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EmbeddingsClient Class

  • Reference

EmbeddingsClient.

Inheritance
azure.ai.inference._client.EmbeddingsClient
EmbeddingsClient

Constructor

EmbeddingsClient(endpoint: str, credential: AzureKeyCredential | TokenCredential, *, dimensions: int | None = None, encoding_format: str | EmbeddingEncodingFormat | None = None, input_type: str | EmbeddingInputType | None = None, model: str | None = None, model_extras: Dict[str, Any] | None = None, **kwargs: Any)

Parameters

Name Description
endpoint
Required
str

Service host. Required.
credential
Required
AzureKeyCredential or TokenCredential

Credential used to authenticate requests to the service. Is either a AzureKeyCredential type or a TokenCredential type. Required.

Keyword-Only Parameters

Name Description
dimensions
int

Optional. The number of dimensions the resulting output embeddings should have. Default value is None.
encoding_format
str or EmbeddingEncodingFormat

Optional. The desired format for the returned embeddings. Known values are: "base64", "binary", "float", "int8", "ubinary", and "uint8". Default value is None.
input_type
str or EmbeddingInputType

Optional. The type of the input. Known values are: "text", "query", and "document". Default value is None.
model
str

ID of the specific AI model to use, if more than one model is available on the endpoint. Default value is None.
model_extras
dict[str, Any]

Additional, model-specific parameters that are not in the standard request payload. They will be added as-is to the root of the JSON in the request body. How the service handles these extra parameters depends on the value of the extra-parameters request header. Default value is None.
api_version
str

The API version to use for this operation. Default value is "2024-05-01-preview". Note that overriding this default value may result in unsupported behavior.

Methods

close
embed

Return the embedding vectors for given text prompts. The method makes a REST API call to the /embeddings route on the given endpoint.
get_model_info

Returns information about the AI model. The method makes a REST API call to the /info route on the given endpoint. This method will only work when using Serverless API or Managed Compute endpoint. It will not work for GitHub Models endpoint or Azure OpenAI endpoint.
send_request

Runs the network request through the client's chained policies.


>>> from azure.core.rest import HttpRequest
>>> request = HttpRequest("GET", "https://www.example.org/")
<HttpRequest [GET], url: 'https://www.example.org/'>
>>> response = client.send_request(request)
<HttpResponse: 200 OK>

For more information on this code flow, see https://aka.ms/azsdk/dpcodegen/python/send_request

close 

close() -> None

embed

Return the embedding vectors for given text prompts. The method makes a REST API call to the /embeddings route on the given endpoint.

embed(*, input: List[str], dimensions: int | None = None, encoding_format: str | _models.EmbeddingEncodingFormat | None = None, input_type: str | _models.EmbeddingInputType | None = None, model: str | None = None, model_extras: Dict[str, Any] | None = None, **kwargs: Any) -> _models.EmbeddingsResult

Parameters

Name Description
body
Required
<xref:JSON> or IO[bytes]

Is either a MutableMapping[str, Any] type (like a dictionary) or a IO[bytes] type that specifies the full request payload. Required.

Keyword-Only Parameters

Name Description
input
list[str]

Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. Required.
dimensions
int

Optional. The number of dimensions the resulting output embeddings should have. Default value is None.
encoding_format
str or EmbeddingEncodingFormat

Optional. The desired format for the returned embeddings. Known values are: "base64", "binary", "float", "int8", "ubinary", and "uint8". Default value is None.
input_type
str or EmbeddingInputType

Optional. The type of the input. Known values are: "text", "query", and "document". Default value is None.
model
str

ID of the specific AI model to use, if more than one model is available on the endpoint. Default value is None.
model_extras
dict[str, Any]

Additional, model-specific parameters that are not in the standard request payload. They will be added as-is to the root of the JSON in the request body. How the service handles these extra parameters depends on the value of the extra-parameters request header. Default value is None.

Returns

Type Description
EmbeddingsResult

EmbeddingsResult. The EmbeddingsResult is compatible with MutableMapping

Exceptions

Type Description
HttpResponseError

get_model_info

Returns information about the AI model. The method makes a REST API call to the /info route on the given endpoint. This method will only work when using Serverless API or Managed Compute endpoint. It will not work for GitHub Models endpoint or Azure OpenAI endpoint.

get_model_info(**kwargs: Any) -> ModelInfo

Returns

Type Description
ModelInfo

ModelInfo. The ModelInfo is compatible with MutableMapping

Exceptions

Type Description
HttpResponseError

send_request

Runs the network request through the client's chained policies.


>>> from azure.core.rest import HttpRequest
>>> request = HttpRequest("GET", "https://www.example.org/")
<HttpRequest [GET], url: 'https://www.example.org/'>
>>> response = client.send_request(request)
<HttpResponse: 200 OK>

For more information on this code flow, see https://aka.ms/azsdk/dpcodegen/python/send_request

send_request(request: HttpRequest, *, stream: bool = False, **kwargs: Any) -> HttpResponse

Parameters

Name Description
request
Required
HttpRequest

The network request you want to make. Required.

Keyword-Only Parameters

Name Description
stream
bool

Whether the response payload will be streamed. Defaults to False.

Returns

Type Description
HttpResponse

The response of your network call. Does not do error handling on your response.