core/utils.py

"""Utility functions for Gen3 Nudge Detection Dashboard."""

# Confidence tier thresholds
CONFIDENCE_HIGH_THRESHOLD = 0.85
CONFIDENCE_MEDIUM_THRESHOLD = 0.70


def get_confidence_tier(confidence: float | None) -> tuple[str, str, str]:
    """Get confidence tier info for nudge candidates.

    Returns:
        Tuple of (tier, emoji, description)
    """
    if confidence is None:
        return "LOW", "🟢", "오탐 가능성"
    if confidence >= CONFIDENCE_HIGH_THRESHOLD:
        return "HIGH", "🔴", "확실한 넛지 대상"
    elif confidence >= CONFIDENCE_MEDIUM_THRESHOLD:
        return "MEDIUM", "🟡", "검토 필요"
    return "LOW", "🟢", "오탐 가능성"


def truncate_text(text: str | None, max_length: int, suffix: str = "...") -> str:
    """Truncate text to max_length with suffix."""
    if not text:
        return "N/A"
    if len(text) <= max_length:
        return text
    return text[:max_length] + suffix


def format_brands_list(brands: list[str] | None) -> str:
    """Format list of brands for display."""
    if not brands:
        return "N/A"
    return ", ".join(brands)


def highlight_evidence_spans(text: str, evidence_spans: list[dict] | None) -> str:
    """Highlight evidence spans in text using HTML.

    Args:
        text: Full answer text
        evidence_spans: List of evidence span dicts with text, start, end, type

    Returns:
        HTML string with highlighted spans
    """
    if not evidence_spans or not text:
        return text or ""

    # Sort spans by start position (descending) to avoid index shifting
    sorted_spans = sorted(
        [s for s in evidence_spans if s.get("text")],
        key=lambda s: s.get("start", 0) if s.get("start") is not None else -1,
        reverse=True,
    )

    result = text
    for span in sorted_spans:
        span_text = span.get("text", "")
        span_type = span.get("type", "negative")
        start = span.get("start")
        end = span.get("end")

        # Color by type
        color_map = {
            "negative": "#FF6B6B",
            "positive": "#51CF66",
            "neutral": "#748FFC",
            "comparison": "#FAB005",
            "hallucination": "#ADB5BD",
            "category_general": "#9775FA",
        }
        color = color_map.get(span_type, "#ADB5BD")

        mark_style = f'background-color: {color}; padding: 2px 4px; border-radius: 3px;'

        mark_style = f'background-color: {color}; padding: 2px 4px; border-radius: 3px;'

        if start is not None and end is not None and 0 <= start < end <= len(result):
            # Use exact positions
            before = result[:start]
            highlighted = f'<mark style="{mark_style}">{result[start:end]}</mark>'
            after = result[end:]
            result = before + highlighted + after
        elif span_text and span_text in result:
            # Fallback: find text in result
            highlighted = f'<mark style="{mark_style}">{span_text}</mark>'
            result = result.replace(span_text, highlighted, 1)
        elif span_text and "..." in span_text:
            # Ellipsis fallback: LLM truncated the evidence with "..."
            # Split into fragments and highlight each one found in the text
            fragments = [f.strip() for f in span_text.split("...") if f.strip()]
            for frag in fragments:
                if frag in result:
                    highlighted = f'<mark style="{mark_style}">{frag}</mark>'
                    result = result.replace(frag, highlighted, 1)

    return result


def get_llm_tier_badge(adjusted_tier: str | None, is_negative: bool | None) -> tuple[str, str]:
    """Get badge info for LLM verification result.

    Returns:
        Tuple of (badge_text, badge_color)
    """
    if adjusted_tier is None:
        return "미검증", "gray"

    if adjusted_tier == "NONE" or is_negative is False:
        return "✅ 오탐 (False Positive)", "green"

    tier_map = {
        "HIGH": ("🔴 부정 확인 (HIGH)", "red"),
        "MEDIUM": ("🟡 부정 확인 (MEDIUM)", "orange"),
        "LOW": ("🟢 부정 확인 (LOW)", "blue"),
    }
    return tier_map.get(adjusted_tier, ("확인됨", "gray"))


def get_feedback_reason_label(reason: str | None) -> str:
    """Get human-readable label for feedback wrong_reason."""
    reason_labels = {
        "actually_positive": "실제로는 긍정적인 내용입니다",
        "actually_neutral": "실제로는 중립적인 내용입니다",
        "wrong_evidence": "근거 문장이 잘못 추출되었습니다",
        "context_missing": "맥락이 빠져서 오해가 있습니다",
        "wrong_brand": "브랜드가 잘못 인식되었습니다",
        "other": "기타",
    }
    return reason_labels.get(reason, reason or "")


def get_feedback_type_emoji(feedback_type: str | None) -> str:
    """Get emoji for feedback type."""
    emoji_map = {
        "correct": "👍",
        "wrong": "👎",
        "ambiguous": "🤔",
    }
    return emoji_map.get(feedback_type, "")