langchain_community.embeddings.sagemaker_endpoint.SagemakerEndpointEmbeddings

class langchain_community.embeddings.sagemaker_endpoint.SagemakerEndpointEmbeddings

Bases: BaseModel, Embeddings

自定义Sagemaker推理端点。

要使用，必须提供部署的Sagemaker模型的端点名称和部署的区域。

要进行身份验证，AWS客户端使用以下方法自动加载凭据： https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html

如果应该使用特定的凭据配置文件，必须传递要使用的位于~/.aws/credentials文件中的配置文件的名称。

确保使用的凭据/角色具有访问Sagemaker端点所需的策略。 参见：https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies.html

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 client: Any = None

param content_handler: langchain_community.embeddings.sagemaker_endpoint.EmbeddingsContentHandler [Required]

提供输入和输出转换函数以处理LLM和端点之间的格式的内容处理程序类。

param credentials_profile_name: Optional[str] = None

~/.aws/credentials 或 ~/.aws/config 文件中配置文件的名称，其中指定了访问密钥或角色信息。 如果未指定，则将使用默认凭据配置文件，或者如果在EC2实例上，则将使用来自IMDS的凭据。 参见：https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html

param endpoint_kwargs: Optional[Dict] = None

传递给invoke_endpoint函数的可选属性。有关更多信息，请参阅`boto3`文档。 .. _boto3: <https://boto3.amazonaws.com/v1/documentation/api/latest/index.html>

param endpoint_name: str = ''

部署的Sagemaker模型的端点名称。 在AWS区域内必须是唯一的。

param model_kwargs: Optional[Dict] = None

传递给模型的关键字参数。

param region_name: str = ''

Sagemaker模型部署的AWS区域，例如`us-west-2`。

async aembed_documents(texts: List[str]) → List[List[float]]

Asynchronous 嵌入搜索文档。

Parameters

texts (List[str]) –

Return type

List[List[float]]

async aembed_query(text: str) → List[float]

Asynchronous 嵌入查询文本。

Parameters

text (str) –

Return type

List[float]

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

Parameters

• _fields_set (Optional[SetStr]) –

• values (Any) –

Return type

Model

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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model

• exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include

• update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model

• self (Model) –

Returns

new model instance

Return type

Model

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.

Parameters

• include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

• exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

• by_alias (bool) –

• skip_defaults (Optional[bool]) –

• exclude_unset (bool) –

• exclude_defaults (bool) –

• exclude_none (bool) –

Return type

DictStrAny

embed_documents(texts: List[str], chunk_size: int = 64) → List[List[float]]

使用SageMaker推理端点计算文档嵌入。

参数：

texts：要嵌入的文本列表。 chunk_size：块大小定义了将多少个输入文本作为请求分组在一起。如果为None，将使用类指定的块大小。

返回：

嵌入列表，每个文本对应一个嵌入。

Parameters

• texts (List[str]) –

• chunk_size (int) –

Return type

List[List[float]]

embed_query(text: str) → List[float]

使用SageMaker推理端点计算查询嵌入。

参数：

text：要嵌入的文本。

返回：

文本的嵌入。

Parameters

text (str) –

Return type

List[float]

classmethod from_orm(obj: Any) → Model

Parameters

obj (Any) –

Return type

Model

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().

Parameters

• include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

• exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

• by_alias (bool) –

• skip_defaults (Optional[bool]) –

• exclude_unset (bool) –

• exclude_defaults (bool) –

• exclude_none (bool) –

• encoder (Optional[Callable[[Any], Any]]) –

• models_as_dict (bool) –

• dumps_kwargs (Any) –

Return type

unicode

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model

Parameters

• path (Union[str, Path]) –

• content_type (unicode) –

• encoding (unicode) –

• proto (Protocol) –

• allow_pickle (bool) –

Return type

Model

classmethod parse_obj(obj: Any) → Model

Parameters

obj (Any) –

Return type

Model

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model

Parameters

• b (Union[str, bytes]) –

• content_type (unicode) –

• encoding (unicode) –

• proto (Protocol) –

• allow_pickle (bool) –

Return type

Model

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny

Parameters

• by_alias (bool) –

• ref_template (unicode) –

Return type

DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode

Parameters

• by_alias (bool) –

• ref_template (unicode) –

• dumps_kwargs (Any) –

Return type

unicode

classmethod update_forward_refs(**localns: Any) → None

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

Parameters

localns (Any) –

Return type

None

classmethod validate(value: Any) → Model

Parameters

value (Any) –

Return type

Model

Examples using SagemakerEndpointEmbeddings

• AWS

• client = boto3.client(