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9c1c0ef | 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 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | from __future__ import annotations
from enum import StrEnum
from typing import Any
from pydantic import BaseModel, Field
class TaskType(StrEnum):
classification = "classification"
regression = "regression"
class Severity(StrEnum):
info = "info"
warning = "warning"
critical = "critical"
class Evidence(BaseModel):
evidence_id: str
claim: str
metric: str
value: float | int | str
source: str
method: str
class QualityIssue(BaseModel):
code: str
severity: Severity
column: str | None = None
message: str
evidence_ids: list[str] = Field(default_factory=list)
class DatasetProfile(BaseModel):
rows: int
columns: int
numeric_columns: list[str]
categorical_columns: list[str]
datetime_columns: list[str]
duplicate_rows: int
missing_cells: int
missing_rate: float
memory_mb: float
target: str
task_type: TaskType
target_cardinality: int
class AnalysisPlan(BaseModel):
objective: str
target: str
task_type: TaskType
primary_metric: str
validation_strategy: str
candidate_models: list[str]
risk_controls: list[str]
class ModelResult(BaseModel):
name: str
primary_metric: str
primary_score: float
metrics: dict[str, float]
cross_validation_mean: float | None = None
cross_validation_std: float | None = None
training_seconds: float
selection_score: float | None = None
final_test_score: float | None = None
final_test_metrics: dict[str, float] = Field(default_factory=dict)
class ModelFailure(BaseModel):
name: str
stage: str
exception_category: str
sanitized_error: str
training_seconds: float
expected: bool = False
class CriticDecision(BaseModel):
approved: bool
score: float
threshold: float
reasons: list[str]
retry_number: int
class ExplainabilityResult(BaseModel):
method: str
feature_importance: dict[str, float]
caveats: list[str]
class RunSummary(BaseModel):
run_id: str
status: str
dataset_name: str
profile: DatasetProfile
plan: AnalysisPlan
quality_issues: list[QualityIssue]
evidence: list[Evidence]
model_results: list[ModelResult]
model_failures: list[ModelFailure] = Field(default_factory=list)
best_model: str
critic: CriticDecision
explainability: ExplainabilityResult
executive_summary: list[str]
recommendations: list[str]
artifacts: dict[str, str]
trace: list[dict[str, Any]]
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