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" &#58; -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