specification/cognitiveservices/data-plane/AzureOpenAI/inference/stable/2024-06-01/inference.yaml (2,083 lines of code) (raw):
openapi: 3.0.0
info:
title: Azure OpenAI Service API
description: Azure OpenAI APIs for completions and search
version: '2024-06-01'
servers:
- url: https://{endpoint}/openai
variables:
endpoint:
default: your-resource-name.openai.azure.com
security:
- bearer:
- api.read
- apiKey: []
paths:
/deployments/{deployment-id}/completions:
post:
summary: Creates a completion for the provided prompt, parameters and chosen model.
operationId: Completions_Create
parameters:
- in: path
name: deployment-id
required: true
schema:
type: string
example: davinci
description: Deployment id of the model which was deployed.
- in: query
name: api-version
required: true
schema:
type: string
example: 2024-06-01
description: api version
requestBody:
required: true
content:
application/json:
schema:
type: object
properties:
prompt:
description: |-
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 is not specified the model will generate as if from the beginning of a new document. Maximum allowed size of string list is 2048.
oneOf:
- type: string
default: ''
example: This is a test.
nullable: true
- type: array
items:
type: string
default: ''
example: This is a test.
nullable: false
description: Array size minimum of 1 and maximum of 2048
max_tokens:
description: The token count of your prompt plus max_tokens cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096). Has minimum of 0.
type: integer
default: 16
example: 16
nullable: true
temperature:
description: |-
What sampling temperature to use. 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.
type: number
default: 1
example: 1
nullable: true
top_p:
description: |-
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.
type: number
default: 1
example: 1
nullable: true
logit_bias:
description: Defaults to 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.
type: object
nullable: false
user:
description: A unique identifier representing your end-user, which can help monitoring and detecting abuse
type: string
nullable: false
'n':
description: |-
How many completions to generate for each prompt. Minimum of 1 and maximum of 128 allowed.
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.
type: integer
default: 1
example: 1
nullable: true
stream:
description: '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.'
type: boolean
nullable: true
default: false
logprobs:
description: |-
Include the log probabilities on the logprobs most likely tokens, as well the chosen tokens. For example, if logprobs is 5, the API will return a list of the 5 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.
Minimum of 0 and maximum of 5 allowed.
type: integer
default: null
nullable: true
suffix:
type: string
nullable: true
description: The suffix that comes after a completion of inserted text.
echo:
description: Echo back the prompt in addition to the completion
type: boolean
default: false
nullable: true
stop:
description: Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
oneOf:
- type: string
default: <|endoftext|>
example: |+
nullable: true
- type: array
items:
type: string
example: |+
nullable: false
description: Array minimum size of 1 and maximum of 4
completion_config:
type: string
nullable: true
presence_penalty:
description: 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.
type: number
default: 0
frequency_penalty:
description: 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.
type: number
default: 0
best_of:
description: |-
Generates best_of completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot 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. Has maximum value of 128.
type: integer
example:
prompt: |-
Negate the following sentence.The price for bubblegum increased on thursday.
Negated Sentence:
max_tokens: 50
responses:
'200':
description: OK
content:
application/json:
schema:
type: object
properties:
id:
type: string
object:
type: string
created:
type: integer
model:
type: string
prompt_filter_results:
$ref: '#/components/schemas/promptFilterResults'
choices:
type: array
items:
type: object
properties:
text:
type: string
index:
type: integer
logprobs:
type: object
properties:
tokens:
type: array
items:
type: string
token_logprobs:
type: array
items:
type: number
top_logprobs:
type: array
items:
type: object
additionalProperties:
type: number
text_offset:
type: array
items:
type: integer
nullable: true
finish_reason:
type: string
content_filter_results:
$ref: '#/components/schemas/contentFilterChoiceResults'
usage:
type: object
properties:
completion_tokens:
type: number
format: int32
prompt_tokens:
type: number
format: int32
total_tokens:
type: number
format: int32
required:
- prompt_tokens
- total_tokens
- completion_tokens
required:
- id
- object
- created
- model
- choices
example:
model: davinci
object: text_completion
id: cmpl-4509KAos68kxOqpE2uYGw81j6m7uo
created: 1637097562
choices:
- index: 0
text: The price for bubblegum decreased on thursday.
logprobs: null
finish_reason: stop
headers:
apim-request-id:
description: Request ID for troubleshooting purposes
schema:
type: string
default:
description: Service unavailable
content:
application/json:
schema:
$ref: '#/components/schemas/errorResponse'
headers:
apim-request-id:
description: Request ID for troubleshooting purposes
schema:
type: string
/deployments/{deployment-id}/embeddings:
post:
summary: Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
operationId: embeddings_create
parameters:
- in: path
name: deployment-id
required: true
schema:
type: string
example: ada-search-index-v1
description: The deployment id of the model which was deployed.
- in: query
name: api-version
required: true
schema:
type: string
example: '2024-06-01'
description: api version
requestBody:
required: true
content:
application/json:
schema:
type: object
additionalProperties: true
properties:
input:
description: |-
Input text to get embeddings for, encoded as a string. To get embeddings for multiple inputs in a single request, pass an array of strings. Each input must not exceed 2048 tokens in length.
Unless you are embedding code, we suggest replacing newlines (\n) in your input with a single space, as we have observed inferior results when newlines are present.
oneOf:
- type: string
default: ''
example: This is a test.
nullable: true
- type: array
minItems: 1
maxItems: 2048
items:
type: string
minLength: 1
example: This is a test.
nullable: false
user:
description: A unique identifier representing your end-user, which can help monitoring and detecting abuse.
type: string
nullable: false
input_type:
description: input type of embedding search to use
type: string
example: query
encoding_format:
description: The format to return the embeddings in. Can be either `float` or `base64`. Defaults to `float`.
type: string
example: base64
nullable: true
dimensions:
description: The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.
type: integer
example: 1
nullable: true
required:
- input
responses:
'200':
description: OK
content:
application/json:
schema:
type: object
properties:
object:
type: string
model:
type: string
data:
type: array
items:
type: object
properties:
index:
type: integer
object:
type: string
embedding:
type: array
items:
type: number
required:
- index
- object
- embedding
usage:
type: object
properties:
prompt_tokens:
type: integer
total_tokens:
type: integer
required:
- prompt_tokens
- total_tokens
required:
- object
- model
- data
- usage
x-ms-examples:
Create a embeddings.:
$ref: ./examples/embeddings.yaml
/deployments/{deployment-id}/chat/completions:
post:
summary: Creates a completion for the chat message
operationId: ChatCompletions_Create
parameters:
- in: path
name: deployment-id
required: true
schema:
type: string
description: Deployment id of the model which was deployed.
- in: query
name: api-version
required: true
schema:
type: string
example: '2024-06-01'
description: api version
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/createChatCompletionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/createChatCompletionResponse'
headers:
apim-request-id:
description: Request ID for troubleshooting purposes
schema:
type: string
default:
description: Service unavailable
content:
application/json:
schema:
$ref: '#/components/schemas/errorResponse'
headers:
apim-request-id:
description: Request ID for troubleshooting purposes
schema:
type: string
x-ms-examples:
Create a chat completion.:
$ref: ./examples/chat_completions.yaml
Creates a completion based on Azure Search data and system-assigned managed identity.:
$ref: ./examples/chat_completions_azure_search_minimum.yaml
Creates a completion based on Azure Search vector data, previous assistant message and user-assigned managed identity.:
$ref: ./examples/chat_completions_azure_search_advanced.yaml
Creates a completion for the provided Azure Cosmos DB.:
$ref: ./examples/chat_completions_cosmos_db.yaml
/deployments/{deployment-id}/audio/transcriptions:
post:
summary: Transcribes audio into the input language.
operationId: Transcriptions_Create
parameters:
- in: path
name: deployment-id
required: true
schema:
type: string
example: whisper
description: Deployment id of the whisper model.
- in: query
name: api-version
required: true
schema:
type: string
example: '2024-06-01'
description: api version
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/createTranscriptionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
oneOf:
- $ref: '#/components/schemas/audioResponse'
- $ref: '#/components/schemas/audioVerboseResponse'
text/plain:
schema:
type: string
description: Transcribed text in the output format (when response_format was one of text, vtt or srt).
x-ms-examples:
Create an audio transcription with json response format.:
$ref: ./examples/audio_transcription_object.yaml
Create an audio transcription with text response format.:
$ref: ./examples/audio_transcription_text.yaml
/deployments/{deployment-id}/audio/translations:
post:
summary: Transcribes and translates input audio into English text.
operationId: Translations_Create
parameters:
- in: path
name: deployment-id
required: true
schema:
type: string
example: whisper
description: Deployment id of the whisper model which was deployed.
- in: query
name: api-version
required: true
schema:
type: string
example: '2024-06-01'
description: api version
requestBody:
required: true
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/createTranslationRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
oneOf:
- $ref: '#/components/schemas/audioResponse'
- $ref: '#/components/schemas/audioVerboseResponse'
text/plain:
schema:
type: string
description: Transcribed text in the output format (when response_format was one of text, vtt or srt).
x-ms-examples:
Create an audio translation with json response format.:
$ref: ./examples/audio_translation_object.yaml
Create an audio translation with text response format.:
$ref: ./examples/audio_translation_text.yaml
/deployments/{deployment-id}/images/generations:
post:
summary: Generates a batch of images from a text caption on a given DALLE model deployment
operationId: ImageGenerations_Create
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/imageGenerationsRequest'
parameters:
- in: path
name: deployment-id
required: true
schema:
type: string
example: dalle-deployment
description: Deployment id of the dalle model which was deployed.
- in: query
name: api-version
required: true
schema:
type: string
example: '2024-06-01'
description: api version
responses:
'200':
description: Ok
content:
application/json:
schema:
$ref: '#/components/schemas/generateImagesResponse'
default:
description: An error occurred.
content:
application/json:
schema:
$ref: '#/components/schemas/dalleErrorResponse'
x-ms-examples:
Create an image.:
$ref: ./examples/image_generation.yaml
components:
schemas:
errorResponse:
type: object
properties:
error:
$ref: '#/components/schemas/error'
errorBase:
type: object
properties:
code:
type: string
message:
type: string
error:
type: object
allOf:
- $ref: '#/components/schemas/errorBase'
properties:
param:
type: string
type:
type: string
inner_error:
$ref: '#/components/schemas/innerError'
innerError:
description: Inner error with additional details.
type: object
properties:
code:
$ref: '#/components/schemas/innerErrorCode'
content_filter_results:
$ref: '#/components/schemas/contentFilterPromptResults'
innerErrorCode:
description: Error codes for the inner error object.
enum:
- ResponsibleAIPolicyViolation
type: string
x-ms-enum:
name: InnerErrorCode
modelAsString: true
values:
- value: ResponsibleAIPolicyViolation
description: The prompt violated one of more content filter rules.
dalleErrorResponse:
type: object
properties:
error:
$ref: '#/components/schemas/dalleError'
dalleError:
type: object
allOf:
- $ref: '#/components/schemas/errorBase'
properties:
param:
type: string
type:
type: string
inner_error:
$ref: '#/components/schemas/dalleInnerError'
dalleInnerError:
description: Inner error with additional details.
type: object
properties:
code:
$ref: '#/components/schemas/innerErrorCode'
content_filter_results:
$ref: '#/components/schemas/dalleFilterResults'
revised_prompt:
type: string
description: The prompt that was used to generate the image, if there was any revision to the prompt.
contentFilterResultBase:
type: object
properties:
filtered:
type: boolean
required:
- filtered
contentFilterSeverityResult:
type: object
allOf:
- $ref: '#/components/schemas/contentFilterResultBase'
- properties:
severity:
type: string
enum:
- safe
- low
- medium
- high
x-ms-enum:
name: ContentFilterSeverity
modelAsString: true
values:
- value: safe
description: General content or related content in generic or non-harmful contexts.
- value: low
description: Harmful content at a low intensity and risk level.
- value: medium
description: Harmful content at a medium intensity and risk level.
- value: high
description: Harmful content at a high intensity and risk level.
required:
- severity
- filtered
contentFilterDetectedResult:
type: object
allOf:
- $ref: '#/components/schemas/contentFilterResultBase'
- properties:
detected:
type: boolean
required:
- detected
- filtered
contentFilterDetectedWithCitationResult:
type: object
allOf:
- $ref: '#/components/schemas/contentFilterDetectedResult'
- properties:
citation:
type: object
properties:
URL:
type: string
license:
type: string
required:
- detected
- filtered
contentFilterResultsBase:
type: object
description: Information about the content filtering results.
properties:
sexual:
$ref: '#/components/schemas/contentFilterSeverityResult'
violence:
$ref: '#/components/schemas/contentFilterSeverityResult'
hate:
$ref: '#/components/schemas/contentFilterSeverityResult'
self_harm:
$ref: '#/components/schemas/contentFilterSeverityResult'
profanity:
$ref: '#/components/schemas/contentFilterDetectedResult'
error:
$ref: '#/components/schemas/errorBase'
contentFilterPromptResults:
type: object
description: Information about the content filtering category (hate, sexual, violence, self_harm), if it has been detected, as well as the severity level (very_low, low, medium, high-scale that determines the intensity and risk level of harmful content) and if it has been filtered or not. Information about jailbreak content and profanity, if it has been detected, and if it has been filtered or not. And information about customer block list, if it has been filtered and its id.
allOf:
- $ref: '#/components/schemas/contentFilterResultsBase'
- properties:
jailbreak:
$ref: '#/components/schemas/contentFilterDetectedResult'
contentFilterChoiceResults:
type: object
description: Information about the content filtering category (hate, sexual, violence, self_harm), if it has been detected, as well as the severity level (very_low, low, medium, high-scale that determines the intensity and risk level of harmful content) and if it has been filtered or not. Information about third party text and profanity, if it has been detected, and if it has been filtered or not. And information about customer block list, if it has been filtered and its id.
allOf:
- $ref: '#/components/schemas/contentFilterResultsBase'
- properties:
protected_material_text:
$ref: '#/components/schemas/contentFilterDetectedResult'
- properties:
protected_material_code:
$ref: '#/components/schemas/contentFilterDetectedWithCitationResult'
promptFilterResult:
type: object
description: Content filtering results for a single prompt in the request.
properties:
prompt_index:
type: integer
content_filter_results:
$ref: '#/components/schemas/contentFilterPromptResults'
promptFilterResults:
type: array
description: Content filtering results for zero or more prompts in the request. In a streaming request, results for different prompts may arrive at different times or in different orders.
items:
$ref: '#/components/schemas/promptFilterResult'
dalleContentFilterResults:
type: object
description: Information about the content filtering results.
properties:
sexual:
$ref: '#/components/schemas/contentFilterSeverityResult'
violence:
$ref: '#/components/schemas/contentFilterSeverityResult'
hate:
$ref: '#/components/schemas/contentFilterSeverityResult'
self_harm:
$ref: '#/components/schemas/contentFilterSeverityResult'
dalleFilterResults:
type: object
description: Information about the content filtering category (hate, sexual, violence, self_harm), if it has been detected, as well as the severity level (very_low, low, medium, high-scale that determines the intensity and risk level of harmful content) and if it has been filtered or not. Information about jailbreak content and profanity, if it has been detected, and if it has been filtered or not. And information about customer block list, if it has been filtered and its id.
allOf:
- $ref: '#/components/schemas/dalleContentFilterResults'
- properties:
profanity:
$ref: '#/components/schemas/contentFilterDetectedResult'
jailbreak:
$ref: '#/components/schemas/contentFilterDetectedResult'
chatCompletionsRequestCommon:
type: object
properties:
temperature:
description: |-
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.
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
top_p:
description: |-
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.
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
stream:
description: '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.'
type: boolean
nullable: true
default: false
stop:
description: Up to 4 sequences where the API will stop generating further tokens.
oneOf:
- type: string
nullable: true
- type: array
items:
type: string
nullable: false
minItems: 1
maxItems: 4
description: Array minimum size of 1 and maximum of 4
default: null
max_tokens:
description: 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).
type: integer
default: 4096
presence_penalty:
description: 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.
type: number
default: 0
minimum: -2
maximum: 2
frequency_penalty:
description: 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.
type: number
default: 0
minimum: -2
maximum: 2
logit_bias:
description: 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.
type: object
nullable: true
user:
description: A unique identifier representing your end-user, which can help Azure OpenAI to monitor and detect abuse.
type: string
example: user-1234
nullable: false
createChatCompletionRequest:
type: object
allOf:
- $ref: '#/components/schemas/chatCompletionsRequestCommon'
- properties:
messages:
description: A list of messages comprising the conversation so far. [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb).
type: array
minItems: 1
items:
$ref: '#/components/schemas/chatCompletionRequestMessage'
data_sources:
type: array
description: |2-
The configuration entries for Azure OpenAI chat extensions that use them.
This additional specification is only compatible with Azure OpenAI.
items:
$ref: '#/components/schemas/azureChatExtensionConfiguration'
'n':
type: integer
minimum: 1
maximum: 128
default: 1
example: 1
nullable: true
description: How many chat completion choices to generate for each input message.
seed:
type: integer
minimum: -9223372036854775808
maximum: 9223372036854775807
default: 0
example: 1
nullable: true
description: If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result.Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.
logprobs:
description: Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`. This option is currently not available on the `gpt-4-vision-preview` model.
type: boolean
default: false
nullable: true
top_logprobs:
description: An integer between 0 and 5 specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to `true` if this parameter is used.
type: integer
minimum: 0
maximum: 5
nullable: true
response_format:
type: object
description: An object specifying the format that the model must output. Used to enable JSON mode.
properties:
type:
$ref: '#/components/schemas/chatCompletionResponseFormat'
tools:
description: A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for.
type: array
minItems: 1
items:
$ref: '#/components/schemas/chatCompletionTool'
tool_choice:
$ref: '#/components/schemas/chatCompletionToolChoiceOption'
functions:
description: Deprecated in favor of `tools`. A list of functions the model may generate JSON inputs for.
type: array
minItems: 1
maxItems: 128
items:
$ref: '#/components/schemas/chatCompletionFunction'
function_call:
description: Deprecated in favor of `tool_choice`. 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.
oneOf:
- type: string
enum:
- none
- auto
description: '`none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function.'
- type: object
description: 'Specifying a particular function via `{"name": "my_function"}` forces the model to call that function.'
properties:
name:
type: string
description: The name of the function to call.
required:
- name
required:
- messages
chatCompletionResponseFormat:
type: string
enum:
- text
- json_object
default: text
example: json_object
nullable: true
description: Setting to `json_object` enables JSON mode. This guarantees that the message the model generates is valid JSON.
x-ms-enum:
name: ChatCompletionResponseFormat
modelAsString: true
values:
- value: text
description: Response format is a plain text string.
- value: json_object
description: Response format is a JSON object.
chatCompletionFunction:
type: object
properties:
name:
type: string
description: The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
description:
type: string
description: The description of what the function does.
parameters:
$ref: '#/components/schemas/chatCompletionFunctionParameters'
required:
- name
chatCompletionFunctionParameters:
type: object
description: The parameters the functions accepts, described as a JSON Schema object. See the [guide](/docs/guides/gpt/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.
additionalProperties: true
chatCompletionRequestMessage:
type: object
properties:
role:
$ref: '#/components/schemas/chatCompletionRequestMessageRole'
discriminator:
propertyName: role
mapping:
system: '#/components/schemas/chatCompletionRequestMessageSystem'
user: '#/components/schemas/chatCompletionRequestMessageUser'
assistant: '#/components/schemas/chatCompletionRequestMessageAssistant'
tool: '#/components/schemas/chatCompletionRequestMessageTool'
function: '#/components/schemas/chatCompletionRequestMessageFunction'
required:
- role
chatCompletionRequestMessageRole:
type: string
enum:
- system
- user
- assistant
- tool
- function
description: The role of the messages author.
x-ms-enum:
name: ChatCompletionRequestMessageRole
modelAsString: true
values:
- value: system
description: The message author role is system.
- value: user
description: The message author role is user.
- value: assistant
description: The message author role is assistant.
- value: tool
description: The message author role is tool.
- value: function
description: Deprecated. The message author role is function.
chatCompletionRequestMessageSystem:
allOf:
- $ref: '#/components/schemas/chatCompletionRequestMessage'
- type: object
properties:
content:
type: string
description: The contents of the message.
nullable: true
required:
- content
chatCompletionRequestMessageUser:
allOf:
- $ref: '#/components/schemas/chatCompletionRequestMessage'
- type: object
properties:
content:
oneOf:
- type: string
description: The contents of the message.
- type: array
description: An array of content parts with a defined type, each can be of type `text` or `image_url` when passing in images. You can pass multiple images by adding multiple `image_url` content parts. Image input is only supported when using the `gpt-4-visual-preview` model.
minimum: 1
items:
$ref: '#/components/schemas/chatCompletionRequestMessageContentPart'
nullable: true
required:
- content
chatCompletionRequestMessageContentPart:
type: object
properties:
type:
$ref: '#/components/schemas/chatCompletionRequestMessageContentPartType'
discriminator:
propertyName: type
mapping:
text: '#/components/schemas/chatCompletionRequestMessageContentPartText'
image_url: '#/components/schemas/chatCompletionRequestMessageContentPartImage'
required:
- type
chatCompletionRequestMessageContentPartType:
type: string
enum:
- text
- image_url
description: The type of the content part.
x-ms-enum:
name: ChatCompletionRequestMessageContentPartType
modelAsString: true
values:
- value: text
description: The content part type is text.
- value: image_url
description: The content part type is image_url.
chatCompletionRequestMessageContentPartText:
allOf:
- $ref: '#/components/schemas/chatCompletionRequestMessageContentPart'
- type: object
properties:
text:
type: string
description: The text content.
required:
- text
chatCompletionRequestMessageContentPartImage:
allOf:
- $ref: '#/components/schemas/chatCompletionRequestMessageContentPart'
- type: object
properties:
url:
type: string
description: Either a URL of the image or the base64 encoded image data.
format: uri
detail:
$ref: '#/components/schemas/imageDetailLevel'
required:
- url
imageDetailLevel:
type: string
description: Specifies the detail level of the image.
enum:
- auto
- low
- high
default: auto
x-ms-enum:
name: ImageDetailLevel
modelAsString: true
values:
- value: auto
description: The image detail level is auto.
- value: low
description: The image detail level is low.
- value: high
description: The image detail level is high.
chatCompletionRequestMessageAssistant:
allOf:
- $ref: '#/components/schemas/chatCompletionRequestMessage'
- type: object
properties:
content:
type: string
description: The contents of the message.
nullable: true
tool_calls:
type: array
description: The tool calls generated by the model, such as function calls.
items:
$ref: '#/components/schemas/chatCompletionMessageToolCall'
context:
$ref: '#/components/schemas/azureChatExtensionsMessageContext'
required:
- content
azureChatExtensionConfiguration:
required:
- type
type: object
properties:
type:
$ref: '#/components/schemas/azureChatExtensionType'
description: |2-
A representation of configuration data for a single Azure OpenAI chat extension. This will be used by a chat
completions request that should use Azure OpenAI chat extensions to augment the response behavior.
The use of this configuration is compatible only with Azure OpenAI.
discriminator:
propertyName: type
mapping:
azure_search: '#/components/schemas/azureSearchChatExtensionConfiguration'
azure_cosmos_db: '#/components/schemas/azureCosmosDBChatExtensionConfiguration'
azureChatExtensionType:
type: string
description: |2-
A representation of configuration data for a single Azure OpenAI chat extension. This will be used by a chat
completions request that should use Azure OpenAI chat extensions to augment the response behavior.
The use of this configuration is compatible only with Azure OpenAI.
enum:
- azure_search
- azure_cosmos_db
x-ms-enum:
name: AzureChatExtensionType
modelAsString: true
values:
- name: azureSearch
value: azure_search
description: Represents the use of Azure Search as an Azure OpenAI chat extension.
- name: azureCosmosDB
value: azure_cosmos_db
description: Represents the use of Azure Cosmos DB as an Azure OpenAI chat extension.
azureSearchChatExtensionConfiguration:
required:
- parameters
description: |-
A specific representation of configurable options for Azure Search when using it as an Azure OpenAI chat
extension.
allOf:
- $ref: '#/components/schemas/azureChatExtensionConfiguration'
- properties:
parameters:
$ref: '#/components/schemas/azureSearchChatExtensionParameters'
x-ms-discriminator-value: azure_search
azureSearchChatExtensionParameters:
required:
- authentication
- endpoint
- index_name
type: object
properties:
authentication:
oneOf:
- $ref: '#/components/schemas/onYourDataApiKeyAuthenticationOptions'
- $ref: '#/components/schemas/onYourDataSystemAssignedManagedIdentityAuthenticationOptions'
- $ref: '#/components/schemas/onYourDataUserAssignedManagedIdentityAuthenticationOptions'
top_n_documents:
type: integer
description: The configured top number of documents to feature for the configured query.
format: int32
in_scope:
type: boolean
description: Whether queries should be restricted to use of indexed data.
strictness:
maximum: 5
minimum: 1
type: integer
description: The configured strictness of the search relevance filtering. The higher of strictness, the higher of the precision but lower recall of the answer.
format: int32
role_information:
type: string
description: Give the model instructions about how it should behave and any context it should reference when generating a response. You can describe the assistant's personality and tell it how to format responses. There's a 100 token limit for it, and it counts against the overall token limit.
endpoint:
type: string
description: The absolute endpoint path for the Azure Search resource to use.
format: uri
index_name:
type: string
description: The name of the index to use as available in the referenced Azure Search resource.
fields_mapping:
$ref: '#/components/schemas/azureSearchIndexFieldMappingOptions'
query_type:
$ref: '#/components/schemas/azureSearchQueryType'
semantic_configuration:
type: string
description: The additional semantic configuration for the query.
filter:
type: string
description: Search filter.
embedding_dependency:
oneOf:
- $ref: '#/components/schemas/onYourDataEndpointVectorizationSource'
- $ref: '#/components/schemas/onYourDataDeploymentNameVectorizationSource'
description: Parameters for Azure Search when used as an Azure OpenAI chat extension.
azureSearchIndexFieldMappingOptions:
type: object
properties:
title_field:
type: string
description: The name of the index field to use as a title.
url_field:
type: string
description: The name of the index field to use as a URL.
filepath_field:
type: string
description: The name of the index field to use as a filepath.
content_fields:
type: array
description: The names of index fields that should be treated as content.
items:
type: string
content_fields_separator:
type: string
description: The separator pattern that content fields should use.
vector_fields:
type: array
description: The names of fields that represent vector data.
items:
type: string
description: Optional settings to control how fields are processed when using a configured Azure Search resource.
azureSearchQueryType:
type: string
description: The type of Azure Search retrieval query that should be executed when using it as an Azure OpenAI chat extension.
enum:
- simple
- semantic
- vector
- vector_simple_hybrid
- vector_semantic_hybrid
x-ms-enum:
name: azureSearchQueryType
modelAsString: true
values:
- name: simple
value: simple
description: Represents the default, simple query parser.
- name: semantic
value: semantic
description: Represents the semantic query parser for advanced semantic modeling.
- name: vector
value: vector
description: Represents vector search over computed data.
- name: vectorSimpleHybrid
value: vector_simple_hybrid
description: Represents a combination of the simple query strategy with vector data.
- name: vectorSemanticHybrid
value: vector_semantic_hybrid
description: Represents a combination of semantic search and vector data querying.
azureCosmosDBChatExtensionConfiguration:
required:
- parameters
description: |-
A specific representation of configurable options for Azure Cosmos DB when using it as an Azure OpenAI chat
extension.
allOf:
- $ref: '#/components/schemas/azureChatExtensionConfiguration'
- properties:
parameters:
$ref: '#/components/schemas/azureCosmosDBChatExtensionParameters'
x-ms-discriminator-value: azure_cosmos_db
azureCosmosDBChatExtensionParameters:
required:
- authentication
- container_name
- database_name
- embedding_dependency
- fields_mapping
- index_name
type: object
properties:
authentication:
$ref: '#/components/schemas/onYourDataConnectionStringAuthenticationOptions'
top_n_documents:
type: integer
description: The configured top number of documents to feature for the configured query.
format: int32
in_scope:
type: boolean
description: Whether queries should be restricted to use of indexed data.
strictness:
maximum: 5
minimum: 1
type: integer
description: The configured strictness of the search relevance filtering. The higher of strictness, the higher of the precision but lower recall of the answer.
format: int32
role_information:
type: string
description: Give the model instructions about how it should behave and any context it should reference when generating a response. You can describe the assistant's personality and tell it how to format responses. There's a 100 token limit for it, and it counts against the overall token limit.
database_name:
type: string
description: The MongoDB vCore database name to use with Azure Cosmos DB.
container_name:
type: string
description: The name of the Azure Cosmos DB resource container.
index_name:
type: string
description: The MongoDB vCore index name to use with Azure Cosmos DB.
fields_mapping:
$ref: '#/components/schemas/azureCosmosDBFieldMappingOptions'
embedding_dependency:
oneOf:
- $ref: '#/components/schemas/onYourDataEndpointVectorizationSource'
- $ref: '#/components/schemas/onYourDataDeploymentNameVectorizationSource'
description: |-
Parameters to use when configuring Azure OpenAI On Your Data chat extensions when using Azure Cosmos DB for
MongoDB vCore.
azureCosmosDBFieldMappingOptions:
required:
- content_fields
- vector_fields
type: object
properties:
title_field:
type: string
description: The name of the index field to use as a title.
url_field:
type: string
description: The name of the index field to use as a URL.
filepath_field:
type: string
description: The name of the index field to use as a filepath.
content_fields:
type: array
description: The names of index fields that should be treated as content.
items:
type: string
content_fields_separator:
type: string
description: The separator pattern that content fields should use.
vector_fields:
type: array
description: The names of fields that represent vector data.
items:
type: string
description: Optional settings to control how fields are processed when using a configured Azure Cosmos DB resource.
onYourDataAuthenticationOptions:
required:
- type
type: object
properties:
type:
$ref: '#/components/schemas/onYourDataAuthenticationType'
description: The authentication options for Azure OpenAI On Your Data.
discriminator:
propertyName: type
mapping:
api_key: '#/components/schemas/onYourDataApiKeyAuthenticationOptions'
connection_string: '#/components/schemas/onYourDataConnectionStringAuthenticationOptions'
system_assigned_managed_identity: '#/components/schemas/onYourDataSystemAssignedManagedIdentityAuthenticationOptions'
user_assigned_managed_identity: '#/components/schemas/onYourDataUserAssignedManagedIdentityAuthenticationOptions'
onYourDataAuthenticationType:
type: string
description: The authentication types supported with Azure OpenAI On Your Data.
enum:
- api_key
- connection_string
- system_assigned_managed_identity
- user_assigned_managed_identity
x-ms-enum:
name: OnYourDataAuthenticationType
modelAsString: true
values:
- name: apiKey
value: api_key
description: Authentication via API key.
- name: connectionString
value: connection_string
description: Authentication via connection string.
- name: systemAssignedManagedIdentity
value: system_assigned_managed_identity
description: Authentication via system-assigned managed identity.
- name: userAssignedManagedIdentity
value: user_assigned_managed_identity
description: Authentication via user-assigned managed identity.
onYourDataApiKeyAuthenticationOptions:
required:
- key
description: The authentication options for Azure OpenAI On Your Data when using an API key.
allOf:
- $ref: '#/components/schemas/onYourDataAuthenticationOptions'
- properties:
key:
type: string
description: The API key to use for authentication.
x-ms-discriminator-value: api_key
onYourDataConnectionStringAuthenticationOptions:
required:
- connection_string
description: The authentication options for Azure OpenAI On Your Data when using a connection string.
allOf:
- $ref: '#/components/schemas/onYourDataAuthenticationOptions'
- properties:
connection_string:
type: string
description: The connection string to use for authentication.
x-ms-discriminator-value: connection_string
onYourDataSystemAssignedManagedIdentityAuthenticationOptions:
description: The authentication options for Azure OpenAI On Your Data when using a system-assigned managed identity.
allOf:
- $ref: '#/components/schemas/onYourDataAuthenticationOptions'
x-ms-discriminator-value: system_assigned_managed_identity
onYourDataUserAssignedManagedIdentityAuthenticationOptions:
required:
- managed_identity_resource_id
description: The authentication options for Azure OpenAI On Your Data when using a user-assigned managed identity.
allOf:
- $ref: '#/components/schemas/onYourDataAuthenticationOptions'
- properties:
managed_identity_resource_id:
type: string
description: The resource ID of the user-assigned managed identity to use for authentication.
x-ms-discriminator-value: user_assigned_managed_identity
onYourDataVectorizationSource:
required:
- type
type: object
properties:
type:
$ref: '#/components/schemas/onYourDataVectorizationSourceType'
description: An abstract representation of a vectorization source for Azure OpenAI On Your Data with vector search.
discriminator:
propertyName: type
mapping:
endpoint: '#/components/schemas/onYourDataEndpointVectorizationSource'
deployment_name: '#/components/schemas/onYourDataDeploymentNameVectorizationSource'
onYourDataVectorizationSourceType:
type: string
description: |-
Represents the available sources Azure OpenAI On Your Data can use to configure vectorization of data for use with
vector search.
enum:
- endpoint
- deployment_name
x-ms-enum:
name: OnYourDataVectorizationSourceType
modelAsString: true
values:
- name: endpoint
value: endpoint
description: Represents vectorization performed by public service calls to an Azure OpenAI embedding model.
- name: deploymentName
value: deployment_name
description: |-
Represents an Ada model deployment name to use. This model deployment must be in the same Azure OpenAI resource, but
On Your Data will use this model deployment via an internal call rather than a public one, which enables vector
search even in private networks.
onYourDataDeploymentNameVectorizationSource:
required:
- deployment_name
description: |-
The details of a a vectorization source, used by Azure OpenAI On Your Data when applying vector search, that is based
on an internal embeddings model deployment name in the same Azure OpenAI resource.
allOf:
- $ref: '#/components/schemas/onYourDataVectorizationSource'
- properties:
deployment_name:
type: string
description: Specifies the name of the model deployment to use for vectorization. This model deployment must be in the same Azure OpenAI resource, but On Your Data will use this model deployment via an internal call rather than a public one, which enables vector search even in private networks.
x-ms-discriminator-value: deployment_name
onYourDataEndpointVectorizationSource:
required:
- authentication
- endpoint
description: |-
The details of a a vectorization source, used by Azure OpenAI On Your Data when applying vector search, that is based
on a public Azure OpenAI endpoint call for embeddings.
allOf:
- $ref: '#/components/schemas/onYourDataVectorizationSource'
- properties:
authentication:
$ref: '#/components/schemas/onYourDataApiKeyAuthenticationOptions'
endpoint:
type: string
description: Specifies the endpoint to use for vectorization. This endpoint must be in the same Azure OpenAI resource, but On Your Data will use this endpoint via an internal call rather than a public one, which enables vector search even in private networks.
format: uri
x-ms-discriminator-value: endpoint
azureChatExtensionsMessageContext:
type: object
properties:
citations:
type: array
description: The data source retrieval result, used to generate the assistant message in the response.
items:
$ref: '#/components/schemas/citation'
x-ms-identifiers: []
intent:
type: string
description: The detected intent from the chat history, used to pass to the next turn to carry over the context.
description: |2-
A representation of the additional context information available when Azure OpenAI chat extensions are involved
in the generation of a corresponding chat completions response. This context information is only populated when
using an Azure OpenAI request configured to use a matching extension.
citation:
required:
- content
type: object
properties:
content:
type: string
description: The content of the citation.
title:
type: string
description: The title of the citation.
url:
type: string
description: The URL of the citation.
filepath:
type: string
description: The file path of the citation.
chunk_id:
type: string
description: The chunk ID of the citation.
description: citation information for a chat completions response message.
chatCompletionMessageToolCall:
type: object
properties:
id:
type: string
description: The ID of the tool call.
type:
$ref: '#/components/schemas/toolCallType'
function:
type: object
description: The function that the model called.
properties:
name:
type: string
description: The name of the function to call.
arguments:
type: string
description: 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 hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
required:
- name
- arguments
required:
- id
- type
- function
toolCallType:
type: string
enum:
- function
description: The type of the tool call, in this case `function`.
x-ms-enum:
name: ToolCallType
modelAsString: true
values:
- value: function
description: The tool call type is function.
chatCompletionRequestMessageTool:
allOf:
- $ref: '#/components/schemas/chatCompletionRequestMessage'
- type: object
nullable: true
properties:
tool_call_id:
type: string
description: Tool call that this message is responding to.
content:
type: string
description: The contents of the message.
nullable: true
required:
- tool_call_id
- content
chatCompletionRequestMessageFunction:
allOf:
- $ref: '#/components/schemas/chatCompletionRequestMessage'
- type: object
description: Deprecated. Message that represents a function.
nullable: true
properties:
role:
type: string
enum:
- function
description: The role of the messages author, in this case `function`.
name:
type: string
description: The contents of the message.
content:
type: string
description: The contents of the message.
nullable: true
required:
- function_call_id
- content
createChatCompletionResponse:
type: object
allOf:
- $ref: '#/components/schemas/chatCompletionsResponseCommon'
- properties:
prompt_filter_results:
$ref: '#/components/schemas/promptFilterResults'
choices:
type: array
items:
type: object
allOf:
- $ref: '#/components/schemas/chatCompletionChoiceCommon'
- properties:
message:
$ref: '#/components/schemas/chatCompletionResponseMessage'
content_filter_results:
$ref: '#/components/schemas/contentFilterChoiceResults'
logprobs:
$ref: '#/components/schemas/chatCompletionChoiceLogProbs'
required:
- id
- object
- created
- model
- choices
chatCompletionChoiceLogProbs:
description: Log probability information for the choice.
type: object
nullable: true
properties:
content:
description: A list of message content tokens with log probability information.
type: array
items:
$ref: '#/components/schemas/chatCompletionTokenLogprob'
nullable: true
required:
- content
chatCompletionTokenLogprob:
type: object
properties:
token:
description: The token.
type: string
logprob:
description: The log probability of this token.
type: number
bytes:
description: A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.
type: array
items:
type: integer
nullable: true
top_logprobs:
description: List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested `top_logprobs` returned.
type: array
items:
type: object
properties:
token:
description: The token.
type: string
logprob:
description: The log probability of this token.
type: number
bytes:
description: A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.
type: array
items:
type: integer
nullable: true
required:
- token
- logprob
- bytes
required:
- token
- logprob
- bytes
- top_logprobs
chatCompletionResponseMessage:
type: object
description: A chat completion message generated by the model.
properties:
role:
$ref: '#/components/schemas/chatCompletionResponseMessageRole'
content:
type: string
description: The contents of the message.
nullable: true
tool_calls:
type: array
description: The tool calls generated by the model, such as function calls.
items:
$ref: '#/components/schemas/chatCompletionMessageToolCall'
function_call:
$ref: '#/components/schemas/chatCompletionFunctionCall'
context:
$ref: '#/components/schemas/azureChatExtensionsMessageContext'
chatCompletionResponseMessageRole:
type: string
enum:
- assistant
description: The role of the author of the response message.
chatCompletionToolChoiceOption:
description: 'Controls which (if any) function is called by the model. `none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function. Specifying a particular function via `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that function.'
oneOf:
- type: string
description: '`none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function.'
enum:
- none
- auto
- required
- $ref: '#/components/schemas/chatCompletionNamedToolChoice'
chatCompletionNamedToolChoice:
type: object
description: Specifies a tool the model should use. Use to force the model to call a specific function.
properties:
type:
type: string
enum:
- function
description: The type of the tool. Currently, only `function` is supported.
function:
type: object
properties:
name:
type: string
description: The name of the function to call.
required:
- name
chatCompletionFunctionCall:
type: object
description: Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model.
properties:
name:
type: string
description: The name of the function to call.
arguments:
type: string
description: 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 hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
required:
- name
- arguments
chatCompletionsResponseCommon:
type: object
properties:
id:
type: string
description: A unique identifier for the chat completion.
object:
$ref: '#/components/schemas/chatCompletionResponseObject'
created:
type: integer
format: unixtime
description: The Unix timestamp (in seconds) of when the chat completion was created.
model:
type: string
description: The model used for the chat completion.
usage:
$ref: '#/components/schemas/completionUsage'
system_fingerprint:
type: string
description: Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.
required:
- id
- object
- created
- model
chatCompletionResponseObject:
type: string
description: The object type.
enum:
- chat.completion
x-ms-enum:
name: ChatCompletionResponseObject
modelAsString: true
values:
- value: chat.completion
description: The object type is chat completion.
completionUsage:
type: object
description: Usage statistics for the completion request.
properties:
prompt_tokens:
type: integer
description: Number of tokens in the prompt.
completion_tokens:
type: integer
description: Number of tokens in the generated completion.
total_tokens:
type: integer
description: Total number of tokens used in the request (prompt + completion).
required:
- prompt_tokens
- completion_tokens
- total_tokens
chatCompletionTool:
type: object
properties:
type:
$ref: '#/components/schemas/chatCompletionToolType'
function:
type: object
properties:
description:
type: string
description: A description of what the function does, used by the model to choose when and how to call the function.
name:
type: string
description: The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
parameters:
$ref: '#/components/schemas/chatCompletionFunctionParameters'
required:
- name
- parameters
required:
- type
- function
chatCompletionToolType:
type: string
enum:
- function
description: The type of the tool. Currently, only `function` is supported.
x-ms-enum:
name: ChatCompletionToolType
modelAsString: true
values:
- value: function
description: The tool type is function.
chatCompletionChoiceCommon:
type: object
properties:
index:
type: integer
finish_reason:
type: string
createTranslationRequest:
type: object
description: Translation request.
properties:
file:
type: string
description: The audio file to translate.
format: binary
prompt:
type: string
description: An optional text to guide the model's style or continue a previous audio segment. The prompt should be in English.
response_format:
$ref: '#/components/schemas/audioResponseFormat'
temperature:
type: number
default: 0
description: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit.
required:
- file
audioResponse:
description: Translation or transcription response when response_format was json
type: object
properties:
text:
type: string
description: Translated or transcribed text.
required:
- text
audioVerboseResponse:
description: Translation or transcription response when response_format was verbose_json
type: object
allOf:
- $ref: '#/components/schemas/audioResponse'
- properties:
task:
type: string
description: Type of audio task.
enum:
- transcribe
- translate
x-ms-enum:
modelAsString: true
language:
type: string
description: Language.
duration:
type: number
description: Duration.
segments:
type: array
items:
$ref: '#/components/schemas/audioSegment'
required:
- text
audioResponseFormat:
title: AudioResponseFormat
description: Defines the format of the output.
enum:
- json
- text
- srt
- verbose_json
- vtt
type: string
x-ms-enum:
modelAsString: true
createTranscriptionRequest:
type: object
description: Transcription request.
properties:
file:
type: string
description: The audio file object to transcribe.
format: binary
prompt:
type: string
description: An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.
response_format:
$ref: '#/components/schemas/audioResponseFormat'
temperature:
type: number
default: 0
description: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit.
language:
type: string
description: The language of the input audio. Supplying the input language in ISO-639-1 format will improve accuracy and latency.
required:
- file
audioSegment:
type: object
description: Transcription or translation segment.
properties:
id:
type: integer
description: Segment identifier.
seek:
type: number
description: Offset of the segment.
start:
type: number
description: Segment start offset.
end:
type: number
description: Segment end offset.
text:
type: string
description: Segment text.
tokens:
type: array
items:
type: number
nullable: false
description: Tokens of the text.
temperature:
type: number
description: Temperature.
avg_logprob:
type: number
description: Average log probability.
compression_ratio:
type: number
description: Compression ratio.
no_speech_prob:
type: number
description: Probability of 'no speech'.
imageQuality:
description: The quality of the image that will be generated.
type: string
enum:
- standard
- hd
default: standard
x-ms-enum:
name: Quality
modelAsString: true
values:
- value: standard
description: Standard quality creates images with standard quality.
name: Standard
- value: hd
description: HD quality creates images with finer details and greater consistency across the image.
name: HD
imagesResponseFormat:
description: The format in which the generated images are returned.
type: string
enum:
- url
- b64_json
default: url
x-ms-enum:
name: ImagesResponseFormat
modelAsString: true
values:
- value: url
description: The URL that provides temporary access to download the generated images.
name: Url
- value: b64_json
description: The generated images are returned as base64 encoded string.
name: Base64Json
imageSize:
description: The size of the generated images.
type: string
enum:
- 1792x1024
- 1024x1792
- 1024x1024
default: 1024x1024
x-ms-enum:
name: Size
modelAsString: true
values:
- value: 1792x1024
description: The desired size of the generated image is 1792x1024 pixels.
name: Size1792x1024
- value: 1024x1792
description: The desired size of the generated image is 1024x1792 pixels.
name: Size1024x1792
- value: 1024x1024
description: The desired size of the generated image is 1024x1024 pixels.
name: Size1024x1024
imageStyle:
description: The style of the generated images.
type: string
enum:
- vivid
- natural
default: vivid
x-ms-enum:
name: Style
modelAsString: true
values:
- value: vivid
description: Vivid creates images that are hyper-realistic and dramatic.
name: Vivid
- value: natural
description: Natural creates images that are more natural and less hyper-realistic.
name: Natural
imageGenerationsRequest:
type: object
properties:
prompt:
description: A text description of the desired image(s). The maximum length is 4000 characters.
type: string
format: string
example: a corgi in a field
minLength: 1
'n':
description: The number of images to generate.
type: integer
minimum: 1
maximum: 1
default: 1
size:
$ref: '#/components/schemas/imageSize'
response_format:
$ref: '#/components/schemas/imagesResponseFormat'
user:
description: A unique identifier representing your end-user, which can help to monitor and detect abuse.
type: string
format: string
example: user123456
quality:
$ref: '#/components/schemas/imageQuality'
style:
$ref: '#/components/schemas/imageStyle'
required:
- prompt
generateImagesResponse:
type: object
properties:
created:
type: integer
format: unixtime
description: The unix timestamp when the operation was created.
example: '1676540381'
data:
type: array
description: The result data of the operation, if successful
items:
$ref: '#/components/schemas/imageResult'
required:
- created
- data
imageResult:
type: object
description: The image url or encoded image if successful, and an error otherwise.
properties:
url:
type: string
description: The image url.
example: https://www.contoso.com
b64_json:
type: string
description: The base64 encoded image
content_filter_results:
$ref: '#/components/schemas/dalleContentFilterResults'
revised_prompt:
type: string
description: The prompt that was used to generate the image, if there was any revision to the prompt.
prompt_filter_results:
$ref: '#/components/schemas/dalleFilterResults'
securitySchemes:
bearer:
type: oauth2
flows:
implicit:
authorizationUrl: https://login.microsoftonline.com/common/oauth2/v2.0/authorize
scopes: {}
x-tokenInfoFunc: api.middleware.auth.bearer_auth
x-scopeValidateFunc: api.middleware.auth.validate_scopes
apiKey:
type: apiKey
name: api-key
in: header