QueryVectorCollection200ResponseResultsInner.md

QueryVectorCollection200ResponseResultsInner

Properties

Name	Type	Description	Notes
document_id	str		[optional]
content	str	Document text content	[optional]
similarity	float	Cosine similarity score (1.0 for metadata-only queries)	[optional]
metadata	Dict[str, object]		[optional]
embedding	List[float]	Vector embedding (only if includeEmbeddings=true)	[optional]

Example

from quantcdn.models.query_vector_collection200_response_results_inner import QueryVectorCollection200ResponseResultsInner

# TODO update the JSON string below
json = "{}"
# create an instance of QueryVectorCollection200ResponseResultsInner from a JSON string
query_vector_collection200_response_results_inner_instance = QueryVectorCollection200ResponseResultsInner.from_json(json)
# print the JSON string representation of the object
print(QueryVectorCollection200ResponseResultsInner.to_json())

# convert the object into a dict
query_vector_collection200_response_results_inner_dict = query_vector_collection200_response_results_inner_instance.to_dict()
# create an instance of QueryVectorCollection200ResponseResultsInner from a dict
query_vector_collection200_response_results_inner_from_dict = QueryVectorCollection200ResponseResultsInner.from_dict(query_vector_collection200_response_results_inner_dict)

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