Extraction Params

Extraction Parameters

class ExtractionParameters(model_id, alias=None, webhook_ids=None, polling_options=None, close_file=True, rag=None, raw_text=None, polygon=None, confidence=None, text_context=None, data_schema=None)

Parameters for sending a file to an Extraction product.

Parameters:

  • model_id (str)

  • alias (str | None)

  • webhook_ids (list[str] | None)

  • polling_options (PollingOptions | None)

  • close_file (bool)

  • rag (bool | None)

  • raw_text (bool | None)

  • polygon (bool | None)

  • confidence (bool | None)

  • text_context (str | None)

  • data_schema (DataSchema | str | dict | None)

classmethod get_enqueue_slug()

Getter for the enqueue slug.

Return type:

str

get_request_parameters()

Return the parameters as a config dictionary.

Return type:

dict[str, str | list[str]]

Returns:

A dict of parameters.

alias: str | None = None

Optional: a free-form string to tag the request with your own identifier. For example, an internal document ID, reference number, or database key. If set, it will be included in the job and result responses.

close_file: bool = True

Whether to close the file after product.

confidence: bool | None = None

Boost the precision and accuracy of all extractions. Calculate confidence scores for all fields, and fill their confidence attribute.

data_schema: DataSchema | str | dict | None = None

Dynamic changes to the data schema of the model for this inference. Not recommended, for specific use only.

model_id: str

Model ID to use for the inference. Required.

polling_options: PollingOptions | None = None

Options for polling. Set only if having timeout issues.

polygon: bool | None = None

Calculate bounding box polygons for all fields, and fill their locations attribute.

rag: bool | None = None

Enhance extraction accuracy with Retrieval-Augmented Generation.

raw_text: bool | None = None

Extract the full text content from the document as strings, and fill the raw_text attribute.

text_context: str | None = None

Additional text context used by the model during inference. Not recommended, for specific use only.

webhook_ids: list[str] | None = None

Webhook IDs to call after all processing is finished. If empty, no webhooks will be used.

Data Schema

class DataSchema(replace=None)

Modify the Data Schema.

Parameters:

replace (DataSchemaReplace | dict | str | None)

replace: DataSchemaReplace | dict | str | None = None

If set, completely replaces the data schema of the model.

Data Schema Field

class DataSchemaField(title, name, is_array, type, classification_values=None, unique_values=None, description=None, guidelines=None, nested_fields=None)

A field in the data schema.

Parameters:

  • title (str)

  • name (str)

  • is_array (bool)

  • type (str)

  • classification_values (list[str] | None)

  • unique_values (bool | None)

  • description (str | None)

  • guidelines (str | None)

  • nested_fields (dict | None)

classification_values: list[str] | None = None

Allowed values when type is classification. Leave empty for other types.

description: str | None = None

Detailed description of what this field represents.

guidelines: str | None = None

Optional extraction guidelines.

is_array: bool

Whether this field can contain multiple values.

name: str

Name of the field in the data schema.

nested_fields: dict | None = None

Subfields when type is nested_object. Leave empty for other types.

title: str

Display name for the field, also impacts inference results.

type: str

Data type of the field.

unique_values: bool | None = None

Whether to remove duplicate values in the array. Only applicable if is_array is True.

Data Schema Replace

class DataSchemaReplace(fields)

The structure to completely replace the data schema of the model.

Parameters:

fields (list[DataSchemaField | dict])

String Data Class

class StringDataClass

Base class for dataclasses that can be serialized to JSON.