specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2023-12-01-preview/inference.yaml (1,770 lines of code) (raw):
openapi: 3.0.0
info:
title: Azure OpenAI Service API
description: Azure OpenAI APIs for completions and search
version: 2023-12-01-preview
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: 2023-12-01-preview
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: 2023-12-01-preview
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
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
/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: 2023-12-01-preview
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
/deployments/{deployment-id}/extensions/chat/completions:
post:
summary: Using extensions to creates a completion for the chat messages.
operationId: ExtensionsChatCompletions_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: 2023-12-01-preview
description: api version
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/extensionsChatCompletionsRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/extensionsChatCompletionsResponse'
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}/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: 2023-12-01-preview
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).
/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: 2023-12-01-preview
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).
/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: 2023-12-01-preview
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/errorResponse'
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:
code:
type: string
message:
type: string
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.
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
contentFilterIdResult:
type: object
allOf:
- $ref: '#/components/schemas/contentFilterResultBase'
- properties:
id:
type: string
required:
- id
- 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'
custom_blocklists:
items:
$ref: '#/components/schemas/contentFilterIdResult'
type: array
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'
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'
'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: -9223372036854776000
maximum: 9223372036854776000
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.
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'
required:
- content
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'
required:
- id
- object
- created
- model
- choices
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'
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
- $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
extensionsChatCompletionsRequest:
type: object
description: Request for the chat completions using extensions
required:
- messages
allOf:
- $ref: '#/components/schemas/chatCompletionsRequestCommon'
- properties:
messages:
type: array
items:
$ref: '#/components/schemas/message'
dataSources:
type: array
description: The data sources to be used for the Azure OpenAI on your data feature.
items:
$ref: '#/components/schemas/dataSource'
enhancements:
type: object
description: The type of enhancements needed.
properties:
grounding:
type: object
description: Request object to specify if grounding enhancement is needed.
properties:
enabled:
type: boolean
default: false
ocr:
type: object
description: Request object to specify if ocr enhancement is needed.
properties:
enabled:
type: boolean
default: false
example:
dataSources:
- type: AzureCognitiveSearch
parameters:
endpoint: https://mysearchexample.search.windows.net
key: '***(admin key)'
indexName: my-chunk-index
fieldsMapping:
titleField: productName
urlField: productUrl
filepathField: productFilePath
contentFields:
- productDescription
contentFieldsSeparator: |+
topNDocuments: 5
queryType: semantic
semanticConfiguration: defaultConfiguration
inScope: true
roleInformation: roleInformation
messages:
- role: user
content: Where can I find a hiking place in Seattle?
temperature: 0.9
dataSource:
type: object
description: The data source to be used for the Azure OpenAI on your data feature.
properties:
type:
type: string
description: The data source type.
parameters:
type: object
description: The parameters to be used for the data source in runtime.
additionalProperties: true
required:
- type
message:
type: object
description: A chat message.
properties:
index:
type: integer
description: The index of the message in the conversation.
role:
type: string
enum:
- system
- user
- assistant
- tool
description: The role of the author of this message.
recipient:
type: string
example: Contoso.productsUsingGET
description: The recipient of the message in the format of <namespace>.<operation>. Present if and only if the recipient is tool.
content:
type: string
description: The contents of the message
end_turn:
type: boolean
description: Whether the message ends the turn.
context:
type: object
description: The conversation context
nullable: true
properties:
messages:
type: array
description: Messages exchanged between model and extensions prior to final message from model
minItems: 1
items:
$ref: '#/components/schemas/message'
nullable: true
required:
- role
- content
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
extensionsChatCompletionChoice:
type: object
allOf:
- $ref: '#/components/schemas/chatCompletionChoiceCommon'
- properties:
message:
$ref: '#/components/schemas/message'
enhancements:
description: The enhancement results returned by the service.
$ref: '#/components/schemas/enhancement'
extensionsChatCompletionsResponse:
type: object
description: The response of the extensions chat completions.
allOf:
- $ref: '#/components/schemas/chatCompletionsResponseCommon'
- properties:
choices:
type: array
items:
$ref: '#/components/schemas/extensionsChatCompletionChoice'
example:
id: '1'
object: extensions.chat.completion
created: 1679201802
model: gpt-3.5-turbo-0301
choices:
- index: 0
finish_reason: stop
message:
role: assistant
content: Seattle is a great place for hiking! Here are some of the best hiking places in Seattle according to Contoso Traveler [doc1] and West Coast Traveler, Snow Lake, Mount Si, and Mount Tenerife [doc2]. I hope this helps! Let me know if you need more information.
end_turn: true
context:
messages:
- role: tool
content: '{"citations":[{"filepath":"ContosoTraveler.pdf","content":"This is the content of the citation 1"},{"filepath":"WestCoastTraveler.html","content":"This is the content of the citation 2"},{"content":"This is the content of the citation 3 without filepath"}],"intent":"hiking place in seattle"}'
end_turn: false
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
style:
$ref: '#/components/schemas/imageStyle'
quality:
$ref: '#/components/schemas/imageQuality'
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'
error:
$ref: '#/components/schemas/error'
required:
- created
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
revised_prompt:
type: string
description: The prompt that was used to generate the image, if there was any revision to the prompt.
enhancement:
type: object
properties:
grounding:
type: object
description: The grounding enhancement that returns the bounding box of the objects detected in the image.
properties:
lines:
type: array
items:
$ref: '#/components/schemas/line'
required:
- lines
line:
type: object
description: A content line object consisting of an adjacent sequence of content elements, such as words and selection marks.
properties:
text:
type: string
spans:
type: array
description: An array of spans that represent detected objects and its bounding box information.
items:
$ref: '#/components/schemas/span'
required:
- text
- spans
span:
type: object
description: A span object that represents a detected object and its bounding box information.
properties:
text:
type: string
description: The text content of the span that represents the detected object.
offset:
type: integer
description: The character offset within the text where the span begins. This offset is defined as the position of the first character of the span, counting from the start of the text as Unicode codepoints.
length:
type: integer
description: The length of the span in characters, measured in Unicode codepoints.
polygon:
type: array
description: An array of objects representing points in the polygon that encloses the detected object.
items:
type: object
properties:
x:
type: number
description: The x-coordinate of the point.
'y':
type: number
description: The y-coordinate of the point.
required:
- text
- offset
- length
- polygon
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