nv_ingest_api.internal.schemas.extract package#

Submodules#

nv_ingest_api.internal.schemas.extract.extract_audio_schema module#

class nv_ingest_api.internal.schemas.extract.extract_audio_schema.AudioConfigSchema(
*,
auth_token: str | None = None,
audio_endpoints: Tuple[str | None, str | None] = (None, None),
audio_infer_protocol: str | None = None,
function_id: str | None = None,
use_ssl: bool | None = None,
ssl_cert: str | None = None,
)[source]#

Bases: BaseModel

Configuration schema for audio extraction endpoints and options.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • audio_endpoints (Tuple[str, str]) – A tuple containing the gRPC and HTTP services for the audio_retriever endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for each endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for any endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

class Config[source]#

Bases: object

extra = 'forbid'#
audio_endpoints: Tuple[str | None, str | None]#
audio_infer_protocol: str | None#
auth_token: str | None#
function_id: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

ssl_cert: str | None#
use_ssl: bool | None#
classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for all endpoints.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for any endpoint.

class nv_ingest_api.internal.schemas.extract.extract_audio_schema.AudioExtractorSchema(
*,
max_queue_size: int = 1,
n_workers: int = 16,
raise_on_failure: bool = False,
audio_extraction_config: AudioConfigSchema | None = None,
)[source]#

Bases: BaseModel

Configuration schema for the PDF extractor settings.

Parameters:

  • max_queue_size (int, default=1) – The maximum number of items allowed in the processing queue.

  • n_workers (int, default=16) – The number of worker threads to use for processing.

  • raise_on_failure (bool, default=False) – A flag indicating whether to raise an exception on processing failure.

  • audio_extraction_config (Optional[AudioConfigSchema], default=None) – Configuration schema for the audio extraction stage.

class Config[source]#

Bases: object

extra = 'forbid'#
audio_extraction_config: AudioConfigSchema | None#
max_queue_size: int#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

n_workers: int#
raise_on_failure: bool#

nv_ingest_api.internal.schemas.extract.extract_chart_schema module#

class nv_ingest_api.internal.schemas.extract.extract_chart_schema.ChartExtractorConfigSchema(
*,
auth_token: str | None = None,
yolox_endpoints: Tuple[str | None, str | None] = (None, None),
yolox_infer_protocol: str = '',
paddle_endpoints: Tuple[str | None, str | None] = (None, None),
paddle_infer_protocol: str = '',
nim_batch_size: int = 2,
workers_per_progress_engine: int = 5,
)[source]#

Bases: BaseModel

Configuration schema for chart extraction service endpoints and options.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • yolox_endpoints (Tuple[Optional[str], Optional[str]], default=(None, None)) – A tuple containing the gRPC and HTTP services for the yolox endpoint. Either the gRPC or HTTP service can be empty, but not both.

  • paddle_endpoints (Tuple[Optional[str], Optional[str]], default=(None, None)) – A tuple containing the gRPC and HTTP services for the paddle endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for each endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for any endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

auth_token: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

nim_batch_size: int#
paddle_endpoints: Tuple[str | None, str | None]#
paddle_infer_protocol: str#
classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for all endpoints.

Ensures that at least one service (either gRPC or HTTP) is provided for each endpoint in the configuration.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for any endpoint.

workers_per_progress_engine: int#
yolox_endpoints: Tuple[str | None, str | None]#
yolox_infer_protocol: str#
class nv_ingest_api.internal.schemas.extract.extract_chart_schema.ChartExtractorSchema(
*,
max_queue_size: int = 1,
n_workers: int = 2,
raise_on_failure: bool = False,
endpoint_config: ChartExtractorConfigSchema | None = None,
)[source]#

Bases: BaseModel

Configuration schema for chart extraction processing settings.

Parameters:

  • max_queue_size (int, default=1) – The maximum number of items allowed in the processing queue.

  • n_workers (int, default=2) – The number of worker threads to use for processing.

  • raise_on_failure (bool, default=False) – A flag indicating whether to raise an exception if a failure occurs during chart extraction.

  • extraction_config (Optional[ChartExtractorConfigSchema], default=None) – Configuration for the chart extraction stage, including yolox and paddle service endpoints.

classmethod check_positive(v, field)[source]#
endpoint_config: ChartExtractorConfigSchema | None#
max_queue_size: int#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

n_workers: int#
raise_on_failure: bool#

nv_ingest_api.internal.schemas.extract.extract_docx_schema module#

class nv_ingest_api.internal.schemas.extract.extract_docx_schema.DocxConfigSchema(
*,
auth_token: str | None = None,
yolox_endpoints: Tuple[str | None, str | None] = (None, None),
yolox_infer_protocol: str = '',
)[source]#

Bases: BaseModel

Configuration schema for docx extraction endpoints and options.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • yolox_endpoints (Tuple[str, str]) – A tuple containing the gRPC and HTTP services for the yolox endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for each endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for any endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

auth_token: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for all endpoints.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for any endpoint.

yolox_endpoints: Tuple[str | None, str | None]#
yolox_infer_protocol: str#
class nv_ingest_api.internal.schemas.extract.extract_docx_schema.DocxExtractorSchema(
*,
max_queue_size: int = 1,
n_workers: int = 16,
raise_on_failure: bool = False,
docx_extraction_config: DocxConfigSchema | None = None,
)[source]#

Bases: BaseModel

Configuration schema for the PDF extractor settings.

Parameters:

  • max_queue_size (int, default=1) – The maximum number of items allowed in the processing queue.

  • n_workers (int, default=16) – The number of worker threads to use for processing.

  • raise_on_failure (bool, default=False) – A flag indicating whether to raise an exception on processing failure.

  • image_extraction_config (Optional[ImageConfigSchema], default=None) – Configuration schema for the image extraction stage.

docx_extraction_config: DocxConfigSchema | None#
max_queue_size: int#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

n_workers: int#
raise_on_failure: bool#

nv_ingest_api.internal.schemas.extract.extract_image_schema module#

class nv_ingest_api.internal.schemas.extract.extract_image_schema.ImageConfigSchema(
*,
auth_token: str | None = None,
yolox_endpoints: Tuple[str | None, str | None] = (None, None),
yolox_infer_protocol: str = '',
)[source]#

Bases: BaseModel

Configuration schema for image extraction endpoints and options.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • yolox_endpoints (Tuple[str, str]) – A tuple containing the gRPC and HTTP services for the yolox endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for each endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for any endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

auth_token: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for all endpoints.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for any endpoint.

yolox_endpoints: Tuple[str | None, str | None]#
yolox_infer_protocol: str#
class nv_ingest_api.internal.schemas.extract.extract_image_schema.ImageExtractorSchema(
*,
max_queue_size: int = 1,
n_workers: int = 16,
raise_on_failure: bool = False,
image_extraction_config: ImageConfigSchema | None = None,
)[source]#

Bases: BaseModel

Configuration schema for the PDF extractor settings.

Parameters:

  • max_queue_size (int, default=1) – The maximum number of items allowed in the processing queue.

  • n_workers (int, default=16) – The number of worker threads to use for processing.

  • raise_on_failure (bool, default=False) – A flag indicating whether to raise an exception on processing failure.

  • image_extraction_config (Optional[ImageConfigSchema], default=None) – Configuration schema for the image extraction stage.

image_extraction_config: ImageConfigSchema | None#
max_queue_size: int#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

n_workers: int#
raise_on_failure: bool#

nv_ingest_api.internal.schemas.extract.extract_infographic_schema module#

class nv_ingest_api.internal.schemas.extract.extract_infographic_schema.InfographicExtractorConfigSchema(
*,
auth_token: str | None = None,
paddle_endpoints: Tuple[str | None, str | None] = (None, None),
paddle_infer_protocol: str = '',
nim_batch_size: int = 2,
workers_per_progress_engine: int = 5,
)[source]#

Bases: BaseModel

Configuration schema for infographic extraction service endpoints and options.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • paddle_endpoints (Tuple[Optional[str], Optional[str]], default=(None, None)) – A tuple containing the gRPC and HTTP services for the paddle endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for each endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for any endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

auth_token: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

nim_batch_size: int#
paddle_endpoints: Tuple[str | None, str | None]#
paddle_infer_protocol: str#
classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for all endpoints.

Ensures that at least one service (either gRPC or HTTP) is provided for each endpoint in the configuration.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for any endpoint.

workers_per_progress_engine: int#
class nv_ingest_api.internal.schemas.extract.extract_infographic_schema.InfographicExtractorSchema(
*,
max_queue_size: int = 1,
n_workers: int = 2,
raise_on_failure: bool = False,
endpoint_config: InfographicExtractorConfigSchema | None = None,
)[source]#

Bases: BaseModel

Configuration schema for infographic extraction processing settings.

Parameters:

  • max_queue_size (int, default=1) – The maximum number of items allowed in the processing queue.

  • n_workers (int, default=2) – The number of worker threads to use for processing.

  • raise_on_failure (bool, default=False) – A flag indicating whether to raise an exception if a failure occurs during infographic extraction.

  • stage_config (Optional[InfographicExtractorConfigSchema], default=None) – Configuration for the infographic extraction stage, including yolox and paddle service endpoints.

classmethod check_positive(v, field)[source]#
endpoint_config: InfographicExtractorConfigSchema | None#
max_queue_size: int#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

n_workers: int#
raise_on_failure: bool#

nv_ingest_api.internal.schemas.extract.extract_pdf_schema module#

class nv_ingest_api.internal.schemas.extract.extract_pdf_schema.NemoRetrieverParseConfigSchema(
*,
auth_token: str | None = None,
yolox_endpoints: Tuple[str | None, str | None] = (None, None),
yolox_infer_protocol: str = '',
nemoretriever_parse_endpoints: Tuple[str | None, str | None] = (None, None),
nemoretriever_parse_infer_protocol: str = '',
nemoretriever_parse_model_name: str = 'nvidia/nemoretriever-parse',
timeout: float = 300.0,
workers_per_progress_engine: int = 5,
)[source]#

Bases: BaseModel

Configuration schema for NemoRetrieverParse endpoints and options.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • nemoretriever_parse_endpoints (Tuple[str, str]) – A tuple containing the gRPC and HTTP services for the nemoretriever_parse endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for each endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for any endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

auth_token: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

nemoretriever_parse_endpoints: Tuple[str | None, str | None]#
nemoretriever_parse_infer_protocol: str#
nemoretriever_parse_model_name: str#
timeout: float#
classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for all endpoints.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for any endpoint.

workers_per_progress_engine: int#
yolox_endpoints: Tuple[str | None, str | None]#
yolox_infer_protocol: str#
class nv_ingest_api.internal.schemas.extract.extract_pdf_schema.PDFExtractorSchema(
*,
max_queue_size: int = 1,
n_workers: int = 16,
raise_on_failure: bool = False,
pdfium_config: PDFiumConfigSchema | None = None,
nemoretriever_parse_config: NemoRetrieverParseConfigSchema | None = None,
)[source]#

Bases: BaseModel

Configuration schema for the PDF extractor settings.

Parameters:

  • max_queue_size (int, default=1) – The maximum number of items allowed in the processing queue.

  • n_workers (int, default=16) – The number of worker threads to use for processing.

  • raise_on_failure (bool, default=False) – A flag indicating whether to raise an exception on processing failure.

  • pdfium_config (Optional[PDFiumConfigSchema], default=None) – Configuration for the PDFium service endpoints.

max_queue_size: int#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

n_workers: int#
nemoretriever_parse_config: NemoRetrieverParseConfigSchema | None#
pdfium_config: PDFiumConfigSchema | None#
raise_on_failure: bool#
class nv_ingest_api.internal.schemas.extract.extract_pdf_schema.PDFiumConfigSchema(
*,
auth_token: str | None = None,
yolox_endpoints: Tuple[str | None, str | None] = (None, None),
yolox_infer_protocol: str = '',
nim_batch_size: int = 4,
workers_per_progress_engine: int = 5,
)[source]#

Bases: BaseModel

Configuration schema for PDFium endpoints and options.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • yolox_endpoints (Tuple[str, str]) – A tuple containing the gRPC and HTTP services for the yolox endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for each endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for any endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

auth_token: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

nim_batch_size: int#
classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for all endpoints.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for any endpoint.

workers_per_progress_engine: int#
yolox_endpoints: Tuple[str | None, str | None]#
yolox_infer_protocol: str#

nv_ingest_api.internal.schemas.extract.extract_pptx_schema module#

class nv_ingest_api.internal.schemas.extract.extract_pptx_schema.PPTXConfigSchema(
*,
auth_token: str | None = None,
yolox_endpoints: Tuple[str | None, str | None] = (None, None),
yolox_infer_protocol: str = '',
)[source]#

Bases: BaseModel

Configuration schema for docx extraction endpoints and options.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • yolox_endpoints (Tuple[str, str]) – A tuple containing the gRPC and HTTP services for the yolox endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for each endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for any endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

auth_token: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for all endpoints.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for any endpoint.

yolox_endpoints: Tuple[str | None, str | None]#
yolox_infer_protocol: str#
class nv_ingest_api.internal.schemas.extract.extract_pptx_schema.PPTXExtractorSchema(
*,
max_queue_size: int = 1,
n_workers: int = 16,
raise_on_failure: bool = False,
pptx_extraction_config: PPTXConfigSchema | None = None,
)[source]#

Bases: BaseModel

Configuration schema for the PDF extractor settings.

Parameters:

  • max_queue_size (int, default=1) – The maximum number of items allowed in the processing queue.

  • n_workers (int, default=16) – The number of worker threads to use for processing.

  • raise_on_failure (bool, default=False) – A flag indicating whether to raise an exception on processing failure.

  • image_extraction_config (Optional[ImageConfigSchema], default=None) – Configuration schema for the image extraction stage.

max_queue_size: int#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

n_workers: int#
pptx_extraction_config: PPTXConfigSchema | None#
raise_on_failure: bool#

nv_ingest_api.internal.schemas.extract.extract_table_schema module#

class nv_ingest_api.internal.schemas.extract.extract_table_schema.TableExtractorConfigSchema(
*,
auth_token: str | None = None,
yolox_endpoints: Tuple[str | None, str | None] = (None, None),
yolox_infer_protocol: str = '',
paddle_endpoints: Tuple[str | None, str | None] = (None, None),
paddle_infer_protocol: str = '',
nim_batch_size: int = 2,
workers_per_progress_engine: int = 5,
)[source]#

Bases: BaseModel

Configuration schema for the table extraction stage settings.

Parameters:

  • auth_token (Optional[str], default=None) – Authentication token required for secure services.

  • paddle_endpoints (Tuple[Optional[str], Optional[str]], default=(None, None)) – A tuple containing the gRPC and HTTP services for the paddle endpoint. Either the gRPC or HTTP service can be empty, but not both.

validate_endpoints(values)[source]#

Validates that at least one of the gRPC or HTTP services is provided for the yolox endpoint.

Raises:

  • ValueError – If both gRPC and HTTP services are empty for the yolox endpoint.

  • Config –

  • ------ –

:raises extra : str: Pydantic config option to forbid extra fields.

auth_token: str | None#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

nim_batch_size: int#
paddle_endpoints: Tuple[str | None, str | None]#
paddle_infer_protocol: str#
classmethod validate_endpoints(values)[source]#

Validates the gRPC and HTTP services for the yolox endpoint.

Parameters:

values (dict) – Dictionary containing the values of the attributes for the class.

Returns:

The validated dictionary of values.

Return type:

dict

Raises:

ValueError – If both gRPC and HTTP services are empty for the yolox endpoint.

workers_per_progress_engine: int#
yolox_endpoints: Tuple[str | None, str | None]#
yolox_infer_protocol: str#
class nv_ingest_api.internal.schemas.extract.extract_table_schema.TableExtractorSchema(
*,
max_queue_size: int = 1,
n_workers: int = 2,
raise_on_failure: bool = False,
endpoint_config: TableExtractorConfigSchema | None = None,
)[source]#

Bases: BaseModel

Configuration schema for the table extraction processing settings.

Parameters:

  • max_queue_size (int, default=1) – The maximum number of items allowed in the processing queue.

  • n_workers (int, default=2) – The number of worker threads to use for processing.

  • raise_on_failure (bool, default=False) – A flag indicating whether to raise an exception if a failure occurs during table extraction.

  • stage_config (Optional[TableExtractorConfigSchema], default=None) – Configuration for the table extraction stage, including yolox service endpoints.

classmethod check_positive(v, field)[source]#
endpoint_config: TableExtractorConfigSchema | None#
max_queue_size: int#
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}#

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

n_workers: int#
raise_on_failure: bool#

Module contents#

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