from __future__ import annotations

from typing import Any



def estimate_uncertainty(message: str, analysis: dict[str, Any], family_candidates: list[dict[str, Any]] | None = None) -> dict[str, Any]:
    candidates = [str((item or {}).get('family') or '') for item in (family_candidates or []) if (item or {}).get('family')]
    confidence = float(analysis.get('confidence', 0.0) or 0.0)
    score = 0.0
    reasons: list[str] = []
    if len(set(candidates)) >= 2:
        score += 0.35
        reasons.append('multiple_family_candidates')
    if confidence < 0.75:
        score += 0.4
        reasons.append('low_confidence')
    elif confidence < 0.9:
        score += 0.2
        reasons.append('medium_confidence')
    if analysis.get('needs_memory') and analysis.get('needs_setup_context'):
        score += 0.15
        reasons.append('mixed_memory_and_setup')
    if 'http' in (message or '').lower() and analysis.get('task_type') not in {'summarize', 'research'}:
        score += 0.1
        reasons.append('url_in_non_research_query')
    if analysis.get('composition_reason'):
        score += 0.1
        reasons.append('composed_path')

    if score >= 0.65:
        level = 'high'
    elif score >= 0.3:
        level = 'medium'
    else:
        level = 'low'
    return {'level': level, 'score': round(score, 3), 'reasons': reasons}