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][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- param AdditionalAttributes: List[AdditionalResultAttribute] | None = []#
One or more additional attributes associated with the result.
- param DocumentAttributes: List[DocumentAttribute] | None = []#
The document attributes.
- param DocumentExcerpt: TextWithHighLights | None [Required]#
Excerpt of the document text.
- param DocumentId: str | None [Required]#
The document ID.
- param DocumentTitle: TextWithHighLights [Required]#
The document title.
- param DocumentURI: str | None [Required]#
The document URI.
- param FeedbackToken: str | None [Required]#
Identifies a particular result from a particular query.
- param Format: str | None [Required]#
- 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: str | None [Required]#
The ID of the relevant result item.
- param ScoreAttributes: dict | None [Required]#
The kendra score confidence
- param Type: str | None [Required]#
Type of result: DOCUMENT or QUESTION_ANSWER or ANSWER
- 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
- Return type:
dict
- get_document_attributes_dict() Dict[str, str | int | List[str] | None] #
Document attributes dict.
- Return type:
Dict[str, str | int | List[str] | None]
- get_excerpt() str [source]#
Document excerpt or passage original content as retrieved by Kendra.
- Return type:
str
- get_score_attribute() str #
Document Score Confidence
- Return type:
str
- to_doc(page_content_formatter: ~typing.Callable[[~langchain_community.retrievers.kendra.ResultItem], str] = <function combined_text>) Document #
Converts this item to a Document.
- Parameters:
page_content_formatter (Callable[[ResultItem], str])
- Return type: