from typing import Dict, List
import streamlit as st


def create_radar_chart(scores: Dict[str, float], title: str):
    import plotly.graph_objects as go
    categories = list(scores.keys())
    values = list(scores.values())
    fig = go.Figure()
    fig.add_trace(go.Scatterpolar(r=values, theta=categories, fill='toself', name=title, line_color='blue'))
    fig.update_layout(polar=dict(radialaxis=dict(visible=True, range=[0, 2])), showlegend=True, title=title, font_size=12)
    return fig


def display_utterance_results(results: List[Dict]):
    st.subheader("Utterance-Level Results")
    for i, result in enumerate(results):
        with st.expander(f"Utterance {i+1}: {result['speaker']}"):
            st.write(f"**Text:** {result['text']}")
            
            # Collect all scores
            all_scores = {}
            
            # OpenAI scores
            if result.get('openai_scores'):
                all_scores['OpenAI'] = result['openai_scores']
            
            # Empathy scores
            empathy_scores = result.get('empathy_scores') or result.get('huggingface_scores')
            if empathy_scores:
                all_scores['Empathy'] = empathy_scores
            
            # Talk Type scores
            if result.get('talk_type_scores'):
                all_scores['Talk Type'] = result['talk_type_scores']
            
            # Display scores in columns
            if all_scores:
                cols = st.columns(len(all_scores))
                for idx, (eval_name, scores) in enumerate(all_scores.items()):
                    with cols[idx]:
                        st.write(f"**{eval_name} Scores:**")
                        for metric, score in scores.items():
                            st.metric(metric.replace('_', ' ').title(), f"{float(score):.2f}/2")
            else:
                st.write("No scores available")