38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
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from __future__ import annotations
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from typing import Any
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def estimate_uncertainty(message: str, analysis: dict[str, Any], family_candidates: list[dict[str, Any]] | None = None) -> dict[str, Any]:
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candidates = [str((item or {}).get('family') or '') for item in (family_candidates or []) if (item or {}).get('family')]
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confidence = float(analysis.get('confidence', 0.0) or 0.0)
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score = 0.0
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reasons: list[str] = []
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if len(set(candidates)) >= 2:
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score += 0.35
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reasons.append('multiple_family_candidates')
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if confidence < 0.75:
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score += 0.4
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reasons.append('low_confidence')
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elif confidence < 0.9:
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score += 0.2
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reasons.append('medium_confidence')
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if analysis.get('needs_memory') and analysis.get('needs_setup_context'):
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score += 0.15
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reasons.append('mixed_memory_and_setup')
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if 'http' in (message or '').lower() and analysis.get('task_type') not in {'summarize', 'research'}:
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score += 0.1
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reasons.append('url_in_non_research_query')
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if analysis.get('composition_reason'):
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score += 0.1
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reasons.append('composed_path')
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if score >= 0.65:
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level = 'high'
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elif score >= 0.3:
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level = 'medium'
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else:
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level = 'low'
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return {'level': level, 'score': round(score, 3), 'reasons': reasons}
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