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630d650 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | import datetime as _dt
import uuid
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
CANCER_RISK_TEMPLATE_COLUMNS: List[str] = [
"record_id",
"chemical_name",
"casrn",
"route",
"exposure_value",
"exposure_unit",
"body_weight_kg",
"csf_value",
"csf_unit",
"iur_value",
"air_conc_value",
"air_conc_unit",
"source_reference",
]
def default_run_id(prefix: str = "run") -> str:
ts = _dt.datetime.utcnow().strftime("%Y%m%d_%H%M%S")
return f"{prefix}_{ts}_{uuid.uuid4().hex[:8]}"
@dataclass
class RegulatoryClause:
clause_id: str
framework: str
title: str
description: str
required_fields: List[str] = field(default_factory=list)
required_evidence_terms: List[str] = field(default_factory=list)
acceptance_rule: str = "all_required_fields"
applicability: Dict[str, Any] = field(default_factory=dict)
source_reference: str = ""
@dataclass
class ClauseEvaluation:
clause_id: str
framework: str
status: str
fields_present: List[str] = field(default_factory=list)
missing_fields: List[str] = field(default_factory=list)
evidence_hits: List[str] = field(default_factory=list)
prompt: str = ""
reason: str = ""
RISK_TIER_THRESHOLDS = {
"low": 1e-6,
"moderate": 1e-4,
}
def classify_risk_tier(value: Optional[float]) -> str:
if value is None:
return "unknown"
if value < RISK_TIER_THRESHOLDS["low"]:
return "de_minimis"
if value <= RISK_TIER_THRESHOLDS["moderate"]:
return "monitor"
return "high_priority"
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