", "url": "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety"},
            {"title": "Mindful Breathing Meditation", "url": "https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation"},
        ],
        "videos": [
            {"title": "Coping with Anxiety", "url": "https://youtu.be/MIc299Flibs"},
            {"title": "Relaxation Techniques", "url": "https://www.youtube.com/shorts/fwH8Ygb0K60?feature=share"},
        ],
    },
    "NEUTRAL": {
        "suggestions": ["Take a short walk.", "Plan your next task mindfully.", "Enjoy a calming activity like reading."],
        "articles": [
            {"title": "Finding Balance", "url": "https://www.health.harvard.edu/health-a-to-z"},
            {"title": "Emotional Wellness Toolkit", "url": "https://www.nih.gov/health-information/emotional-wellness-toolkit"},
        ],
        "videos": [
            {"title": "Mindfulness for Beginners", "url": "https://youtu.be/Y8HIFRPU6pM"},
            {"title": "Peaceful Mind Short", "url": "https://www.youtube.com/shorts/hTXMi7ZBKdM?feature=share"},
        ],
    },
    "STRESSED": {
        "suggestions": ["Practice deep breathing exercises.", "Write down your thoughts to release stress.", "Spend time in a quiet environment."],
        "articles": [
            {"title": "Mindful Breathing Meditation", "url": "https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation"},
            {"title": "Tips for Dealing with Anxiety", "url": "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety"},
        ],
        "videos": [
            {"title": "Managing Stress", "url": "https://youtu.be/-e-4Kx5px_I"},
            {"title": "Overcoming Overwhelm", "url": "https://www.youtube.com/shorts/fwH8Ygb0K60?feature=share"},
        ],
    },
}

# Function to map moods to emotion categories
def map_mood_to_category(mood):
    if mood in ["Happy", "Excited", "Relaxed", "Grateful", "Calm", "Hopeful", "Motivated", "Curious", "Peaceful"]:
        return "POSITIVE"
    elif mood in ["Dull", "Neutral", "Tired", "Bored", "Lonely"]:
        return "NEUTRAL"
    elif mood in ["Angry", "Frustrated", "Anxious", "Stressed", "Overwhelmed"]:
        return "NEGATIVE"
    else:
        return "STRESSED"

# Function to suggest activities based on the mood
def suggest_activity(mood):
    category = map_mood_to_category(mood)
    resources = suggestion_database.get(category, {})
    return resources

# Streamlit app
def main():
    st.title("Mood Analysis and Suggestions")
    
    # Step 1: Display the questions
    st.write("Answer the following 3 questions to help us understand your mood:")
    responses = []
    for i, question in enumerate(questions, start=1):
        response = st.text_input(f"{i}. {question}")
        if response:
            responses.append(response)
    
    # Step 2: Analyze responses if all questions are answered
    if len(responses) == len(questions):
        combined_text = " ".join(responses)
        
        # Analyze responses to determine mood
        analysis_result = emotion_analyzer(combined_text)
        detected_emotion = analysis_result[0]['label']
        
        # Map detected emotion to a mood state
        detected_mood = random.choice(moods)  # Mock mapping for demonstration
        st.write(f"Detected Mood: {detected_mood}")
        
        # Step 3: Fetch suggestions based on mood
        resources = suggest_activity(detected_mood)
        
        # Display suggestions, articles, and videos
        st.write("Suggestions:")
        for suggestion in resources.get("suggestions", []):
            st.write(f"- {suggestion}")
        
        st.write("Articles:")
        for article in resources.get("articles", []):
            st.write(f"- [{article['title']}]({article['url']})")
        
        st.write("Videos:")
        for video in resources.get("videos", []):
            st.write(f"- [{video['title']}]({video['url']})")
    else:
        st.write("Please answer all questions to receive suggestions.")

if __name__ == "__main__":
    main()