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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

We currently do not support batching of embeddings into a single API call. If you receive the error InvalidRequestError: Too many inputs. The max number of inputs is 1. We hope to increase the number of inputs per request soon., this typically occurs when an array of embeddings is attempted to be passed as a batch rather than a single string. The string can be up to 8191 tokens in length when using the text-embedding-ada-002 (Version 2) 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 Yes N/A Input text to get embeddings for, encoded as a string. The number of input tokens varies depending on what model you are using.
Unless you're embedding code, we suggest replacing newlines (\n) in your input with a single space, as we have observed inferior results when newlines are present.
user string No Null A unique identifier representing for 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 ChatGPT 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 Cognitive 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 Cognitive Services also support customer managed keys. Azure Cognitive 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 messages to generate chat completions for, in the chat format.
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.

Management APIs

Azure OpenAI is deployed as a part of the Azure Cognitive Services. All Cognitive 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 managing deployments, models, and fine-tuning with the REST API. Learn more about the underlying models that power Azure OpenAI.