Source code for alibabacloud_oss_v2.vectors.models.index_basic

import datetime
from typing import Optional, List, Any, Dict
from ... import serde


# Put
[docs] class PutVectorIndexRequest(serde.RequestModel): """ The request for the vector index operation. """ _attribute_map = { 'bucket': {'tag': 'input', 'position': 'host', 'rename': 'bucket', 'type': 'str', 'required': True}, 'data_type': {'tag': 'input', 'position': 'body', 'rename': 'dataType', 'type': 'str'}, 'dimension': {'tag': 'input', 'position': 'body', 'rename': 'dimension', 'type': 'int'}, 'distance_metric': {'tag': 'input', 'position': 'body', 'rename': 'distanceMetric', 'type': 'str'}, 'index_name': {'tag': 'input', 'position': 'body', 'rename': 'indexName', 'type': 'str'}, 'metadata': {'tag': 'input', 'position': 'body', 'rename': 'metadata', 'type': 'dict'}, } def __init__( self, bucket: Optional[str] = None, data_type: Optional[str] = None, dimension: Optional[int] = None, distance_metric: Optional[str] = None, index_name: Optional[str] = None, metadata: Optional[Dict] = None, **kwargs: Any ) -> None: """ Args: bucket (str, optional): The name of the bucket. data_type (str, optional): The type of data for the vector index. dimension (int, optional): The dimension of the vector data. distance_metric (str, optional): The distance measurement function has the following optional values: Euclidean distance: Euclidean distance Cosine: cosine distance index_name (str, optional): The name of the index. metadata (Dict, optional): The metadata configuration. """ super().__init__(**kwargs) self.bucket = bucket self.data_type = data_type self.dimension = dimension self.distance_metric = distance_metric self.index_name = index_name self.metadata = metadata
[docs] class PutVectorIndexResult(serde.ResultModel): """ The result for the PutVectorIndex operation. """
# Get
[docs] class GetVectorIndexRequest(serde.RequestModel): """ The request for the GetVectorIndex operation. """ _attribute_map = { 'bucket': {'tag': 'input', 'position': 'path', 'rename': 'bucket', 'type': 'str'}, 'index_name': {'tag': 'input', 'position': 'body', 'rename': 'indexName', 'type': 'str'}, } def __init__( self, bucket: Optional[str] = None, index_name: Optional[str] = None, **kwargs: Any ) -> None: """ Args: bucket (str, optional): The name of the bucket. index_name (str, optional): The name of the index. """ super().__init__(**kwargs) self.bucket = bucket self.index_name = index_name
[docs] class GetVectorIndexResult(serde.ResultModel): """ The result for the GetVectorIndex operation. """ _attribute_map = { 'index': {'tag': 'output', 'position': 'body', 'rename': 'index', 'type': 'dict'}, } def __init__( self, index: Optional[Dict] = None, **kwargs: Any ) -> None: """ Args: index (Dict, optional): The vector index information. """ super().__init__(**kwargs) self.index = index
# List
[docs] class ListVectorIndexesRequest(serde.RequestModel): """ The request for the ListVectorIndexes operation. """ _attribute_map = { 'bucket': {'tag': 'input', 'position': 'path', 'rename': 'bucket', 'type': 'str'}, 'max_results': {'tag': 'input', 'position': 'body', 'rename': 'maxResults', 'type': 'int'}, 'next_token': {'tag': 'input', 'position': 'body', 'rename': 'nextToken', 'type': 'str'}, 'prefix': {'tag': 'input', 'position': 'body', 'rename': 'prefix', 'type': 'str'}, } def __init__( self, bucket: Optional[str] = None, max_results: Optional[int] = None, next_token: Optional[str] = None, prefix: Optional[str] = None, **kwargs: Any ) -> None: """ Args: bucket (str, optional): The name of the bucket. max_results (int, optional): The maximum number of indexes to return. next_token (str, optional): The token for the next page of indexes. prefix (str, optional): The prefix to filter indexes by name. """ super().__init__(**kwargs) self.bucket = bucket self.max_results = max_results self.next_token = next_token self.prefix = prefix
[docs] class ListVectorIndexesResult(serde.ResultModel): """ The result for the ListVectorIndexes operation. """ _attribute_map = { 'indexes': {'tag': 'output', 'position': 'body', 'rename': 'indexes', 'type': '[dict]'}, 'next_token': {'tag': 'output', 'position': 'body', 'rename': 'nextToken', 'type': 'str'}, } def __init__( self, indexes: Optional[List[Dict]] = None, next_token: Optional[str] = None, **kwargs: Any ) -> None: """ Args: indexes (List[Dict], optional): The list of vector index summaries. next_token (str, optional): The token for the next page of indexes. """ super().__init__(**kwargs) self.indexes = indexes self.next_token = next_token
# Delete
[docs] class DeleteVectorIndexRequest(serde.RequestModel): """ The request for the DeleteVectorIndex operation. """ _attribute_map = { 'bucket': {'tag': 'input', 'position': 'path', 'rename': 'bucket', 'type': 'str'}, 'index_name': {'tag': 'input', 'position': 'body', 'rename': 'indexName', 'type': 'str'}, } def __init__( self, bucket: Optional[str] = None, index_name: Optional[str] = None, **kwargs: Any ) -> None: """ Args: bucket (str, optional): The name of the bucket. index_name (str, optional): The name of the index to delete. """ super().__init__(**kwargs) self.bucket = bucket self.index_name = index_name
[docs] class DeleteVectorIndexResult(serde.ResultModel): """ The result for the DeleteVectorIndex operation. """