"""
Step 3 Left Panel: Predefined Metrics
"""
import streamlit as st

def render_step3_left():
    """Render the left panel for Step 3: Predefined Metrics"""
    st.markdown("### 📊 Available Metrics")
    st.markdown("Select which therapeutic metrics to evaluate:")
    
    # Get available metrics from registry
    from evaluators import list_available_metrics, get_metrics_by_category, get_metric_metadata
    
    available_metrics = list_available_metrics()
    metrics_by_category = get_metrics_by_category()
    
    selected_metrics = []
    
    # Display metrics grouped by category
    if metrics_by_category:
        for category, metric_keys in metrics_by_category.items():
            if category:
                st.markdown(f"**{category}**")
            for metric_key in metric_keys:
                metadata = get_metric_metadata(metric_key)
                if metadata:
                    label = metadata.label
                    description = metadata.description
                    help_text = description if description else None
                    
                    if st.checkbox(
                        label, 
                        value=st.session_state.get(f'metric_{metric_key}', False), 
                        key=f'metric_{metric_key}',
                        help=help_text
                    ):
                        selected_metrics.append(metric_key)
    else:
        # Fallback: display all metrics without categories
        for metric_key in available_metrics:
            metadata = get_metric_metadata(metric_key)
            label = metadata.label if metadata else metric_key.replace('_', ' ').title()
            description = metadata.description if metadata else None
            
            if st.checkbox(
                label, 
                value=st.session_state.get(f'metric_{metric_key}', False), 
                key=f'metric_{metric_key}',
                help=description
            ):
                selected_metrics.append(metric_key)
    
    st.session_state.selected_metrics = selected_metrics
    
    # Validation message for metrics
    if not selected_metrics:
        st.warning("⚠️ Please select at least one metric.")
    else:
        st.success(f"✅ {len(selected_metrics)} metric(s) selected")
    
    return selected_metrics