langchain_community.retrievers.kendra.QueryResultItem¶

class langchain_community.retrievers.kendra.QueryResultItem[source]¶

Bases: ResultItem

Query API result item.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

param AdditionalAttributes: Optional[List[langchain_community.retrievers.kendra.AdditionalResultAttribute]] = []¶

One or more additional attributes associated with the result.

param DocumentAttributes: Optional[List[langchain_community.retrievers.kendra.DocumentAttribute]] = []¶

The document attributes.

param DocumentExcerpt: Optional[langchain_community.retrievers.kendra.TextWithHighLights] = None¶

Excerpt of the document text.

param DocumentId: Optional[str] = None¶

The document ID.

param DocumentTitle: langchain_community.retrievers.kendra.TextWithHighLights [Required]¶

The document title.

param DocumentURI: Optional[str] = None¶

The document URI.

param FeedbackToken: Optional[str] = None¶

Identifies a particular result from a particular query.

param Format: Optional[str] = None¶
If the Type is ANSWER, then format is either:

  • TABLE: a table excerpt is returned in TableExcerpt;

  • TEXT: a text excerpt is returned in DocumentExcerpt.

param Id: Optional[str] = None¶

The ID of the relevant result item.

param Type: Optional[str] = None¶

Type of result: DOCUMENT or QUESTION_ANSWER or ANSWER

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

  • include – fields to include in new model

  • exclude – fields to exclude from new model, as with values this takes precedence over include

  • update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) → Model¶
get_additional_metadata() → dict[source]¶

Document additional metadata dict. This returns any extra metadata except these:

  • result_id

  • document_id

  • source

  • title

  • excerpt

  • document_attributes

get_attribute_value() → str[source]¶
get_document_attributes_dict() → Dict[str, Optional[Union[str, int, List[str]]]]¶

Document attributes dict.

get_excerpt() → str[source]¶

Document excerpt or passage original content as retrieved by Kendra.

get_title() → str[source]¶

Document title.

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
to_doc(page_content_formatter: ~typing.Callable[[~langchain_community.retrievers.kendra.ResultItem], str] = <function combined_text>) → Document¶

Converts this item to a Document.

classmethod update_forward_refs(**localns: Any) → None¶

Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model¶