Azure OpenAI Embeddings

API Version: v1

License: MIT

Server: {endpoint}/openai/v1 — Azure AI Foundry Models APIs

Server Variables:

Variable Default Description
endpoint A supported Azure AI Foundry Models APIs endpoint, including protocol and hostname.
For example:
https://westus.api.cognitive.microsoft.com).

Authentication

ApiKeyAuth (API Key)

Pass your API key in the api-key header.

ApiKeyAuth_ (API Key)

Pass your API key in the authorization header.

OAuth2Auth (OAuth 2.0)

Flow: implicit

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

Scopes:

  • https://cognitiveservices.azure.com/.default

Security Requirements

Endpoints accept any one of the following authentication methods:

  1. ApiKeyAuth
  2. ApiKeyAuth_
  3. OAuth2Auth (scopes: https://cognitiveservices.azure.com/.default)

Create embedding

POST {endpoint}/openai/v1/embeddings

Creates an embedding vector representing the input text.

URI Parameters

Name In Required Type Description
endpoint server Yes string A supported Azure AI Foundry Models APIs endpoint, including protocol and hostname.
For example:
https://westus.api.cognitive.microsoft.com).
api-version query No string
Possible values: v1, preview		 The explicit Azure AI Foundry Models API version to use for this request.
v1 if not otherwise specified.

Request Body

Content-Type: application/json

Name Type Description Required Default
dimensions integer The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.
Constraints: min: 1		 No
encoding_format enum The format to return the embeddings in. Can be either float or base64.
Possible values: float, base64		 No float
input string or array of string or array of integer or array of array 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. The input must not exceed the max input tokens for the model (8192 tokens for all embedding models), cannot be an empty string, and any array must be 2048 dimensions or less. Example Python code for counting tokens. In addition to the per-input token limit, all embedding models enforce a maximum of 300,000 tokens summed across all inputs in a single request. Yes
model string ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them. Yes
user string A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more. No

Responses

Status Code: 200

Description: The request has succeeded.

Content-Type Type Description
application/json OpenAI.CreateEmbeddingResponse

Response Headers:

Header Type Description
apim-request-id string A request ID used for troubleshooting purposes.

Status Code: default

Description: An unexpected error response.

Content-Type Type Description
application/json object
Name Type Description Required Default
code string or null Yes
inner_error No
message string Yes
param string or null Yes
type string Yes

Response Headers:

Header Type Description
apim-request-id string A request ID used for troubleshooting purposes.

Examples

Example

POST {endpoint}/openai/v1/embeddings?api-version=v1

Components

AzureAIFoundryModelsApiVersion

Property Value
Type string
Values v1
preview

OpenAI.CreateEmbeddingRequest

Name Type Description Required Default
dimensions integer The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.
Constraints: min: 1		 No
encoding_format enum The format to return the embeddings in. Can be either float or base64.
Possible values: float, base64		 No float
input string or array of string or array of integer or array of array 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. The input must not exceed the max input tokens for the model (8192 tokens for all embedding models), cannot be an empty string, and any array must be 2048 dimensions or less. Example Python code for counting tokens. In addition to the per-input token limit, all embedding models enforce a maximum of 300,000 tokens summed across all inputs in a single request. Yes
model string ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them. Yes
user string A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more. No

OpenAI.CreateEmbeddingResponse

Name Type Description Required Default
data array of OpenAI.Embedding The list of embeddings generated by the model. Yes
model string The name of the model used to generate the embedding. Yes
object enum The object type, which is always "list".
Possible values: list		 Yes
usage OpenAI.CreateEmbeddingResponseUsage Yes
└─ prompt_tokens integer Yes
└─ total_tokens integer Yes

OpenAI.CreateEmbeddingResponseUsage

Name Type Description Required Default
prompt_tokens integer Yes
total_tokens integer Yes

OpenAI.Embedding

Represents an embedding vector returned by embedding endpoint.

Name Type Description Required Default
embedding array of number The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the embedding guide. Yes
index integer The index of the embedding in the list of embeddings. Yes
object enum The object type, which is always "embedding".
Possible values: embedding		 Yes
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