features/sentiment/feedback.py

"""피드백 통계 섹션.

사용자 검증 현황 (Human-in-the-Loop).
"""
import pandas as pd
import streamlit as st

from core.utils import get_feedback_reason_label, get_feedback_type_emoji


def render_feedback_stats(feedback_stats: dict):
    """피드백 통계 섹션 렌더링."""
    if not feedback_stats or feedback_stats.get("total_feedback", 0) == 0:
        return

    with st.expander("📝 **피드백 분석** - 사용자 검증 현황", expanded=False):
        fb_total = feedback_stats.get("total_feedback", 0)
        fb_correct = feedback_stats.get("correct_count", 0)
        fb_wrong = feedback_stats.get("wrong_count", 0)
        fb_ambiguous = feedback_stats.get("ambiguous_count", 0)
        accuracy = feedback_stats.get("accuracy_rate", 0)

        fb_col1, fb_col2, fb_col3, fb_col4, fb_col5 = st.columns(5)

        with fb_col1:
            st.metric(label="총 피드백", value=f"{fb_total}건", help="사용자가 제출한 총 피드백 수")
        with fb_col2:
            st.metric(
                label="👍 정확", value=f"{fb_correct}건",
                delta=f"{fb_correct/fb_total*100:.0f}%" if fb_total > 0 else None,
                delta_color="normal", help="정확하다고 평가된 분석 수",
            )
        with fb_col3:
            st.metric(
                label="👎 오류", value=f"{fb_wrong}건",
                delta=f"{fb_wrong/fb_total*100:.0f}%" if fb_total > 0 else None,
                delta_color="inverse", help="틀렸다고 평가된 분석 수",
            )
        with fb_col4:
            st.metric(label="🤔 애매", value=f"{fb_ambiguous}건", help="판단하기 어려운 경우")
        with fb_col5:
            st.metric(label="정확도", value=f"{accuracy:.1f}%", help="correct / (correct + wrong) x 100")

        wrong_reasons = feedback_stats.get("wrong_reasons", {})
        if wrong_reasons:
            st.markdown("##### 오류 원인 분포")
            reason_df = pd.DataFrame([
                {"원인": get_feedback_reason_label(k), "건수": v}
                for k, v in wrong_reasons.items()
            ]).sort_values("건수", ascending=False)
            st.dataframe(reason_df, use_container_width=True, hide_index=True)

        recent_feedback = feedback_stats.get("recent_feedback", [])
        if recent_feedback:
            st.markdown("##### 최근 피드백 (10건)")
            recent_df = pd.DataFrame([
                {
                    "Answer ID": fb.get("answer_id"),
                    "유형": get_feedback_type_emoji(fb.get("feedback_type", "")),
                    "원인": get_feedback_reason_label(fb.get("wrong_reason")) if fb.get("wrong_reason") else "-",
                    "코멘트": fb.get("comment", "-")[:50] + "..." if fb.get("comment") and len(fb.get("comment", "")) > 50 else fb.get("comment", "-"),
                    "시간": fb.get("created_at", "")[:16].replace("T", " ") if fb.get("created_at") else "-",
                }
                for fb in recent_feedback
            ])
            st.dataframe(recent_df, use_container_width=True, hide_index=True)