openapi: 3.0.0 info: title: Azure OpenAI Service API description: Azure OpenAI APIs for completions and search version: '2024-06-01' servers: - url: https://{endpoint}/openai variables: endpoint: default: your-resource-name.openai.azure.com security: - bearer: - api.read - apiKey: [] paths: /deployments/{deployment-id}/completions: post: summary: Creates a completion for the provided prompt, parameters and chosen model. operationId: Completions_Create parameters: - in: path name: deployment-id required: true schema: type: string example: davinci description: Deployment id of the model which was deployed. - in: query name: api-version required: true schema: type: string example: 2024-06-01 description: api version requestBody: required: true content: application/json: schema: type: object properties: prompt: description: |- The prompt(s) to generate completions for, encoded as a string or array of strings. Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document. Maximum allowed size of string list is 2048. oneOf: - type: string default: '' example: This is a test. nullable: true - type: array items: type: string default: '' example: This is a test. nullable: false description: Array size minimum of 1 and maximum of 2048 max_tokens: description: The token count of your prompt plus max_tokens cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096). Has minimum of 0. type: integer default: 16 example: 16 nullable: true temperature: description: |- What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer. We generally recommend altering this or top_p but not both. type: number default: 1 example: 1 nullable: true top_p: description: |- An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both. type: number default: 1 example: 1 nullable: true logit_bias: description: Defaults to null. Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this tokenizer tool (which works for both GPT-2 and GPT-3) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. As an example, you can pass {"50256" : -100} to prevent the <|endoftext|> token from being generated. type: object nullable: false user: description: A unique identifier representing your end-user, which can help monitoring and detecting abuse type: string nullable: false 'n': description: |- How many completions to generate for each prompt. Minimum of 1 and maximum of 128 allowed. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop. type: integer default: 1 example: 1 nullable: true stream: description: 'Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.' type: boolean nullable: true default: false logprobs: description: |- Include the log probabilities on the logprobs most likely tokens, as well the chosen tokens. For example, if logprobs is 5, the API will return a list of the 5 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response. Minimum of 0 and maximum of 5 allowed. type: integer default: null nullable: true suffix: type: string nullable: true description: The suffix that comes after a completion of inserted text. echo: description: Echo back the prompt in addition to the completion type: boolean default: false nullable: true stop: description: Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence. oneOf: - type: string default: <|endoftext|> example: |+ nullable: true - type: array items: type: string example: |+ nullable: false description: Array minimum size of 1 and maximum of 4 completion_config: type: string nullable: true presence_penalty: description: Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. type: number default: 0 frequency_penalty: description: Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. type: number default: 0 best_of: description: |- Generates best_of completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed. When used with n, best_of controls the number of candidate completions and n specifies how many to return - best_of must be greater than n. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop. Has maximum value of 128. type: integer example: prompt: |- Negate the following sentence.The price for bubblegum increased on thursday. Negated Sentence: max_tokens: 50 responses: '200': description: OK content: application/json: schema: type: object properties: id: type: string object: type: string created: type: integer model: type: string prompt_filter_results: $ref: '#/components/schemas/promptFilterResults' choices: type: array items: type: object properties: text: type: string index: type: integer logprobs: type: object properties: tokens: type: array items: type: string token_logprobs: type: array items: type: number top_logprobs: type: array items: type: object additionalProperties: type: number text_offset: type: array items: type: integer nullable: true finish_reason: type: string content_filter_results: $ref: '#/components/schemas/contentFilterChoiceResults' usage: type: object properties: completion_tokens: type: number format: int32 prompt_tokens: type: number format: int32 total_tokens: type: number format: int32 required: - prompt_tokens - total_tokens - completion_tokens required: - id - object - created - model - choices example: model: davinci object: text_completion id: cmpl-4509KAos68kxOqpE2uYGw81j6m7uo created: 1637097562 choices: - index: 0 text: The price for bubblegum decreased on thursday. logprobs: null finish_reason: stop headers: apim-request-id: description: Request ID for troubleshooting purposes schema: type: string default: description: Service unavailable content: application/json: schema: $ref: '#/components/schemas/errorResponse' headers: apim-request-id: description: Request ID for troubleshooting purposes schema: type: string /deployments/{deployment-id}/embeddings: post: summary: Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. operationId: embeddings_create parameters: - in: path name: deployment-id required: true schema: type: string example: ada-search-index-v1 description: The deployment id of the model which was deployed. - in: query name: api-version required: true schema: type: string example: '2024-06-01' description: api version requestBody: required: true content: application/json: schema: type: object additionalProperties: true properties: input: description: |- Input text to get embeddings for, encoded as a string. To get embeddings for multiple inputs in a single request, pass an array of strings. Each input must not exceed 2048 tokens in length. Unless you are embedding code, we suggest replacing newlines (\n) in your input with a single space, as we have observed inferior results when newlines are present. oneOf: - type: string default: '' example: This is a test. nullable: true - type: array minItems: 1 maxItems: 2048 items: type: string minLength: 1 example: This is a test. nullable: false user: description: A unique identifier representing your end-user, which can help monitoring and detecting abuse. type: string nullable: false input_type: description: input type of embedding search to use type: string example: query encoding_format: description: The format to return the embeddings in. Can be either `float` or `base64`. Defaults to `float`. type: string example: base64 nullable: true dimensions: description: The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models. type: integer example: 1 nullable: true required: - input responses: '200': description: OK content: application/json: schema: type: object properties: object: type: string model: type: string data: type: array items: type: object properties: index: type: integer object: type: string embedding: type: array items: type: number required: - index - object - embedding usage: type: object properties: prompt_tokens: type: integer total_tokens: type: integer required: - prompt_tokens - total_tokens required: - object - model - data - usage x-ms-examples: Create a embeddings.: $ref: ./examples/embeddings.yaml /deployments/{deployment-id}/chat/completions: post: summary: Creates a completion for the chat message operationId: ChatCompletions_Create parameters: - in: path name: deployment-id required: true schema: type: string description: Deployment id of the model which was deployed. - in: query name: api-version required: true schema: type: string example: '2024-06-01' description: api version requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/createChatCompletionRequest' responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/createChatCompletionResponse' headers: apim-request-id: description: Request ID for troubleshooting purposes schema: type: string default: description: Service unavailable content: application/json: schema: $ref: '#/components/schemas/errorResponse' headers: apim-request-id: description: Request ID for troubleshooting purposes schema: type: string x-ms-examples: Create a chat completion.: $ref: ./examples/chat_completions.yaml Creates a completion based on Azure Search data and system-assigned managed identity.: $ref: ./examples/chat_completions_azure_search_minimum.yaml Creates a completion based on Azure Search vector data, previous assistant message and user-assigned managed identity.: $ref: ./examples/chat_completions_azure_search_advanced.yaml Creates a completion for the provided Azure Cosmos DB.: $ref: ./examples/chat_completions_cosmos_db.yaml /deployments/{deployment-id}/audio/transcriptions: post: summary: Transcribes audio into the input language. operationId: Transcriptions_Create parameters: - in: path name: deployment-id required: true schema: type: string example: whisper description: Deployment id of the whisper model. - in: query name: api-version required: true schema: type: string example: '2024-06-01' description: api version requestBody: required: true content: multipart/form-data: schema: $ref: '#/components/schemas/createTranscriptionRequest' responses: '200': description: OK content: application/json: schema: oneOf: - $ref: '#/components/schemas/audioResponse' - $ref: '#/components/schemas/audioVerboseResponse' text/plain: schema: type: string description: Transcribed text in the output format (when response_format was one of text, vtt or srt). x-ms-examples: Create an audio transcription with json response format.: $ref: ./examples/audio_transcription_object.yaml Create an audio transcription with text response format.: $ref: ./examples/audio_transcription_text.yaml /deployments/{deployment-id}/audio/translations: post: summary: Transcribes and translates input audio into English text. operationId: Translations_Create parameters: - in: path name: deployment-id required: true schema: type: string example: whisper description: Deployment id of the whisper model which was deployed. - in: query name: api-version required: true schema: type: string example: '2024-06-01' description: api version requestBody: required: true content: multipart/form-data: schema: $ref: '#/components/schemas/createTranslationRequest' responses: '200': description: OK content: application/json: schema: oneOf: - $ref: '#/components/schemas/audioResponse' - $ref: '#/components/schemas/audioVerboseResponse' text/plain: schema: type: string description: Transcribed text in the output format (when response_format was one of text, vtt or srt). x-ms-examples: Create an audio translation with json response format.: $ref: ./examples/audio_translation_object.yaml Create an audio translation with text response format.: $ref: ./examples/audio_translation_text.yaml /deployments/{deployment-id}/images/generations: post: summary: Generates a batch of images from a text caption on a given DALLE model deployment operationId: ImageGenerations_Create requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/imageGenerationsRequest' parameters: - in: path name: deployment-id required: true schema: type: string example: dalle-deployment description: Deployment id of the dalle model which was deployed. - in: query name: api-version required: true schema: type: string example: '2024-06-01' description: api version responses: '200': description: Ok content: application/json: schema: $ref: '#/components/schemas/generateImagesResponse' default: description: An error occurred. content: application/json: schema: $ref: '#/components/schemas/dalleErrorResponse' x-ms-examples: Create an image.: $ref: ./examples/image_generation.yaml components: schemas: errorResponse: type: object properties: error: $ref: '#/components/schemas/error' errorBase: type: object properties: code: type: string message: type: string error: type: object allOf: - $ref: '#/components/schemas/errorBase' properties: param: type: string type: type: string inner_error: $ref: '#/components/schemas/innerError' innerError: description: Inner error with additional details. type: object properties: code: $ref: '#/components/schemas/innerErrorCode' content_filter_results: $ref: '#/components/schemas/contentFilterPromptResults' innerErrorCode: description: Error codes for the inner error object. enum: - ResponsibleAIPolicyViolation type: string x-ms-enum: name: InnerErrorCode modelAsString: true values: - value: ResponsibleAIPolicyViolation description: The prompt violated one of more content filter rules. dalleErrorResponse: type: object properties: error: $ref: '#/components/schemas/dalleError' dalleError: type: object allOf: - $ref: '#/components/schemas/errorBase' properties: param: type: string type: type: string inner_error: $ref: '#/components/schemas/dalleInnerError' dalleInnerError: description: Inner error with additional details. type: object properties: code: $ref: '#/components/schemas/innerErrorCode' content_filter_results: $ref: '#/components/schemas/dalleFilterResults' revised_prompt: type: string description: The prompt that was used to generate the image, if there was any revision to the prompt. contentFilterResultBase: type: object properties: filtered: type: boolean required: - filtered contentFilterSeverityResult: type: object allOf: - $ref: '#/components/schemas/contentFilterResultBase' - properties: severity: type: string enum: - safe - low - medium - high x-ms-enum: name: ContentFilterSeverity modelAsString: true values: - value: safe description: General content or related content in generic or non-harmful contexts. - value: low description: Harmful content at a low intensity and risk level. - value: medium description: Harmful content at a medium intensity and risk level. - value: high description: Harmful content at a high intensity and risk level. required: - severity - filtered contentFilterDetectedResult: type: object allOf: - $ref: '#/components/schemas/contentFilterResultBase' - properties: detected: type: boolean required: - detected - filtered contentFilterDetectedWithCitationResult: type: object allOf: - $ref: '#/components/schemas/contentFilterDetectedResult' - properties: citation: type: object properties: URL: type: string license: type: string required: - detected - filtered contentFilterResultsBase: type: object description: Information about the content filtering results. properties: sexual: $ref: '#/components/schemas/contentFilterSeverityResult' violence: $ref: '#/components/schemas/contentFilterSeverityResult' hate: $ref: '#/components/schemas/contentFilterSeverityResult' self_harm: $ref: '#/components/schemas/contentFilterSeverityResult' profanity: $ref: '#/components/schemas/contentFilterDetectedResult' error: $ref: '#/components/schemas/errorBase' contentFilterPromptResults: type: object description: Information about the content filtering category (hate, sexual, violence, self_harm), if it has been detected, as well as the severity level (very_low, low, medium, high-scale that determines the intensity and risk level of harmful content) and if it has been filtered or not. Information about jailbreak content and profanity, if it has been detected, and if it has been filtered or not. And information about customer block list, if it has been filtered and its id. allOf: - $ref: '#/components/schemas/contentFilterResultsBase' - properties: jailbreak: $ref: '#/components/schemas/contentFilterDetectedResult' contentFilterChoiceResults: type: object description: Information about the content filtering category (hate, sexual, violence, self_harm), if it has been detected, as well as the severity level (very_low, low, medium, high-scale that determines the intensity and risk level of harmful content) and if it has been filtered or not. Information about third party text and profanity, if it has been detected, and if it has been filtered or not. And information about customer block list, if it has been filtered and its id. allOf: - $ref: '#/components/schemas/contentFilterResultsBase' - properties: protected_material_text: $ref: '#/components/schemas/contentFilterDetectedResult' - properties: protected_material_code: $ref: '#/components/schemas/contentFilterDetectedWithCitationResult' promptFilterResult: type: object description: Content filtering results for a single prompt in the request. properties: prompt_index: type: integer content_filter_results: $ref: '#/components/schemas/contentFilterPromptResults' promptFilterResults: type: array description: Content filtering results for zero or more prompts in the request. In a streaming request, results for different prompts may arrive at different times or in different orders. items: $ref: '#/components/schemas/promptFilterResult' dalleContentFilterResults: type: object description: Information about the content filtering results. properties: sexual: $ref: '#/components/schemas/contentFilterSeverityResult' violence: $ref: '#/components/schemas/contentFilterSeverityResult' hate: $ref: '#/components/schemas/contentFilterSeverityResult' self_harm: $ref: '#/components/schemas/contentFilterSeverityResult' dalleFilterResults: type: object description: Information about the content filtering category (hate, sexual, violence, self_harm), if it has been detected, as well as the severity level (very_low, low, medium, high-scale that determines the intensity and risk level of harmful content) and if it has been filtered or not. Information about jailbreak content and profanity, if it has been detected, and if it has been filtered or not. And information about customer block list, if it has been filtered and its id. allOf: - $ref: '#/components/schemas/dalleContentFilterResults' - properties: profanity: $ref: '#/components/schemas/contentFilterDetectedResult' jailbreak: $ref: '#/components/schemas/contentFilterDetectedResult' chatCompletionsRequestCommon: type: object properties: temperature: description: |- What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or `top_p` but not both. type: number minimum: 0 maximum: 2 default: 1 example: 1 nullable: true top_p: description: |- An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both. type: number minimum: 0 maximum: 1 default: 1 example: 1 nullable: true stream: description: 'If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a `data: [DONE]` message.' type: boolean nullable: true default: false stop: description: Up to 4 sequences where the API will stop generating further tokens. oneOf: - type: string nullable: true - type: array items: type: string nullable: false minItems: 1 maxItems: 4 description: Array minimum size of 1 and maximum of 4 default: null max_tokens: description: The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens). type: integer default: 4096 presence_penalty: description: Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. type: number default: 0 minimum: -2 maximum: 2 frequency_penalty: description: Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. type: number default: 0 minimum: -2 maximum: 2 logit_bias: description: Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. type: object nullable: true user: description: A unique identifier representing your end-user, which can help Azure OpenAI to monitor and detect abuse. type: string example: user-1234 nullable: false createChatCompletionRequest: type: object allOf: - $ref: '#/components/schemas/chatCompletionsRequestCommon' - properties: messages: description: A list of messages comprising the conversation so far. [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb). type: array minItems: 1 items: $ref: '#/components/schemas/chatCompletionRequestMessage' data_sources: type: array description: |2- The configuration entries for Azure OpenAI chat extensions that use them. This additional specification is only compatible with Azure OpenAI. items: $ref: '#/components/schemas/azureChatExtensionConfiguration' 'n': type: integer minimum: 1 maximum: 128 default: 1 example: 1 nullable: true description: How many chat completion choices to generate for each input message. seed: type: integer minimum: -9223372036854775808 maximum: 9223372036854775807 default: 0 example: 1 nullable: true description: If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result.Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend. logprobs: description: Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`. This option is currently not available on the `gpt-4-vision-preview` model. type: boolean default: false nullable: true top_logprobs: description: An integer between 0 and 5 specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to `true` if this parameter is used. type: integer minimum: 0 maximum: 5 nullable: true response_format: type: object description: An object specifying the format that the model must output. Used to enable JSON mode. properties: type: $ref: '#/components/schemas/chatCompletionResponseFormat' tools: description: A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. type: array minItems: 1 items: $ref: '#/components/schemas/chatCompletionTool' tool_choice: $ref: '#/components/schemas/chatCompletionToolChoiceOption' functions: description: Deprecated in favor of `tools`. A list of functions the model may generate JSON inputs for. type: array minItems: 1 maxItems: 128 items: $ref: '#/components/schemas/chatCompletionFunction' function_call: description: Deprecated in favor of `tool_choice`. Controls how the model responds to function calls. "none" means the model does not call a function, and responds to the end-user. "auto" means the model can pick between an end-user or calling a function. Specifying a particular function via `{"name":\ "my_function"}` forces the model to call that function. "none" is the default when no functions are present. "auto" is the default if functions are present. oneOf: - type: string enum: - none - auto description: '`none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function.' - type: object description: 'Specifying a particular function via `{"name": "my_function"}` forces the model to call that function.' properties: name: type: string description: The name of the function to call. required: - name required: - messages chatCompletionResponseFormat: type: string enum: - text - json_object default: text example: json_object nullable: true description: Setting to `json_object` enables JSON mode. This guarantees that the message the model generates is valid JSON. x-ms-enum: name: ChatCompletionResponseFormat modelAsString: true values: - value: text description: Response format is a plain text string. - value: json_object description: Response format is a JSON object. chatCompletionFunction: type: object properties: name: type: string description: The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64. description: type: string description: The description of what the function does. parameters: $ref: '#/components/schemas/chatCompletionFunctionParameters' required: - name chatCompletionFunctionParameters: type: object description: The parameters the functions accepts, described as a JSON Schema object. See the [guide](/docs/guides/gpt/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format. additionalProperties: true chatCompletionRequestMessage: type: object properties: role: $ref: '#/components/schemas/chatCompletionRequestMessageRole' discriminator: propertyName: role mapping: system: '#/components/schemas/chatCompletionRequestMessageSystem' user: '#/components/schemas/chatCompletionRequestMessageUser' assistant: '#/components/schemas/chatCompletionRequestMessageAssistant' tool: '#/components/schemas/chatCompletionRequestMessageTool' function: '#/components/schemas/chatCompletionRequestMessageFunction' required: - role chatCompletionRequestMessageRole: type: string enum: - system - user - assistant - tool - function description: The role of the messages author. x-ms-enum: name: ChatCompletionRequestMessageRole modelAsString: true values: - value: system description: The message author role is system. - value: user description: The message author role is user. - value: assistant description: The message author role is assistant. - value: tool description: The message author role is tool. - value: function description: Deprecated. The message author role is function. chatCompletionRequestMessageSystem: allOf: - $ref: '#/components/schemas/chatCompletionRequestMessage' - type: object properties: content: type: string description: The contents of the message. nullable: true required: - content chatCompletionRequestMessageUser: allOf: - $ref: '#/components/schemas/chatCompletionRequestMessage' - type: object properties: content: oneOf: - type: string description: The contents of the message. - type: array description: An array of content parts with a defined type, each can be of type `text` or `image_url` when passing in images. You can pass multiple images by adding multiple `image_url` content parts. Image input is only supported when using the `gpt-4-visual-preview` model. minimum: 1 items: $ref: '#/components/schemas/chatCompletionRequestMessageContentPart' nullable: true required: - content chatCompletionRequestMessageContentPart: type: object properties: type: $ref: '#/components/schemas/chatCompletionRequestMessageContentPartType' discriminator: propertyName: type mapping: text: '#/components/schemas/chatCompletionRequestMessageContentPartText' image_url: '#/components/schemas/chatCompletionRequestMessageContentPartImage' required: - type chatCompletionRequestMessageContentPartType: type: string enum: - text - image_url description: The type of the content part. x-ms-enum: name: ChatCompletionRequestMessageContentPartType modelAsString: true values: - value: text description: The content part type is text. - value: image_url description: The content part type is image_url. chatCompletionRequestMessageContentPartText: allOf: - $ref: '#/components/schemas/chatCompletionRequestMessageContentPart' - type: object properties: text: type: string description: The text content. required: - text chatCompletionRequestMessageContentPartImage: allOf: - $ref: '#/components/schemas/chatCompletionRequestMessageContentPart' - type: object properties: url: type: string description: Either a URL of the image or the base64 encoded image data. format: uri detail: $ref: '#/components/schemas/imageDetailLevel' required: - url imageDetailLevel: type: string description: Specifies the detail level of the image. enum: - auto - low - high default: auto x-ms-enum: name: ImageDetailLevel modelAsString: true values: - value: auto description: The image detail level is auto. - value: low description: The image detail level is low. - value: high description: The image detail level is high. chatCompletionRequestMessageAssistant: allOf: - $ref: '#/components/schemas/chatCompletionRequestMessage' - type: object properties: content: type: string description: The contents of the message. nullable: true tool_calls: type: array description: The tool calls generated by the model, such as function calls. items: $ref: '#/components/schemas/chatCompletionMessageToolCall' context: $ref: '#/components/schemas/azureChatExtensionsMessageContext' required: - content azureChatExtensionConfiguration: required: - type type: object properties: type: $ref: '#/components/schemas/azureChatExtensionType' description: |2- A representation of configuration data for a single Azure OpenAI chat extension. This will be used by a chat completions request that should use Azure OpenAI chat extensions to augment the response behavior. The use of this configuration is compatible only with Azure OpenAI. discriminator: propertyName: type mapping: azure_search: '#/components/schemas/azureSearchChatExtensionConfiguration' azure_cosmos_db: '#/components/schemas/azureCosmosDBChatExtensionConfiguration' azureChatExtensionType: type: string description: |2- A representation of configuration data for a single Azure OpenAI chat extension. This will be used by a chat completions request that should use Azure OpenAI chat extensions to augment the response behavior. The use of this configuration is compatible only with Azure OpenAI. enum: - azure_search - azure_cosmos_db x-ms-enum: name: AzureChatExtensionType modelAsString: true values: - name: azureSearch value: azure_search description: Represents the use of Azure Search as an Azure OpenAI chat extension. - name: azureCosmosDB value: azure_cosmos_db description: Represents the use of Azure Cosmos DB as an Azure OpenAI chat extension. azureSearchChatExtensionConfiguration: required: - parameters description: |- A specific representation of configurable options for Azure Search when using it as an Azure OpenAI chat extension. allOf: - $ref: '#/components/schemas/azureChatExtensionConfiguration' - properties: parameters: $ref: '#/components/schemas/azureSearchChatExtensionParameters' x-ms-discriminator-value: azure_search azureSearchChatExtensionParameters: required: - authentication - endpoint - index_name type: object properties: authentication: oneOf: - $ref: '#/components/schemas/onYourDataApiKeyAuthenticationOptions' - $ref: '#/components/schemas/onYourDataSystemAssignedManagedIdentityAuthenticationOptions' - $ref: '#/components/schemas/onYourDataUserAssignedManagedIdentityAuthenticationOptions' top_n_documents: type: integer description: The configured top number of documents to feature for the configured query. format: int32 in_scope: type: boolean description: Whether queries should be restricted to use of indexed data. strictness: maximum: 5 minimum: 1 type: integer description: The configured strictness of the search relevance filtering. The higher of strictness, the higher of the precision but lower recall of the answer. format: int32 role_information: type: string description: Give the model instructions about how it should behave and any context it should reference when generating a response. You can describe the assistant's personality and tell it how to format responses. There's a 100 token limit for it, and it counts against the overall token limit. endpoint: type: string description: The absolute endpoint path for the Azure Search resource to use. format: uri index_name: type: string description: The name of the index to use as available in the referenced Azure Search resource. fields_mapping: $ref: '#/components/schemas/azureSearchIndexFieldMappingOptions' query_type: $ref: '#/components/schemas/azureSearchQueryType' semantic_configuration: type: string description: The additional semantic configuration for the query. filter: type: string description: Search filter. embedding_dependency: oneOf: - $ref: '#/components/schemas/onYourDataEndpointVectorizationSource' - $ref: '#/components/schemas/onYourDataDeploymentNameVectorizationSource' description: Parameters for Azure Search when used as an Azure OpenAI chat extension. azureSearchIndexFieldMappingOptions: type: object properties: title_field: type: string description: The name of the index field to use as a title. url_field: type: string description: The name of the index field to use as a URL. filepath_field: type: string description: The name of the index field to use as a filepath. content_fields: type: array description: The names of index fields that should be treated as content. items: type: string content_fields_separator: type: string description: The separator pattern that content fields should use. vector_fields: type: array description: The names of fields that represent vector data. items: type: string description: Optional settings to control how fields are processed when using a configured Azure Search resource. azureSearchQueryType: type: string description: The type of Azure Search retrieval query that should be executed when using it as an Azure OpenAI chat extension. enum: - simple - semantic - vector - vector_simple_hybrid - vector_semantic_hybrid x-ms-enum: name: azureSearchQueryType modelAsString: true values: - name: simple value: simple description: Represents the default, simple query parser. - name: semantic value: semantic description: Represents the semantic query parser for advanced semantic modeling. - name: vector value: vector description: Represents vector search over computed data. - name: vectorSimpleHybrid value: vector_simple_hybrid description: Represents a combination of the simple query strategy with vector data. - name: vectorSemanticHybrid value: vector_semantic_hybrid description: Represents a combination of semantic search and vector data querying. azureCosmosDBChatExtensionConfiguration: required: - parameters description: |- A specific representation of configurable options for Azure Cosmos DB when using it as an Azure OpenAI chat extension. allOf: - $ref: '#/components/schemas/azureChatExtensionConfiguration' - properties: parameters: $ref: '#/components/schemas/azureCosmosDBChatExtensionParameters' x-ms-discriminator-value: azure_cosmos_db azureCosmosDBChatExtensionParameters: required: - authentication - container_name - database_name - embedding_dependency - fields_mapping - index_name type: object properties: authentication: $ref: '#/components/schemas/onYourDataConnectionStringAuthenticationOptions' top_n_documents: type: integer description: The configured top number of documents to feature for the configured query. format: int32 in_scope: type: boolean description: Whether queries should be restricted to use of indexed data. strictness: maximum: 5 minimum: 1 type: integer description: The configured strictness of the search relevance filtering. The higher of strictness, the higher of the precision but lower recall of the answer. format: int32 role_information: type: string description: Give the model instructions about how it should behave and any context it should reference when generating a response. You can describe the assistant's personality and tell it how to format responses. There's a 100 token limit for it, and it counts against the overall token limit. database_name: type: string description: The MongoDB vCore database name to use with Azure Cosmos DB. container_name: type: string description: The name of the Azure Cosmos DB resource container. index_name: type: string description: The MongoDB vCore index name to use with Azure Cosmos DB. fields_mapping: $ref: '#/components/schemas/azureCosmosDBFieldMappingOptions' embedding_dependency: oneOf: - $ref: '#/components/schemas/onYourDataEndpointVectorizationSource' - $ref: '#/components/schemas/onYourDataDeploymentNameVectorizationSource' description: |- Parameters to use when configuring Azure OpenAI On Your Data chat extensions when using Azure Cosmos DB for MongoDB vCore. azureCosmosDBFieldMappingOptions: required: - content_fields - vector_fields type: object properties: title_field: type: string description: The name of the index field to use as a title. url_field: type: string description: The name of the index field to use as a URL. filepath_field: type: string description: The name of the index field to use as a filepath. content_fields: type: array description: The names of index fields that should be treated as content. items: type: string content_fields_separator: type: string description: The separator pattern that content fields should use. vector_fields: type: array description: The names of fields that represent vector data. items: type: string description: Optional settings to control how fields are processed when using a configured Azure Cosmos DB resource. onYourDataAuthenticationOptions: required: - type type: object properties: type: $ref: '#/components/schemas/onYourDataAuthenticationType' description: The authentication options for Azure OpenAI On Your Data. discriminator: propertyName: type mapping: api_key: '#/components/schemas/onYourDataApiKeyAuthenticationOptions' connection_string: '#/components/schemas/onYourDataConnectionStringAuthenticationOptions' system_assigned_managed_identity: '#/components/schemas/onYourDataSystemAssignedManagedIdentityAuthenticationOptions' user_assigned_managed_identity: '#/components/schemas/onYourDataUserAssignedManagedIdentityAuthenticationOptions' onYourDataAuthenticationType: type: string description: The authentication types supported with Azure OpenAI On Your Data. enum: - api_key - connection_string - system_assigned_managed_identity - user_assigned_managed_identity x-ms-enum: name: OnYourDataAuthenticationType modelAsString: true values: - name: apiKey value: api_key description: Authentication via API key. - name: connectionString value: connection_string description: Authentication via connection string. - name: systemAssignedManagedIdentity value: system_assigned_managed_identity description: Authentication via system-assigned managed identity. - name: userAssignedManagedIdentity value: user_assigned_managed_identity description: Authentication via user-assigned managed identity. onYourDataApiKeyAuthenticationOptions: required: - key description: The authentication options for Azure OpenAI On Your Data when using an API key. allOf: - $ref: '#/components/schemas/onYourDataAuthenticationOptions' - properties: key: type: string description: The API key to use for authentication. x-ms-discriminator-value: api_key onYourDataConnectionStringAuthenticationOptions: required: - connection_string description: The authentication options for Azure OpenAI On Your Data when using a connection string. allOf: - $ref: '#/components/schemas/onYourDataAuthenticationOptions' - properties: connection_string: type: string description: The connection string to use for authentication. x-ms-discriminator-value: connection_string onYourDataSystemAssignedManagedIdentityAuthenticationOptions: description: The authentication options for Azure OpenAI On Your Data when using a system-assigned managed identity. allOf: - $ref: '#/components/schemas/onYourDataAuthenticationOptions' x-ms-discriminator-value: system_assigned_managed_identity onYourDataUserAssignedManagedIdentityAuthenticationOptions: required: - managed_identity_resource_id description: The authentication options for Azure OpenAI On Your Data when using a user-assigned managed identity. allOf: - $ref: '#/components/schemas/onYourDataAuthenticationOptions' - properties: managed_identity_resource_id: type: string description: The resource ID of the user-assigned managed identity to use for authentication. x-ms-discriminator-value: user_assigned_managed_identity onYourDataVectorizationSource: required: - type type: object properties: type: $ref: '#/components/schemas/onYourDataVectorizationSourceType' description: An abstract representation of a vectorization source for Azure OpenAI On Your Data with vector search. discriminator: propertyName: type mapping: endpoint: '#/components/schemas/onYourDataEndpointVectorizationSource' deployment_name: '#/components/schemas/onYourDataDeploymentNameVectorizationSource' onYourDataVectorizationSourceType: type: string description: |- Represents the available sources Azure OpenAI On Your Data can use to configure vectorization of data for use with vector search. enum: - endpoint - deployment_name x-ms-enum: name: OnYourDataVectorizationSourceType modelAsString: true values: - name: endpoint value: endpoint description: Represents vectorization performed by public service calls to an Azure OpenAI embedding model. - name: deploymentName value: deployment_name description: |- Represents an Ada model deployment name to use. This model deployment must be in the same Azure OpenAI resource, but On Your Data will use this model deployment via an internal call rather than a public one, which enables vector search even in private networks. onYourDataDeploymentNameVectorizationSource: required: - deployment_name description: |- The details of a a vectorization source, used by Azure OpenAI On Your Data when applying vector search, that is based on an internal embeddings model deployment name in the same Azure OpenAI resource. allOf: - $ref: '#/components/schemas/onYourDataVectorizationSource' - properties: deployment_name: type: string description: Specifies the name of the model deployment to use for vectorization. This model deployment must be in the same Azure OpenAI resource, but On Your Data will use this model deployment via an internal call rather than a public one, which enables vector search even in private networks. x-ms-discriminator-value: deployment_name onYourDataEndpointVectorizationSource: required: - authentication - endpoint description: |- The details of a a vectorization source, used by Azure OpenAI On Your Data when applying vector search, that is based on a public Azure OpenAI endpoint call for embeddings. allOf: - $ref: '#/components/schemas/onYourDataVectorizationSource' - properties: authentication: $ref: '#/components/schemas/onYourDataApiKeyAuthenticationOptions' endpoint: type: string description: Specifies the endpoint to use for vectorization. This endpoint must be in the same Azure OpenAI resource, but On Your Data will use this endpoint via an internal call rather than a public one, which enables vector search even in private networks. format: uri x-ms-discriminator-value: endpoint azureChatExtensionsMessageContext: type: object properties: citations: type: array description: The data source retrieval result, used to generate the assistant message in the response. items: $ref: '#/components/schemas/citation' x-ms-identifiers: [] intent: type: string description: The detected intent from the chat history, used to pass to the next turn to carry over the context. description: |2- A representation of the additional context information available when Azure OpenAI chat extensions are involved in the generation of a corresponding chat completions response. This context information is only populated when using an Azure OpenAI request configured to use a matching extension. citation: required: - content type: object properties: content: type: string description: The content of the citation. title: type: string description: The title of the citation. url: type: string description: The URL of the citation. filepath: type: string description: The file path of the citation. chunk_id: type: string description: The chunk ID of the citation. description: citation information for a chat completions response message. chatCompletionMessageToolCall: type: object properties: id: type: string description: The ID of the tool call. type: $ref: '#/components/schemas/toolCallType' function: type: object description: The function that the model called. properties: name: type: string description: The name of the function to call. arguments: type: string description: The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function. required: - name - arguments required: - id - type - function toolCallType: type: string enum: - function description: The type of the tool call, in this case `function`. x-ms-enum: name: ToolCallType modelAsString: true values: - value: function description: The tool call type is function. chatCompletionRequestMessageTool: allOf: - $ref: '#/components/schemas/chatCompletionRequestMessage' - type: object nullable: true properties: tool_call_id: type: string description: Tool call that this message is responding to. content: type: string description: The contents of the message. nullable: true required: - tool_call_id - content chatCompletionRequestMessageFunction: allOf: - $ref: '#/components/schemas/chatCompletionRequestMessage' - type: object description: Deprecated. Message that represents a function. nullable: true properties: role: type: string enum: - function description: The role of the messages author, in this case `function`. name: type: string description: The contents of the message. content: type: string description: The contents of the message. nullable: true required: - function_call_id - content createChatCompletionResponse: type: object allOf: - $ref: '#/components/schemas/chatCompletionsResponseCommon' - properties: prompt_filter_results: $ref: '#/components/schemas/promptFilterResults' choices: type: array items: type: object allOf: - $ref: '#/components/schemas/chatCompletionChoiceCommon' - properties: message: $ref: '#/components/schemas/chatCompletionResponseMessage' content_filter_results: $ref: '#/components/schemas/contentFilterChoiceResults' logprobs: $ref: '#/components/schemas/chatCompletionChoiceLogProbs' required: - id - object - created - model - choices chatCompletionChoiceLogProbs: description: Log probability information for the choice. type: object nullable: true properties: content: description: A list of message content tokens with log probability information. type: array items: $ref: '#/components/schemas/chatCompletionTokenLogprob' nullable: true required: - content chatCompletionTokenLogprob: type: object properties: token: description: The token. type: string logprob: description: The log probability of this token. type: number bytes: description: A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token. type: array items: type: integer nullable: true top_logprobs: description: List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested `top_logprobs` returned. type: array items: type: object properties: token: description: The token. type: string logprob: description: The log probability of this token. type: number bytes: description: A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token. type: array items: type: integer nullable: true required: - token - logprob - bytes required: - token - logprob - bytes - top_logprobs chatCompletionResponseMessage: type: object description: A chat completion message generated by the model. properties: role: $ref: '#/components/schemas/chatCompletionResponseMessageRole' content: type: string description: The contents of the message. nullable: true tool_calls: type: array description: The tool calls generated by the model, such as function calls. items: $ref: '#/components/schemas/chatCompletionMessageToolCall' function_call: $ref: '#/components/schemas/chatCompletionFunctionCall' context: $ref: '#/components/schemas/azureChatExtensionsMessageContext' chatCompletionResponseMessageRole: type: string enum: - assistant description: The role of the author of the response message. chatCompletionToolChoiceOption: description: 'Controls which (if any) function is called by the model. `none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function. Specifying a particular function via `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that function.' oneOf: - type: string description: '`none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function.' enum: - none - auto - required - $ref: '#/components/schemas/chatCompletionNamedToolChoice' chatCompletionNamedToolChoice: type: object description: Specifies a tool the model should use. Use to force the model to call a specific function. properties: type: type: string enum: - function description: The type of the tool. Currently, only `function` is supported. function: type: object properties: name: type: string description: The name of the function to call. required: - name chatCompletionFunctionCall: type: object description: Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model. properties: name: type: string description: The name of the function to call. arguments: type: string description: The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function. required: - name - arguments chatCompletionsResponseCommon: type: object properties: id: type: string description: A unique identifier for the chat completion. object: $ref: '#/components/schemas/chatCompletionResponseObject' created: type: integer format: unixtime description: The Unix timestamp (in seconds) of when the chat completion was created. model: type: string description: The model used for the chat completion. usage: $ref: '#/components/schemas/completionUsage' system_fingerprint: type: string description: Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism. required: - id - object - created - model chatCompletionResponseObject: type: string description: The object type. enum: - chat.completion x-ms-enum: name: ChatCompletionResponseObject modelAsString: true values: - value: chat.completion description: The object type is chat completion. completionUsage: type: object description: Usage statistics for the completion request. properties: prompt_tokens: type: integer description: Number of tokens in the prompt. completion_tokens: type: integer description: Number of tokens in the generated completion. total_tokens: type: integer description: Total number of tokens used in the request (prompt + completion). required: - prompt_tokens - completion_tokens - total_tokens chatCompletionTool: type: object properties: type: $ref: '#/components/schemas/chatCompletionToolType' function: type: object properties: description: type: string description: A description of what the function does, used by the model to choose when and how to call the function. name: type: string description: The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64. parameters: $ref: '#/components/schemas/chatCompletionFunctionParameters' required: - name - parameters required: - type - function chatCompletionToolType: type: string enum: - function description: The type of the tool. Currently, only `function` is supported. x-ms-enum: name: ChatCompletionToolType modelAsString: true values: - value: function description: The tool type is function. chatCompletionChoiceCommon: type: object properties: index: type: integer finish_reason: type: string createTranslationRequest: type: object description: Translation request. properties: file: type: string description: The audio file to translate. format: binary prompt: type: string description: An optional text to guide the model's style or continue a previous audio segment. The prompt should be in English. response_format: $ref: '#/components/schemas/audioResponseFormat' temperature: type: number default: 0 description: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit. required: - file audioResponse: description: Translation or transcription response when response_format was json type: object properties: text: type: string description: Translated or transcribed text. required: - text audioVerboseResponse: description: Translation or transcription response when response_format was verbose_json type: object allOf: - $ref: '#/components/schemas/audioResponse' - properties: task: type: string description: Type of audio task. enum: - transcribe - translate x-ms-enum: modelAsString: true language: type: string description: Language. duration: type: number description: Duration. segments: type: array items: $ref: '#/components/schemas/audioSegment' required: - text audioResponseFormat: title: AudioResponseFormat description: Defines the format of the output. enum: - json - text - srt - verbose_json - vtt type: string x-ms-enum: modelAsString: true createTranscriptionRequest: type: object description: Transcription request. properties: file: type: string description: The audio file object to transcribe. format: binary prompt: type: string description: An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language. response_format: $ref: '#/components/schemas/audioResponseFormat' temperature: type: number default: 0 description: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit. language: type: string description: The language of the input audio. Supplying the input language in ISO-639-1 format will improve accuracy and latency. required: - file audioSegment: type: object description: Transcription or translation segment. properties: id: type: integer description: Segment identifier. seek: type: number description: Offset of the segment. start: type: number description: Segment start offset. end: type: number description: Segment end offset. text: type: string description: Segment text. tokens: type: array items: type: number nullable: false description: Tokens of the text. temperature: type: number description: Temperature. avg_logprob: type: number description: Average log probability. compression_ratio: type: number description: Compression ratio. no_speech_prob: type: number description: Probability of 'no speech'. imageQuality: description: The quality of the image that will be generated. type: string enum: - standard - hd default: standard x-ms-enum: name: Quality modelAsString: true values: - value: standard description: Standard quality creates images with standard quality. name: Standard - value: hd description: HD quality creates images with finer details and greater consistency across the image. name: HD imagesResponseFormat: description: The format in which the generated images are returned. type: string enum: - url - b64_json default: url x-ms-enum: name: ImagesResponseFormat modelAsString: true values: - value: url description: The URL that provides temporary access to download the generated images. name: Url - value: b64_json description: The generated images are returned as base64 encoded string. name: Base64Json imageSize: description: The size of the generated images. type: string enum: - 1792x1024 - 1024x1792 - 1024x1024 default: 1024x1024 x-ms-enum: name: Size modelAsString: true values: - value: 1792x1024 description: The desired size of the generated image is 1792x1024 pixels. name: Size1792x1024 - value: 1024x1792 description: The desired size of the generated image is 1024x1792 pixels. name: Size1024x1792 - value: 1024x1024 description: The desired size of the generated image is 1024x1024 pixels. name: Size1024x1024 imageStyle: description: The style of the generated images. type: string enum: - vivid - natural default: vivid x-ms-enum: name: Style modelAsString: true values: - value: vivid description: Vivid creates images that are hyper-realistic and dramatic. name: Vivid - value: natural description: Natural creates images that are more natural and less hyper-realistic. name: Natural imageGenerationsRequest: type: object properties: prompt: description: A text description of the desired image(s). The maximum length is 4000 characters. type: string format: string example: a corgi in a field minLength: 1 'n': description: The number of images to generate. type: integer minimum: 1 maximum: 1 default: 1 size: $ref: '#/components/schemas/imageSize' response_format: $ref: '#/components/schemas/imagesResponseFormat' user: description: A unique identifier representing your end-user, which can help to monitor and detect abuse. type: string format: string example: user123456 quality: $ref: '#/components/schemas/imageQuality' style: $ref: '#/components/schemas/imageStyle' required: - prompt generateImagesResponse: type: object properties: created: type: integer format: unixtime description: The unix timestamp when the operation was created. example: '1676540381' data: type: array description: The result data of the operation, if successful items: $ref: '#/components/schemas/imageResult' required: - created - data imageResult: type: object description: The image url or encoded image if successful, and an error otherwise. properties: url: type: string description: The image url. example: https://www.contoso.com b64_json: type: string description: The base64 encoded image content_filter_results: $ref: '#/components/schemas/dalleContentFilterResults' revised_prompt: type: string description: The prompt that was used to generate the image, if there was any revision to the prompt. prompt_filter_results: $ref: '#/components/schemas/dalleFilterResults' securitySchemes: bearer: type: oauth2 flows: implicit: authorizationUrl: https://login.microsoftonline.com/common/oauth2/v2.0/authorize scopes: {} x-tokenInfoFunc: api.middleware.auth.bearer_auth x-scopeValidateFunc: api.middleware.auth.validate_scopes apiKey: type: apiKey name: api-key in: header