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Models API

ModelDoctor relies on Pydantic models to guarantee data structure integrity throughout the pipeline.

Finding

Represents a final diagnosed issue after Confidence and Risk engines have processed the raw evidence.

class Finding(BaseModel):
    title: str
    description: str
    severity: Severity
    confidence: Confidence
    risk_score: float
    risk_level: str
    evidence: Dict[str, Any]
    structured_evidence: List[DiagnosticEvidence]
    tags: List[str]

DiagnosticEvidence

Represents raw signals collected by Doctors.

class DiagnosticEvidence(BaseModel):
    name: str
    measured_value: float
    expected_range: str
    weight: str
    normalized_score: float

ModelPassport

Snapshot of the model's footprint.

class ModelPassport(BaseModel):
    framework: str
    model_family: str
    training_samples: int
    feature_count: int
    model_size_bytes: int
    inference_latency_ms: float

Enums

Severity

INFO, WARNING, CRITICAL

Confidence

LOW, MEDIUM, HIGH

TaskType

BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, REGRESSION