src.asqi.response_schemas¶

Classes¶

`GeneratedDataset`	Represents a dataset produced by a container during execution.
`GeneratedReport`	Runtime output for a generated report.
`ContainerOutput`	Complete container output schema.

Functions¶

validate_container_output(→ ContainerOutput)

Validate container output against the schema.

Module Contents¶

class src.asqi.response_schemas.GeneratedDataset(/, **data: Any)¶

Bases: pydantic.BaseModel

Represents a dataset produced by a container during execution. The paths are container-internal and get translated to host paths by the workflow system.

dataset_name: str = None¶

dataset_type: Literal['huggingface', 'pdf', 'txt'] = None¶

dataset_path: str = None¶

format: str | None = None¶

metadata: Dict[str, Any] | None = None¶

classmethod validate_path_not_empty(v: str) → str¶: Validate that dataset_path is not empty or whitespace-only.

classmethod validate_name_not_empty(v: str) → str¶: Validate that dataset_name is not empty or whitespace-only.

class src.asqi.response_schemas.GeneratedReport(/, **data: Any)¶

Bases: pydantic.BaseModel

Runtime output for a generated report.

Represents a report (HTML, PDF, JSON, etc.) produced by a container during execution. The paths are container-internal and get translated to host paths by the workflow system.

report_name: str = None¶

report_type: Literal['html', 'pdf', 'json'] = None¶

report_path: str = None¶

metadata: Dict[str, Any] | None = None¶

classmethod validate_path_not_empty(v: str) → str¶: Validate that report_path is not empty or whitespace-only.

classmethod validate_name_not_empty(v: str) → str¶: Validate that report_name is not empty or whitespace-only.

class src.asqi.response_schemas.ContainerOutput(/, **data: Any)¶

Bases: pydantic.BaseModel

Complete container output schema.

Supports both ‘results’ (recommended) and ‘test_results’ (legacy) field names for backward compatibility.

results: Dict[str, Any] | None = None¶

test_results: Dict[str, Any] | None = None¶

generated_reports: List[GeneratedReport] = None¶

generated_datasets: List[GeneratedDataset] = None¶

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod validate_results_not_empty_if_present(v: Dict[str, Any] | None) → Dict[str, Any] | None¶

Ensure results field is not empty if present.

At least one results field must contain the ‘success’ key.

get_results() → Dict[str, Any]¶

Get results, preferring ‘results’ over ‘test_results’.

Returns:: Results dictionary, preferring ‘results’ field over ‘test_results’. Returns empty dict if neither field is present.

src.asqi.response_schemas.validate_container_output(output_dict: Dict[str, Any]) → ContainerOutput¶

Validate container output against the schema.

It supports both ‘results’ (recommended) and ‘test_results’ (legacy) field names for backward compatibility.

Args:

output_dict: Raw container output dictionary parsed from JSON

Returns:

Validated ContainerOutput object

Raises:

ValidationError: If output doesn’t match schema (missing required fields,: invalid types, etc.)

ValueError: If neither ‘results’ nor ‘test_results’ field is present