DocumentItemFilter

Converter

DashAI.back.converters.document.DocumentItemFilter

---

Drop the selected document items that a rule picks.

The rule drops items that are too short or too long, items that match or do not match a regular expression, or every selected item, which is how page headers, footers or other kinds are removed.

Parameters

rule : string, default=Too short or too long

Which selected items to drop. 'Every selected item' drops the whole scope, for example the page headers and footers; it is the only rule for Image items.

min_characters : integer, default=1

With 'Too short or too long', items with fewer characters, not counting surrounding spaces, are dropped.

max_characters, default=None

With 'Too short or too long', items with more characters are dropped. Empty means no upper limit.

pattern, default=None

Regular expression (Python syntax) searched in each item by the pattern rules, such as '^Page \d+$'.

Methods

transform(self, x: 'DashAIDataset', y: Optional[ForwardRef('DashAIDataset')] = None) -> 'DashAIDataset'

Defined on DocumentItemFilter

Return the items the rule keeps, each from its own source.

Parameters

x : DashAIDataset

The selected items, in one column.

y : DashAIDataset, optional

Ignored.

Returns

DashAIDataset

The kept items with their source rows.

build_report(self, data: 'Dict[str, Any]') -> 'Dict[str, Any]'

Defined on BaseConverter

Wrap converter-specific data with the producer converter name.

fit(self, x: 'DashAIDataset', y: Optional[ForwardRef('DashAIDataset')] = None) -> 'DocumentConverter'

Defined on DocumentConverter

Return the converter unchanged; override to learn from the items.

Parameters

x : DashAIDataset

The selected items.

y : DashAIDataset, optional

Ignored.

Returns

DocumentConverter

This converter.

get_credential(self, name: str)

Defined on ConfigObject

Resolve a registered credential component by name.

Parameters

name : str

Credential component class name (e.g. "HuggingFaceCredential").

Returns

BaseCredential

An instance of the requested credential component.

get_metadata(cls) -> 'Dict[str, Any]'

Defined on BaseConverter

Get metadata for the converter, used by the DashAI frontend.

Parameters

cls : type

The converter class (injected automatically by Python for classmethods).

Returns

Dict[str, Any]

Dictionary containing display name, short description, image preview path, category, icon, color, and whether the converter is supervised.

get_output_type(self, column_name: Optional[str] = None) -> DashAI.back.types.dashai_data_type.DashAIDataType

Defined on DocumentConverter

Return Text, the content type most document converters produce.

Parameters

column_name : str, optional

Unused.

Returns

DashAIDataType

A string backed Text type.

get_report(self) -> 'Union[Dict[str, Any], None]'

Defined on BaseConverter

Return the converter report produced after execution, if any.

Returns

Dict[str, Any] or None

JSON-serializable report dict, or None when the converter does not produce one.

get_schema(cls) -> dict

Defined on ConfigObject

Generates the component related Json Schema.

Returns

dict

Dictionary representing the Json Schema of the component.

infer_output_columns(self, inputs: 'List[StateItem]') -> 'StructureDelta'

Defined on BaseConverter

Estimate what this converter does to its scope, without any data.

Parameters

inputs : list of ColumnItem | BlockItem

The dataset state items in this converter's scope.

Returns

StructureDelta

The scope items that survive (maybe retyped) and the new items.

items_result(contents: List[Any], sources: List[int], content_type: type = <class 'DashAI.back.types.value_types.Text'>, kinds: Optional[List[Optional[str]]] = None, attrs: Optional[List[Optional[Dict[str, Any]]]] = None) -> 'DashAIDataset'

Defined on DocumentConverter

Build the dataset a document converter returns.

Parameters

contents : List[Any]

The new item contents: strings for Text, {"bytes", "path"} dicts for images.

sources : List[int]

For each new item, the index of the input row it comes from.

content_type : type, optional

Text (default) or DashAIImage.

kinds : List[Optional[str]], optional

The element kind of each new item; None inherits or defaults.

attrs : List[Optional[Dict[str, Any]]], optional

The element attributes of each new item.

Returns

DashAIDataset

content and source columns, plus kind and attrs when given.

rows_to_keep(self, x: "'DashAIDataset'") -> 'List[int]'

Defined on BaseConverter

Positions of the rows of x that survive this converter.

Parameters

x : DashAIDataset

The converter's scope columns of one split.

Returns

list of int

0-based positions of the kept rows, in order.

validate_and_transform(self, raw_data: dict) -> dict

Defined on ConfigObject

It takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.

Parameters

raw_data : dict

A dictionary with the data provided by the user to initialize the model.

Returns

dict

A validated dictionary with the necessary objects.