import streamlit as st
import os

# Set Page Configuration
st.set_page_config(
    page_title="Emotion Prediction App",
    page_icon="🌟",
    layout="wide",
)

# Custom CSS for Background and Styling
def add_custom_styles():
    st.markdown("""
        <style>
            /* Background Styling */
            .stApp {
                background: linear-gradient(to right, #f2f7ff, #d9faff);
                color: #333333;
                font-family: Arial, sans-serif;
            }

            /* Header Styling */
            .main-title {
                color: #1e88e5;
                text-align: center;
                font-size: 3rem;
                margin-top: -20px;
                margin-bottom: 30px;
                font-weight: bold;
            }

            /* Section Headers */
            .section-header {
                color: #0d47a1;
                font-size: 1.8rem;
                margin-top: 20px;
                margin-bottom: 10px;
                border-bottom: 2px solid #1e88e5;
            }

            /* Suggestions Styling */
            .suggestions {
                font-size: 1.1rem;
                line-height: 1.6;
            }

            /* Footer Styling */
            .footer {
                text-align: center;
                margin-top: 50px;
                font-size: 0.9rem;
                color: #555;
            }
        </style>
    """, unsafe_allow_html=True)

add_custom_styles()

# Debugging Logger
def debug_log(message):
    st.sidebar.text(f"DEBUG: {message}")

# Suggestion Database
suggestion_database = {
    "sadness": {
        "suggestions": ["Try guided meditation", "Take a walk in nature", "Connect with a friend"],
        "articles": [
            {"title": "Overcoming Sadness", "url": "https://example.com/sadness1"},
            {"title": "Understanding Depression", "url": "https://example.com/sadness2"},
        ],
        "videos": [
            {"title": "Mindfulness for Sadness", "url": "https://www.youtube.com/watch?v=sadnessvideo1"},
            {"title": "Coping with Grief", "url": "https://www.youtube.com/watch?v=sadnessvideo2"},
        ],
    },
    "joy": {
        "suggestions": ["Practice gratitude", "Engage in a hobby", "Spend time with loved ones"],
        "articles": [
            {"title": "The Benefits of Joy", "url": "https://example.com/joy1"},
            {"title": "Maintaining Positive Emotions", "url": "https://example.com/joy2"},
        ],
        "videos": [
            {"title": "Boosting Your Happiness", "url": "https://www.youtube.com/watch?v=joyvideo1"},
            {"title": "Practicing Gratitude", "url": "https://www.youtube.com/watch?v=joyvideo2"},
        ],
    },
    "neutral": {
        "suggestions": ["Take a break", "Engage in a relaxing activity", "Spend time in nature"],
        "articles": [
            {"title": "Importance of Self-Care", "url": "https://example.com/selfcare1"},
            {"title": "Stress Management Techniques", "url": "https://example.com/stress1"},
        ],
        "videos": [
            {"title": "Relaxation Techniques", "url": "https://www.youtube.com/watch?v=relaxvideo1"},
            {"title": "Mindfulness Exercises", "url": "https://www.youtube.com/watch?v=mindfulnessvideo1"},
        ],
    },
}

# Function to Fetch Relevant Suggestions
def get_relevant_resources(emotion):
    return suggestion_database.get(emotion, suggestion_database["neutral"])

# Placeholder for Model Loading
def load_emotion_model(model_path):
    try:
        if not os.path.exists(model_path):
            raise FileNotFoundError(f"Model file not found at {model_path}")
        debug_log("Model loaded successfully.")
        return "Emotion Model Placeholder"
    except Exception as e:
        debug_log(str(e))
        return None

# Main Application Header
st.markdown('<div class="main-title">Emotion Prediction & Suggestions 🌈</div>', unsafe_allow_html=True)
st.markdown("""
This app is designed to help you discover activities, articles, and videos tailored to your emotional state.  
Simply describe how you're feeling, and let us provide uplifting and insightful suggestions.  
""")

# Sidebar for Model Path Input
st.sidebar.header("Emotion Model Configuration")
model_path = st.sidebar.text_input("Enter the Path to the Emotion Prediction Model", "path/to/model")

# Load Emotion Prediction Model
emotion_model = load_emotion_model(model_path)
if emotion_model is None:
    st.sidebar.error("Model failed to load. Please check the path or contact support.")

# Emotion Analysis Section
st.markdown('<div class="section-header">How Are You Feeling Today?</div>', unsafe_allow_html=True)
user_response = st.text_input("Describe your current emotion (e.g., happy, sad, neutral):", "neutral")

# Display Suggestions
if user_response:
    resources = get_relevant_resources(user_response.lower())
    st.markdown('<div class="section-header">Here Are Some Suggestions for You:</div>', unsafe_allow_html=True)

    # Suggestions
    st.markdown("#### Activities:")
    st.markdown('<div class="suggestions">', unsafe_allow_html=True)
    for suggestion in resources["suggestions"]:
        st.write(f"- {suggestion}")
    st.markdown('</div>', unsafe_allow_html=True)

    # Articles
    st.markdown("#### Articles:")
    for article in resources["articles"]:
        st.write(f"- [{article['title']}]({article['url']})")

    # Videos
    st.markdown("#### Videos:")
    for video in resources["videos"]:
        st.write(f"- [{video['title']}]({video['url']})")

# Footer
st.markdown('<div class="footer">Crafted with ❤️ by Your Emotion App Team</div>', unsafe_allow_html=True)