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Azure OpenAI Service REST API reference

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This article provides details on the inference REST API endpoints for Azure OpenAI.

Authentication

Azure OpenAI provides two methods for authentication. you can use either API Keys or Azure Active Directory.

  • API Key authentication: For this type of authentication, all API requests must include the API Key in the api-key HTTP header. The Quickstart provides guidance for how to make calls with this type of authentication.

  • Azure Active Directory authentication: You can authenticate an API call using an Azure Active Directory token. Authentication tokens are included in a request as the Authorization header. The token provided must be preceded by Bearer, for example Bearer YOUR_AUTH_TOKEN. You can read our how-to guide on authenticating with Azure Active Directory.

REST API versioning

The service APIs are versioned using the api-version query parameter. All versions follow the YYYY-MM-DD date structure. For example:

POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/completions?api-version=2023-05-15

Completions

With the Completions operation, the model will generate one or more predicted completions based on a provided prompt. The service can also return the probabilities of alternative tokens at each position.

Create a completion

POST https://{your-resource-name}.openai.azure.com/openai/deployments/{deployment-id}/completions?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
deployment-id string Required The deployment name you chose when you deployed the model.
api-version string Required The API version to use for this operation. This follows the YYYY-MM-DD format.

Supported versions

Request body

Parameter Type Required? Default Description
prompt string or array Optional <\|endoftext\|> The prompt(s) to generate completions for, encoded as a string, or array of strings. Note that <\|endoftext\|> is the document separator that the model sees during training, so if a prompt isn't specified the model will generate as if from the beginning of a new document.
max_tokens integer Optional 16 The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens can't exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096).
temperature number Optional 1 What sampling temperature to use, between 0 and 2. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer. We generally recommend altering this or top_p but not both.
top_p number Optional 1 An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.
logit_bias map Optional null Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this tokenizer tool (which works for both GPT-2 and GPT-3) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. As an example, you can pass {"50256": -100} to prevent the <|endoftext|> token from being generated.
user string Optional A unique identifier representing your end-user, which can help monitoring and detecting abuse
n integer Optional 1 How many completions to generate for each prompt. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop.
stream boolean Optional False Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.
logprobs integer Optional null Include the log probabilities on the logprobs most likely tokens, as well the chosen tokens. For example, if logprobs is 10, the API will return a list of the 10 most likely tokens. the API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response. This parameter cannot be used with gpt-35-turbo.
suffix string Optional null The suffix that comes after a completion of inserted text.
echo boolean Optional False Echo back the prompt in addition to the completion. This parameter cannot be used with gpt-35-turbo.
stop string or array Optional null Up to four sequences where the API will stop generating further tokens. The returned text won't contain the stop sequence.
presence_penalty number Optional 0 Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
frequency_penalty number Optional 0 Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
best_of integer Optional 1 Generates best_of completions server-side and returns the "best" (the one with the lowest log probability per token). Results can't be streamed. When used with n, best_of controls the number of candidate completions and n specifies how many to return – best_of must be greater than n. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop. This parameter cannot be used with gpt-35-turbo.

Example request

curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/completions?api-version=2023-05-15\
  -H "Content-Type: application/json" \
  -H "api-key: YOUR_API_KEY" \
  -d "{
  \"prompt\": \"Once upon a time\",
  \"max_tokens\": 5
}"

Example response

{
    "id": "cmpl-4kGh7iXtjW4lc9eGhff6Hp8C7btdQ",
    "object": "text_completion",
    "created": 1646932609,
    "model": "ada",
    "choices": [
        {
            "text": ", a dark line crossed",
            "index": 0,
            "logprobs": null,
            "finish_reason": "length"
        }
    ]
}

In the example response, finish_reason equals stop. If finish_reason equals content_filter consult our content filtering guide to understand why this is occurring.

Embeddings

Get a vector representation of a given input that can be easily consumed by machine learning models and other algorithms.

Note

OpenAI currently allows a larger number of array inputs with text-embedding-ada-002. Azure OpenAI currently supports input arrays up to 16 for text-embedding-ada-002 (Version 2). Both require the max input token limit per API request to remain under 8191 for this model.

Create an embedding

POST https://{your-resource-name}.openai.azure.com/openai/deployments/{deployment-id}/embeddings?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
deployment-id string Required The name of your model deployment. You're required to first deploy a model before you can make calls.
api-version string Required The API version to use for this operation. This follows the YYYY-MM-DD format.

Supported versions

Request body

Parameter Type Required? Default Description
input string or array Yes N/A Input text to get embeddings for, encoded as an array or string. The number of input tokens varies depending on what model you are using. Only text-embedding-ada-002 (Version 2) supports array input.
user string No Null A unique identifier representing your end-user. This will help Azure OpenAI monitor and detect abuse. Do not pass PII identifiers instead use pseudoanonymized values such as GUIDs

Example request

curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/embeddings?api-version=2023-05-15 \
  -H "Content-Type: application/json" \
  -H "api-key: YOUR_API_KEY" \
  -d "{\"input\": \"The food was delicious and the waiter...\"}"

Example response

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.018990106880664825,
        -0.0073809814639389515,
        .... (1024 floats total for ada)
        0.021276434883475304,
      ],
      "index": 0
    }
  ],
  "model": "text-similarity-babbage:001"
}

Chat completions

Create completions for chat messages with the GPT-35-Turbo and GPT-4 models.

Create chat completions

POST https://{your-resource-name}.openai.azure.com/openai/deployments/{deployment-id}/chat/completions?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
deployment-id string Required The name of your model deployment. You're required to first deploy a model before you can make calls.
api-version string Required The API version to use for this operation. This follows the YYYY-MM-DD format.

Supported versions

Example request

curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/chat/completions?api-version=2023-05-15 \
  -H "Content-Type: application/json" \
  -H "api-key: YOUR_API_KEY" \
  -d '{"messages":[{"role": "system", "content": "You are a helpful assistant."},{"role": "user", "content": "Does Azure OpenAI support customer managed keys?"},{"role": "assistant", "content": "Yes, customer managed keys are supported by Azure OpenAI."},{"role": "user", "content": "Do other Azure AI services support this too?"}]}'

Example response

{"id":"chatcmpl-6v7mkQj980V1yBec6ETrKPRqFjNw9",
"object":"chat.completion","created":1679072642,
"model":"gpt-35-turbo",
"usage":{"prompt_tokens":58,
"completion_tokens":68,
"total_tokens":126},
"choices":[{"message":{"role":"assistant",
"content":"Yes, other Azure AI services also support customer managed keys. Azure AI services offer multiple options for customers to manage keys, such as using Azure Key Vault, customer-managed keys in Azure Key Vault or customer-managed keys through Azure Storage service. This helps customers ensure that their data is secure and access to their services is controlled."},"finish_reason":"stop","index":0}]}

In the example response, finish_reason equals stop. If finish_reason equals content_filter consult our content filtering guide to understand why this is occurring.

Output formatting adjusted for ease of reading, actual output is a single block of text without line breaks.

Parameter Type Required? Default Description
messages array Required The collection of context messages associated with this chat completions request. Typical usage begins with a chat message for the System role that provides instructions for the behavior of the assistant, followed by alternating messages between the User and Assistant roles.
temperature number Optional 1 What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\nWe generally recommend altering this or top_p but not both.
n integer Optional 1 How many chat completion choices to generate for each input message.
stream boolean Optional false If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message."
stop string or array Optional null Up to 4 sequences where the API will stop generating further tokens.
max_tokens integer Optional inf The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens).
presence_penalty number Optional 0 Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
frequency_penalty number Optional 0 Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
logit_bias object Optional null Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
user string Optional A unique identifier representing your end-user, which can help Azure OpenAI to monitor and detect abuse.
function_call Optional Controls how the model responds to function calls. "none" means the model does not call a function, and responds to the end-user. "auto" means the model can pick between an end-user or calling a function. Specifying a particular function via {"name": "my_function"} forces the model to call that function. "none" is the default when no functions are present. "auto" is the default if functions are present. This parameter requires API version 2023-07-01-preview
functions FunctionDefinition[] Optional A list of functions the model may generate JSON inputs for. This parameter requires API version 2023-07-01-preview

ChatMessage

A single, role-attributed message within a chat completion interaction.

Name Type Description
content string The text associated with this message payload.
function_call FunctionCall The name and arguments of a function that should be called, as generated by the model.
name string The name of the author of this message. name is required if role is function, and it should be the name of the function whose response is in the content. May contain a-z, A-Z, 0-9, and underscores, with a maximum length of 64 characters.
role ChatRole The role associated with this message payload

ChatRole

A description of the intended purpose of a message within a chat completions interaction.

Name Type Description
assistant string The role that provides responses to system-instructed, user-prompted input.
function string The role that provides function results for chat completions.
system string The role that instructs or sets the behavior of the assistant.
user string The role that provides input for chat completions.

FunctionCall

The name and arguments of a function that should be called, as generated by the model. This requires API version 2023-07-01-preview

Name Type Description
arguments string The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may fabricate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
name string The name of the function to call.

FunctionDefinition

The definition of a caller-specified function that chat completions may invoke in response to matching user input. This requires API version 2023-07-01-preview

Name Type Description
description string A description of what the function does. The model will use this description when selecting the function and interpreting its parameters.
name string The name of the function to be called.
parameters The parameters the functions accepts, described as a JSON Schema object.

Completions extensions

Extensions for chat completions, for example Azure OpenAI on your data.

Use chat completions extensions

POST {your-resource-name}/openai/deployments/{deployment-id}/extensions/chat/completions?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
deployment-id string Required The name of your model deployment. You're required to first deploy a model before you can make calls.
api-version string Required The API version to use for this operation. This follows the YYYY-MM-DD format.

Supported versions

Example request

curl -i -X POST YOUR_RESOURCE_NAME/openai/deployments/YOUR_DEPLOYMENT_NAME/extensions/chat/completions?api-version=2023-06-01-preview \
-H "Content-Type: application/json" \
-H "api-key: YOUR_API_KEY" \
-d \
'
{
    "temperature": 0,
    "max_tokens": 1000,
    "top_p": 1.0,
    "dataSources": [
        {
            "type": "AzureCognitiveSearch",
            "parameters": {
                "endpoint": "'YOUR_AZURE_COGNITIVE_SEARCH_ENDPOINT'",
                "key": "'YOUR_AZURE_COGNITIVE_SEARCH_KEY'",
                "indexName": "'YOUR_AZURE_COGNITIVE_SEARCH_INDEX_NAME'"
            }
        }
    ],
    "messages": [
        {
            "role": "user",
            "content": "What are the differences between Azure Machine Learning and Azure AI services?"
        }
    ]
}
'

Example response

{
    "id": "12345678-1a2b-3c4e5f-a123-12345678abcd",
    "model": "",
    "created": 1684304924,
    "object": "chat.completion",
    "choices": [
        {
            "index": 0,
            "messages": [
                {
                    "role": "tool",
                    "content": "{\"citations\": [{\"content\": \"\\nAzure AI services are cloud-based artificial intelligence (AI) services...\", \"id\": null, \"title\": \"What is Azure AI services\", \"filepath\": null, \"url\": null, \"metadata\": {\"chunking\": \"orignal document size=250. Scores=0.4314117431640625 and 1.72564697265625.Org Highlight count=4.\"}, \"chunk_id\": \"0\"}], \"intent\": \"[\\\"Learn about Azure AI services.\\\"]\"}",
                    "end_turn": false
                },
                {
                    "role": "assistant",
                    "content": " \nAzure AI services are cloud-based artificial intelligence (AI) services that help developers build cognitive intelligence into applications without having direct AI or data science skills or knowledge. [doc1]. Azure Machine Learning is a cloud service for accelerating and managing the machine learning project lifecycle. [doc1].",
                    "end_turn": true
                }
            ]
        }
    ]
}
Parameters Type Required? Default Description
messages array Required null The messages to generate chat completions for, in the chat format.
dataSources array Required The data sources to be used for the Azure OpenAI on your data feature.
temperature number Optional 0 What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.
top_p number Optional 1 An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.
stream boolean Optional false If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a message "messages": [{"delta": {"content": "[DONE]"}, "index": 2, "end_turn": true}]
stop string or array Optional null Up to 2 sequences where the API will stop generating further tokens.
max_tokens integer Optional 1000 The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return is 4096 - prompt_tokens.

The following parameters can be used inside of the parameters field inside of dataSources.

Parameters Type Required? Default Description
type string Required null The data source to be used for the Azure OpenAI on your data feature. For Azure Cognitive search the value is AzureCognitiveSearch.
endpoint string Required null The data source endpoint.
key string Required null One of the Azure Cognitive Search admin keys for your service.
indexName string Required null The search index to be used.
fieldsMapping dictionary Optional null Index data column mapping.
inScope boolean Optional true If set, this value will limit responses specific to the grounding data content.
topNDocuments number Optional 5 Number of documents that need to be fetched for document augmentation.
queryType string Optional simple Indicates which query option will be used for Azure Cognitive Search. Available types: simple, semantic, vector, vectorSimpleHybrid, vectorSemanticHybrid.
semanticConfiguration string Optional null The semantic search configuration. Only required when queryType is set to semantic or vectorSemanticHybrid.
roleInformation string Optional null Gives the model instructions about how it should behave and the context it should reference when generating a response. Corresponds to the "System Message" in Azure OpenAI Studio. See Using your data for more information. There’s a 100 token limit, which counts towards the overall token limit.
filter string Optional null The filter pattern used for restricting access to sensitive documents
embeddingEndpoint string Optional null The endpoint URL for an Ada embedding model deployment, generally of the format https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/embeddings?api-version=2023-05-15. Used for vector search.
embeddingKey string Optional null The API key for an Ada embedding model deployment. Used for vector search.

Image generation

Request a generated image

Generate a batch of images from a text caption.

POST https://{your-resource-name}.openai.azure.com/openai/images/generations:submit?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
api-version string Required The API version to use for this operation. This follows the YYYY-MM-DD format.

Supported versions

Request body

Parameter Type Required? Default Description
prompt string Required A text description of the desired image(s). The maximum length is 1000 characters.
n integer Optional 1 The number of images to generate. Must be between 1 and 5.
size string Optional 1024x1024 The size of the generated images. Must be one of 256x256, 512x512, or 1024x1024.

Example request

curl -X POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/images/generations:submit?api-version=2023-06-01-preview \
  -H "Content-Type: application/json" \
  -H "api-key: YOUR_API_KEY" \
  -d '{
"prompt": "An avocado chair",
"size": "512x512",
"n": 3
}'

Example response

The operation returns a 202 status code and an GenerateImagesResponse JSON object containing the ID and status of the operation.

{
  "id": "f508bcf2-e651-4b4b-85a7-58ad77981ffa",
  "status": "notRunning"
}

Get a generated image result

Use this API to retrieve the results of an image generation operation. Image generation is currently only available with api-version=2023-06-01-preview.

GET https://{your-resource-name}.openai.azure.com/openai/operations/images/{operation-id}?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
operation-id string Required The GUID that identifies the original image generation request.

Supported versions

Example request

curl -X GET "https://{your-resource-name}.openai.azure.com/openai/operations/images/{operation-id}?api-version=2023-06-01-preview"
-H "Content-Type: application/json"
-H "Api-Key: {api key}"

Example response

Upon success the operation returns a 200 status code and an OperationResponse JSON object. The status field can be "notRunning" (task is queued but hasn't started yet), "running", "succeeded", "canceled" (task has timed out), "failed", or "deleted". A succeeded status indicates that the generated image is available for download at the given URL. If multiple images were generated, their URLs are all returned in the result.data field.

{
  "created": 1685064331,
  "expires": 1685150737,
  "id": "4b755937-3173-4b49-bf3f-da6702a3971a",
  "result": {
    "data": [
      {
        "url": "<URL_TO_IMAGE>"
      },
      {
        "url": "<URL_TO_NEXT_IMAGE>"
      },
      ...
    ]
  },
  "status": "succeeded"
}

Delete a generated image from the server

You can use the operation ID returned by the request to delete the corresponding image from the Azure server. Generated images are automatically deleted after 24 hours by default, but you can trigger the deletion earlier if you want to.

DELETE https://{your-resource-name}.openai.azure.com/openai/operations/images/{operation-id}?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
operation-id string Required The GUID that identifies the original image generation request.

Supported versions

Example request

curl -X DELETE "https://{your-resource-name}.openai.azure.com/openai/operations/images/{operation-id}?api-version=2023-06-01-preview"
-H "Content-Type: application/json"
-H "Api-Key: {api key}"

Response

The operation returns a 204 status code if successful. This API only succeeds if the operation is in an end state (not running).

Speech to text

Request a speech to text transcription

Transcribes an audio file.

POST https://{your-resource-name}.openai.azure.com/openai/deployments/{deployment-id}/audio/transcriptions?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
deployment-id string Required The name of your Whisper model deployment such as MyWhisperDeployment. You're required to first deploy a Whisper model before you can make calls.
api-version string Required The API version to use for this operation. This value follows the YYYY-MM-DD format.

Supported versions

  • 2023-09-01-preview

Request body

Parameter Type Required? Default Description
file file Yes N/A The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.

The file size limit for the Azure OpenAI Whisper model is 25 MB. If you need to transcribe a file larger than 25 MB, break it into chunks. Alternatively you can use the Azure AI Speech batch transcription API.

You can get sample audio files from the Azure AI Speech SDK repository at GitHub.
language string No Null The language of the input audio such as fr. Supplying the input language in ISO-639-1 format improves accuracy and latency.

For the list of supported languages, see the OpenAI documentation.
prompt string No Null An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.

For more information about prompts including example use cases, see the OpenAI documentation.
response_format string No json The format of the transcript output, in one of these options: json, text, srt, verbose_json, or vtt.

The default value is json.
temperature number No 0 The sampling temperature, between 0 and 1.

Higher values like 0.8 makes the output more random, while lower values like 0.2 make it more focused and deterministic. If set to 0, the model uses log probability to automatically increase the temperature until certain thresholds are hit.

The default value is 0.

Example request

curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/audio/transcriptions?api-version=2023-09-01-preview \
  -H "Content-Type: multipart/form-data" \
  -H "api-key: $YOUR_API_KEY" \
  -F file="@./YOUR_AUDIO_FILE_NAME.wav" \
  -F "language=en" \
  -F "prompt=The transcript contains zoology terms and geographical locations." \
  -F "temperature=0" \
  -F "response_format=srt"

Example response

1
00:00:00,960 --> 00:00:07,680
The ocelot, Lepardus paradalis, is a small wild cat native to the southwestern United States,

2
00:00:07,680 --> 00:00:13,520
Mexico, and Central and South America. This medium-sized cat is characterized by

3
00:00:13,520 --> 00:00:18,960
solid black spots and streaks on its coat, round ears, and white neck and undersides.

4
00:00:19,760 --> 00:00:27,840
It weighs between 8 and 15.5 kilograms, 18 and 34 pounds, and reaches 40 to 50 centimeters

5
00:00:27,840 --> 00:00:34,560
16 to 20 inches at the shoulders. It was first described by Carl Linnaeus in 1758.

6
00:00:35,360 --> 00:00:42,880
Two subspecies are recognized, L. p. paradalis and L. p. mitis. Typically active during twilight

7
00:00:42,880 --> 00:00:48,480
and at night, the ocelot tends to be solitary and territorial. It is efficient at climbing,

8
00:00:48,480 --> 00:00:54,480
leaping, and swimming. It preys on small terrestrial mammals such as armadillo, opossum,

9
00:00:54,480 --> 00:00:56,480
and lagomorphs.

Request a speech to text translation

Translates an audio file from another language into English. For the list of supported languages, see the OpenAI documentation.

POST https://{your-resource-name}.openai.azure.com/openai/deployments/{deployment-id}/audio/translations?api-version={api-version}

Path parameters

Parameter Type Required? Description
your-resource-name string Required The name of your Azure OpenAI Resource.
deployment-id string Required The name of your Whisper model deployment such as MyWhisperDeployment. You're required to first deploy a Whisper model before you can make calls.
api-version string Required The API version to use for this operation. This value follows the YYYY-MM-DD format.

Supported versions

  • 2023-09-01-preview

Request body

Parameter Type Required? Default Description
file file Yes N/A The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.

The file size limit for the Azure OpenAI Whisper model is 25 MB. If you need to transcribe a file larger than 25 MB, break it into chunks.

You can download sample audio files from the Azure AI Speech SDK repository at GitHub.
prompt string No Null An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.

For more information about prompts including example use cases, see the OpenAI documentation.
response_format string No json The format of the transcript output, in one of these options: json, text, srt, verbose_json, or vtt.

The default value is json.
temperature number No 0 The sampling temperature, between 0 and 1.

Higher values like 0.8 makes the output more random, while lower values like 0.2 make it more focused and deterministic. If set to 0, the model uses log probability to automatically increase the temperature until certain thresholds are hit.

The default value is 0.

Example request

curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/audio/translations?api-version=2023-09-01-preview \
  -H "Content-Type: multipart/form-data" \
  -H "api-key: $YOUR_API_KEY" \
  -F file="@./YOUR_AUDIO_FILE_NAME.wav" \
  -F "temperature=0" \
  -F "response_format=json"

Example response

{
  "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
}

Management APIs

Azure OpenAI is deployed as a part of the Azure AI services. All Azure AI services rely on the same set of management APIs for creation, update and delete operations. The management APIs are also used for deploying models within an OpenAI resource.

Management APIs reference documentation

Next steps

Learn about Models, and fine-tuning with the REST API. Learn more about the underlying models that power Azure OpenAI.