Get Embeddings - Get Embeddings

Reference

Service:: AI Foundry

API Version:: 2024-05-01-preview

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

POST https:///embeddings?api-version=2024-05-01-preview

URI Parameters

Name	In	Required	Type	Description
api-version	query	True	string minLength: 1	The API version to use for this operation.

Request Header

Name	Required	Type	Description
extra-parameters		ExtraParameters	Controls what happens if extra parameters, undefined by the REST API, are passed in the JSON request payload. This sets the HTTP request header `extra-parameters`.

Request Body

Name	Required	Type	Description
input	True	string[]	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.
dimensions		integer (int32)	Optional. The number of dimensions the resulting output embeddings should have. Passing null causes the model to use its default value. Returns a 422 error if the model doesn't support the value or parameter.
encoding_format		EmbeddingEncodingFormat	Optional. The desired format for the returned embeddings.
input_type		EmbeddingInputType	Optional. The type of the input. Returns a 422 error if the model doesn't support the value or parameter.
model		string	ID of the specific AI model to use, if more than one model is available on the endpoint.

Responses

Name	Type	Description
200 OK	EmbeddingsResult	The request has succeeded.
Other Status Codes	Azure.Core.Foundations.ErrorResponse	An unexpected error response. Headers x-ms-error-code: string

Name

Type

Description

200 OK

EmbeddingsResult

The request has succeeded.

Other Status Codes

Azure.Core.Foundations.ErrorResponse

An unexpected error response.

Headers

x-ms-error-code: string

Security

api-key

Type: apiKey
In: header

OAuth2Auth

Type: oauth2
Flow: implicit
Authorization URL: https://login.microsoftonline.com/common/oauth2/v2.0/authorize

Scopes

Name	Description
https://ml.azure.com/.default

Examples

maximum set embeddings

minimum set embeddings

maximum set embeddings

Sample request

HTTP

POST https:///embeddings?api-version=2024-05-01-preview


{
  "input": [
    "This is a very good text"
  ],
  "dimensions": 1024,
  "encoding_format": "float",
  "input_type": "text",
  "model": "my-model-name"
}

Sample response

Status code:: 200

{
  "id": "cknxthfa",
  "data": [
    {
      "index": 0,
      "object": "embedding",
      "embedding": [
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0
      ]
    }
  ],
  "object": "list",
  "model": "my-model-name",
  "usage": {
    "prompt_tokens": 15,
    "total_tokens": 15
  }
}

minimum set embeddings

Sample request

HTTP

POST https:///embeddings?api-version=2024-05-01-preview

{
  "input": [
    "This is a very good text"
  ]
}

Sample response

Status code:: 200

{
  "id": "cknxthfa",
  "data": [
    {
      "index": 0,
      "object": "embedding",
      "embedding": [
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0
      ]
    }
  ],
  "object": "list",
  "model": "my-model-name",
  "usage": {
    "prompt_tokens": 15,
    "total_tokens": 15
  }
}

Definitions

Name	Description
Azure.Core.Foundations.Error	The error object.
Azure.Core.Foundations.ErrorResponse	A response containing error details.
Azure.Core.Foundations.InnerError	An object containing more specific information about the error. As per Microsoft One API guidelines - https://github.com/Microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses.
EmbeddingEncodingFormat	Specifies the types of embeddings to generate. Compressed embeddings types like `uint8`, `int8`, `ubinary` and `binary`, may reduce storage costs without sacrificing the integrity of the data. Returns a 422 error if the model doesn't support the value or parameter. Read the model's documentation to know the values supported by the your model.
EmbeddingInputType	Represents the input types used for embedding search.
EmbeddingItem	Representation of a single embeddings relatedness comparison.
EmbeddingsOptions	The configuration information for an embeddings request.
EmbeddingsResult	Representation of the response data from an embeddings request. Embeddings measure the relatedness of text strings and are commonly used for search, clustering, recommendations, and other similar scenarios.
EmbeddingsUsage	Measurement of the amount of tokens used in this request and response.
ExtraParameters	Controls what happens if extra parameters, undefined by the REST API, are passed in the JSON request payload.

Azure.Core.Foundations.Error

Object

The error object.

Name	Type	Description
code	string	One of a server-defined set of error codes.
details	Azure.Core.Foundations.Error[]	An array of details about specific errors that led to this reported error.
innererror	Azure.Core.Foundations.InnerError	An object containing more specific information than the current object about the error.
message	string	A human-readable representation of the error.
target	string	The target of the error.

Azure.Core.Foundations.ErrorResponse

Object

A response containing error details.

Name	Type	Description
error	Azure.Core.Foundations.Error	The error object.

Azure.Core.Foundations.InnerError

Object

An object containing more specific information about the error. As per Microsoft One API guidelines - https://github.com/Microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses.

Name	Type	Description
code	string	One of a server-defined set of error codes.
innererror	Azure.Core.Foundations.InnerError	Inner error.

EmbeddingEncodingFormat

Enumeration

Specifies the types of embeddings to generate. Compressed embeddings types like uint8, int8, ubinary and binary, may reduce storage costs without sacrificing the integrity of the data. Returns a 422 error if the model doesn't support the value or parameter. Read the model's documentation to know the values supported by the your model.

Value	Description
base64	Get back binary representation of the embeddings encoded as Base64 string. OpenAI Python library retrieves embeddings from the API as encoded binary data, rather than using intermediate decimal representations as is usually done.
binary	Get back signed binary embeddings
float	Get back full precision embeddings
int8	Get back signed int8 embeddings
ubinary	Get back unsigned binary embeddings
uint8	Get back unsigned int8 embeddings

EmbeddingInputType

Enumeration

Represents the input types used for embedding search.

Value	Description
document	Indicates the input represents a document that is stored in a vector database.
query	Indicates the input represents a search query to find the most relevant documents in your vector database.
text	Indicates the input is a general text input.

EmbeddingItem

Object

Representation of a single embeddings relatedness comparison.

Name	Type	Description
embedding	number[] (float)	List of embedding values for the input prompt. These represent a measurement of the vector-based relatedness of the provided input. Or a base64 encoded string of the embedding vector.
index	integer (int32)	Index of the prompt to which the EmbeddingItem corresponds.
object	enum: embedding	The object type of this embeddings item. Will always be `embedding`.

EmbeddingsOptions

Object

The configuration information for an embeddings request.

Name	Type	Description
dimensions	integer (int32)	Optional. The number of dimensions the resulting output embeddings should have. Passing null causes the model to use its default value. Returns a 422 error if the model doesn't support the value or parameter.
encoding_format	EmbeddingEncodingFormat	Optional. The desired format for the returned embeddings.
input	string[]	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.
input_type	EmbeddingInputType	Optional. The type of the input. Returns a 422 error if the model doesn't support the value or parameter.
model	string	ID of the specific AI model to use, if more than one model is available on the endpoint.

EmbeddingsResult

Object

Representation of the response data from an embeddings request. Embeddings measure the relatedness of text strings and are commonly used for search, clustering, recommendations, and other similar scenarios.

Name	Type	Description
data	EmbeddingItem[]	Embedding values for the prompts submitted in the request.
id	string	Unique identifier for the embeddings result.
model	string	The model ID used to generate this result.
object	enum: list	The object type of the embeddings result. Will always be `list`.
usage	EmbeddingsUsage	Usage counts for tokens input using the embeddings API.

EmbeddingsUsage

Object

Measurement of the amount of tokens used in this request and response.

Name	Type	Description
prompt_tokens	integer (int32)	Number of tokens in the request.
total_tokens	integer (int32)	Total number of tokens transacted in this request/response. Should equal the number of tokens in the request.

ExtraParameters

Enumeration

Controls what happens if extra parameters, undefined by the REST API, are passed in the JSON request payload.

Value	Description
drop	The service will ignore (drop) extra parameters in the request payload. It will only pass the known parameters to the back-end AI model.
error	The service will error if it detected extra parameters in the request payload. This is the service default.
pass-through	The service will pass extra parameters to the back-end AI model.

Del via

Get Embeddings - Get Embeddings

URI Parameters

Request Header

Request Body

Responses

Security

api-key

OAuth2Auth

Scopes

Examples

maximum set embeddings

Sample request

Sample response

minimum set embeddings

Sample request

Sample response

Definitions

Azure.Core.Foundations.Error

Azure.Core.Foundations.ErrorResponse

Azure.Core.Foundations.InnerError

EmbeddingEncodingFormat

EmbeddingInputType

EmbeddingItem

EmbeddingsOptions

EmbeddingsResult

EmbeddingsUsage

ExtraParameters

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