Chat

ChatCompletion = object { id, choices, created, 5 more }

Represents a chat completion response returned by model, based on the provided input.

id: string

A unique identifier for the chat completion.

choices: array of object { finish_reason, index, logprobs, message }

A list of chat completion choices. Can be more than one if n is greater than 1.

finish_reason: "stop" or "length" or "tool_calls" or 2 more

The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

One of the following:

"stop"

"length"

"tool_calls"

"content_filter"

"function_call"

index: number

The index of the choice in the list of choices.

logprobs: object { content, refusal }

Log probability information for the choice.

content: array of ChatCompletionTokenLogprob { token, bytes, logprob, top_logprobs }

A list of message content tokens with log probability information.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

top_logprobs: array of object { token, bytes, logprob }

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.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

refusal: array of ChatCompletionTokenLogprob { token, bytes, logprob, top_logprobs }

A list of message refusal tokens with log probability information.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

top_logprobs: array of object { token, bytes, logprob }

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.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

message: ChatCompletionMessage { content, refusal, role, 4 more }

A chat completion message generated by the model.

created: number

The Unix timestamp (in seconds) of when the chat completion was created.

model: string

The model used for the chat completion.

object: "chat.completion"

The object type, which is always chat.completion.

service_tier: optional "auto" or "default" or "flex" or 2 more

Specifies the processing type used for serving the request.

If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.
If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.
If set to 'flex' or 'priority', then the request will be processed with the corresponding service tier.
When not set, the default behavior is 'auto'.

When the service_tier parameter is set, the response body will include the service_tier value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.

One of the following:

"auto"

"default"

"flex"

"scale"

"priority"

Deprecatedsystem_fingerprint: optional string

This fingerprint represents the backend configuration that the model runs with.

Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

usage: optional CompletionUsage { completion_tokens, prompt_tokens, total_tokens, 2 more }

Usage statistics for the completion request.

ChatCompletionAllowedToolChoice = object { allowed_tools, type }

Constrains the tools available to the model to a pre-defined set.

allowed_tools: ChatCompletionAllowedTools { mode, tools }

Constrains the tools available to the model to a pre-defined set.

type: "allowed_tools"

Allowed tool configuration type. Always allowed_tools.

ChatCompletionAssistantMessageParam = object { role, audio, content, 4 more }

Messages sent by the model in response to user messages.

role: "assistant"

The role of the messages author, in this case assistant.

audio: optional object { id }

Data about a previous audio response from the model. Learn more.

id: string

Unique identifier for a previous audio response from the model.

content: optional string or array of ChatCompletionContentPartText { text, type } or ChatCompletionContentPartRefusal { refusal, type }

The contents of the assistant message. Required unless tool_calls or function_call is specified.

One of the following:

TextContent = string

The contents of the assistant message.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type } or ChatCompletionContentPartRefusal { refusal, type }

An array of content parts with a defined type. Can be one or more of type text, or exactly one of type refusal.

One of the following:

ChatCompletionContentPartText = object { text, type }

Learn about text inputs.

text: string

The text content.

type: "text"

The type of the content part.

ChatCompletionContentPartRefusal = object { refusal, type }

refusal: string

The refusal message generated by the model.

type: "refusal"

The type of the content part.

Deprecatedfunction_call: optional object { arguments, name }

Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

arguments: string

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.

The name of the function to call.

An optional name for the participant. Provides the model information to differentiate between participants of the same role.

refusal: optional string

The refusal message by the assistant.

tool_calls: optional array of ChatCompletionMessageToolCall

The tool calls generated by the model, such as function calls.

One of the following:

ChatCompletionMessageFunctionToolCall = object { id, function, type }

A call to a function tool created by the model.

id: string

The ID of the tool call.

function: object { arguments, name }

The function that the model called.

arguments: string

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.

The name of the function to call.

type: "function"

The type of the tool. Currently, only function is supported.

ChatCompletionMessageCustomToolCall = object { id, custom, type }

A call to a custom tool created by the model.

id: string

The ID of the tool call.

custom: object { input, name }

The custom tool that the model called.

input: string

The input for the custom tool call generated by the model.

The name of the custom tool to call.

type: "custom"

The type of the tool. Always custom.

ChatCompletionAudio = object { id, data, expires_at, transcript }

If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

id: string

Unique identifier for this audio response.

data: string

Base64 encoded audio bytes generated by the model, in the format specified in the request.

expires_at: number

The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

transcript: string

Transcript of the audio generated by the model.

ChatCompletionAudioParam = object { format, voice }

Parameters for audio output. Required when audio output is requested with modalities: ["audio"]. Learn more.

format: "wav" or "aac" or "mp3" or 3 more

Specifies the output audio format. Must be one of wav, mp3, flac, opus, or pcm16.

One of the following:

"wav"

"aac"

"mp3"

"flac"

"opus"

"pcm16"

voice: string or "alloy" or "ash" or "ballad" or 7 more or object { id }

The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }.

One of the following:

string

"alloy" or "ash" or "ballad" or 7 more

One of the following:

"alloy"

"ash"

"ballad"

"coral"

"echo"

"sage"

"shimmer"

"verse"

"marin"

"cedar"

ID = object { id }

Custom voice reference.

id: string

The custom voice ID, e.g. voice_1234.

ChatCompletionChunk = object { id, choices, created, 5 more }

Represents a streamed chunk of a chat completion response returned by the model, based on the provided input. Learn more.

id: string

A unique identifier for the chat completion. Each chunk has the same ID.

choices: array of object { delta, finish_reason, index, logprobs }

A list of chat completion choices. Can contain more than one elements if n is greater than 1. Can also be empty for the last chunk if you set stream_options: {"include_usage": true}.

delta: object { content, function_call, refusal, 2 more }

A chat completion delta generated by streamed model responses.

content: optional string

The contents of the chunk message.

Deprecatedfunction_call: optional object { arguments, name }

Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

arguments: optional string

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.

The name of the function to call.

refusal: optional string

The refusal message generated by the model.

role: optional "developer" or "system" or "user" or 2 more

The role of the author of this message.

One of the following:

"developer"

"system"

"user"

"assistant"

"tool"

tool_calls: optional array of object { index, id, function, type }

index: number

id: optional string

The ID of the tool call.

function: optional object { arguments, name }

arguments: optional string

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.

The name of the function to call.

type: optional "function"

The type of the tool. Currently, only function is supported.

finish_reason: "stop" or "length" or "tool_calls" or 2 more

The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

One of the following:

"stop"

"length"

"tool_calls"

"content_filter"

"function_call"

index: number

The index of the choice in the list of choices.

logprobs: optional object { content, refusal }

Log probability information for the choice.

content: array of ChatCompletionTokenLogprob { token, bytes, logprob, top_logprobs }

A list of message content tokens with log probability information.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

top_logprobs: array of object { token, bytes, logprob }

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.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

refusal: array of ChatCompletionTokenLogprob { token, bytes, logprob, top_logprobs }

A list of message refusal tokens with log probability information.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

top_logprobs: array of object { token, bytes, logprob }

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.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

created: number

The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same timestamp.

model: string

The model to generate the completion.

object: "chat.completion.chunk"

The object type, which is always chat.completion.chunk.

service_tier: optional "auto" or "default" or "flex" or 2 more

Specifies the processing type used for serving the request.

If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.
If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.
If set to 'flex' or 'priority', then the request will be processed with the corresponding service tier.
When not set, the default behavior is 'auto'.

When the service_tier parameter is set, the response body will include the service_tier value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.

One of the following:

"auto"

"default"

"flex"

"scale"

"priority"

Deprecatedsystem_fingerprint: optional string

This fingerprint represents the backend configuration that the model runs with. Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

usage: optional CompletionUsage { completion_tokens, prompt_tokens, total_tokens, 2 more }

An optional field that will only be present when you set stream_options: {"include_usage": true} in your request. When present, it contains a null value except for the last chunk which contains the token usage statistics for the entire request.

NOTE: If the stream is interrupted or cancelled, you may not receive the final usage chunk which contains the total token usage for the request.

ChatCompletionContentPart = ChatCompletionContentPartText { text, type } or ChatCompletionContentPartImage { image_url, type } or ChatCompletionContentPartInputAudio { input_audio, type } or object { file, type }

Learn about text inputs.

One of the following:

ChatCompletionContentPartText = object { text, type }

Learn about text inputs.

text: string

The text content.

type: "text"

The type of the content part.

ChatCompletionContentPartImage = object { image_url, type }

Learn about image inputs.

image_url: object { url, detail }

url: string

Either a URL of the image or the base64 encoded image data.

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detail: optional "auto" or "low" or "high"

Specifies the detail level of the image. Learn more in the Vision guide.

One of the following:

"auto"

"low"

"high"

type: "image_url"

The type of the content part.

ChatCompletionContentPartInputAudio = object { input_audio, type }

Learn about audio inputs.

input_audio: object { data, format }

data: string

Base64 encoded audio data.

format: "wav" or "mp3"

The format of the encoded audio data. Currently supports "wav" and "mp3".

One of the following:

"wav"

"mp3"

type: "input_audio"

The type of the content part. Always input_audio.

FileContentPart = object { file, type }

Learn about file inputs for text generation.

file: object { file_data, file_id, filename }

file_data: optional string

The base64 encoded file data, used when passing the file to the model as a string.

file_id: optional string

The ID of an uploaded file to use as input.

filename: optional string

The name of the file, used when passing the file to the model as a string.

type: "file"

The type of the content part. Always file.

ChatCompletionContentPartImage = object { image_url, type }

Learn about image inputs.

image_url: object { url, detail }

url: string

Either a URL of the image or the base64 encoded image data.

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detail: optional "auto" or "low" or "high"

Specifies the detail level of the image. Learn more in the Vision guide.

One of the following:

"auto"

"low"

"high"

type: "image_url"

The type of the content part.

ChatCompletionContentPartInputAudio = object { input_audio, type }

Learn about audio inputs.

input_audio: object { data, format }

data: string

Base64 encoded audio data.

format: "wav" or "mp3"

The format of the encoded audio data. Currently supports "wav" and "mp3".

One of the following:

"wav"

"mp3"

type: "input_audio"

The type of the content part. Always input_audio.

ChatCompletionContentPartRefusal = object { refusal, type }

refusal: string

The refusal message generated by the model.

type: "refusal"

The type of the content part.

ChatCompletionContentPartText = object { text, type }

Learn about text inputs.

text: string

The text content.

type: "text"

The type of the content part.

ChatCompletionCustomTool = object { custom, type }

A custom tool that processes input using a specified format.

custom: object { name, description, format }

Properties of the custom tool.

The name of the custom tool, used to identify it in tool calls.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional object { type } or object { grammar, type }

The input format for the custom tool. Default is unconstrained text.

One of the following:

TextFormat = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

GrammarFormat = object { grammar, type }

A grammar defined by the user.

grammar: object { definition, syntax }

Your chosen grammar.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

type: "custom"

The type of the custom tool. Always custom.

ChatCompletionDeleted = object { id, deleted, object }

id: string

The ID of the chat completion that was deleted.

deleted: boolean

Whether the chat completion was deleted.

object: "chat.completion.deleted"

The type of object being deleted.

ChatCompletionDeveloperMessageParam = object { content, role, name }

Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, developer messages replace the previous system messages.

content: string or array of ChatCompletionContentPartText { text, type }

The contents of the developer message.

One of the following:

TextContent = string

The contents of the developer message.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type }

An array of content parts with a defined type. For developer messages, only type text is supported.

text: string

The text content.

type: "text"

The type of the content part.

role: "developer"

The role of the messages author, in this case developer.

An optional name for the participant. Provides the model information to differentiate between participants of the same role.

ChatCompletionFunctionCallOption = object { name }

Specifying a particular function via {"name": "my_function"} forces the model to call that function.

The name of the function to call.

ChatCompletionFunctionMessageParam = object { content, name, role }

content: string

The contents of the function message.

The name of the function to call.

role: "function"

The role of the messages author, in this case function.

ChatCompletionFunctionTool = object { function, type }

A function tool that can be used to generate a response.

function: FunctionDefinition { name, description, parameters, strict }

type: "function"

The type of the tool. Currently, only function is supported.

ChatCompletionMessage = object { content, refusal, role, 4 more }

A chat completion message generated by the model.

content: string

The contents of the message.

refusal: string

The refusal message generated by the model.

role: "assistant"

The role of the author of this message.

annotations: optional array of object { type, url_citation }

Annotations for the message, when applicable, as when using the web search tool.

type: "url_citation"

The type of the URL citation. Always url_citation.

url_citation: object { end_index, start_index, title, url }

A URL citation when using web search.

end_index: number

The index of the last character of the URL citation in the message.

start_index: number

The index of the first character of the URL citation in the message.

title: string

The title of the web resource.

url: string

The URL of the web resource.

audio: optional ChatCompletionAudio { id, data, expires_at, transcript }

If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

Deprecatedfunction_call: optional object { arguments, name }

Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

arguments: string

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.

The name of the function to call.

tool_calls: optional array of ChatCompletionMessageToolCall

The tool calls generated by the model, such as function calls.

One of the following:

ChatCompletionMessageFunctionToolCall = object { id, function, type }

A call to a function tool created by the model.

id: string

The ID of the tool call.

function: object { arguments, name }

The function that the model called.

arguments: string

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.

The name of the function to call.

type: "function"

The type of the tool. Currently, only function is supported.

ChatCompletionMessageCustomToolCall = object { id, custom, type }

A call to a custom tool created by the model.

id: string

The ID of the tool call.

custom: object { input, name }

The custom tool that the model called.

input: string

The input for the custom tool call generated by the model.

The name of the custom tool to call.

type: "custom"

The type of the tool. Always custom.

ChatCompletionMessageCustomToolCall = object { id, custom, type }

A call to a custom tool created by the model.

id: string

The ID of the tool call.

custom: object { input, name }

The custom tool that the model called.

input: string

The input for the custom tool call generated by the model.

The name of the custom tool to call.

type: "custom"

The type of the tool. Always custom.

ChatCompletionMessageFunctionToolCall = object { id, function, type }

A call to a function tool created by the model.

id: string

The ID of the tool call.

function: object { arguments, name }

The function that the model called.

arguments: string

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.

The name of the function to call.

type: "function"

The type of the tool. Currently, only function is supported.

ChatCompletionMessageParam = ChatCompletionDeveloperMessageParam { content, role, name } or ChatCompletionSystemMessageParam { content, role, name } or ChatCompletionUserMessageParam { content, role, name } or 3 more

Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, developer messages replace the previous system messages.

One of the following:

ChatCompletionDeveloperMessageParam = object { content, role, name }

Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, developer messages replace the previous system messages.

content: string or array of ChatCompletionContentPartText { text, type }

The contents of the developer message.

One of the following:

TextContent = string

The contents of the developer message.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type }

An array of content parts with a defined type. For developer messages, only type text is supported.

text: string

The text content.

type: "text"

The type of the content part.

role: "developer"

The role of the messages author, in this case developer.

An optional name for the participant. Provides the model information to differentiate between participants of the same role.

ChatCompletionSystemMessageParam = object { content, role, name }

Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, use developer messages for this purpose instead.

content: string or array of ChatCompletionContentPartText { text, type }

The contents of the system message.

One of the following:

TextContent = string

The contents of the system message.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type }

An array of content parts with a defined type. For system messages, only type text is supported.

text: string

The text content.

type: "text"

The type of the content part.

role: "system"

The role of the messages author, in this case system.

An optional name for the participant. Provides the model information to differentiate between participants of the same role.

ChatCompletionUserMessageParam = object { content, role, name }

Messages sent by an end user, containing prompts or additional context information.

content: string or array of ChatCompletionContentPart

The contents of the user message.

One of the following:

TextContent = string

The text contents of the message.

ArrayOfContentParts = array of ChatCompletionContentPart

An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text, image, or audio inputs.

One of the following:

ChatCompletionContentPartText = object { text, type }

Learn about text inputs.

text: string

The text content.

type: "text"

The type of the content part.

ChatCompletionContentPartImage = object { image_url, type }

Learn about image inputs.

image_url: object { url, detail }

url: string

Either a URL of the image or the base64 encoded image data.

formaturi

detail: optional "auto" or "low" or "high"

Specifies the detail level of the image. Learn more in the Vision guide.

One of the following:

"auto"

"low"

"high"

type: "image_url"

The type of the content part.

ChatCompletionContentPartInputAudio = object { input_audio, type }

Learn about audio inputs.

input_audio: object { data, format }

data: string

Base64 encoded audio data.

format: "wav" or "mp3"

The format of the encoded audio data. Currently supports "wav" and "mp3".

One of the following:

"wav"

"mp3"

type: "input_audio"

The type of the content part. Always input_audio.

FileContentPart = object { file, type }

Learn about file inputs for text generation.

file: object { file_data, file_id, filename }

file_data: optional string

The base64 encoded file data, used when passing the file to the model as a string.

file_id: optional string

The ID of an uploaded file to use as input.

filename: optional string

The name of the file, used when passing the file to the model as a string.

type: "file"

The type of the content part. Always file.

role: "user"

The role of the messages author, in this case user.

An optional name for the participant. Provides the model information to differentiate between participants of the same role.

ChatCompletionAssistantMessageParam = object { role, audio, content, 4 more }

Messages sent by the model in response to user messages.

role: "assistant"

The role of the messages author, in this case assistant.

audio: optional object { id }

Data about a previous audio response from the model. Learn more.

id: string

Unique identifier for a previous audio response from the model.

content: optional string or array of ChatCompletionContentPartText { text, type } or ChatCompletionContentPartRefusal { refusal, type }

The contents of the assistant message. Required unless tool_calls or function_call is specified.

One of the following:

TextContent = string

The contents of the assistant message.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type } or ChatCompletionContentPartRefusal { refusal, type }

An array of content parts with a defined type. Can be one or more of type text, or exactly one of type refusal.

One of the following:

ChatCompletionContentPartText = object { text, type }

Learn about text inputs.

text: string

The text content.

type: "text"

The type of the content part.

ChatCompletionContentPartRefusal = object { refusal, type }

refusal: string

The refusal message generated by the model.

type: "refusal"

The type of the content part.

Deprecatedfunction_call: optional object { arguments, name }

Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

arguments: string

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.

The name of the function to call.

An optional name for the participant. Provides the model information to differentiate between participants of the same role.

refusal: optional string

The refusal message by the assistant.

tool_calls: optional array of ChatCompletionMessageToolCall

The tool calls generated by the model, such as function calls.

One of the following:

ChatCompletionMessageFunctionToolCall = object { id, function, type }

A call to a function tool created by the model.

id: string

The ID of the tool call.

function: object { arguments, name }

The function that the model called.

arguments: string

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.

The name of the function to call.

type: "function"

The type of the tool. Currently, only function is supported.

ChatCompletionMessageCustomToolCall = object { id, custom, type }

A call to a custom tool created by the model.

id: string

The ID of the tool call.

custom: object { input, name }

The custom tool that the model called.

input: string

The input for the custom tool call generated by the model.

The name of the custom tool to call.

type: "custom"

The type of the tool. Always custom.

ChatCompletionToolMessageParam = object { content, role, tool_call_id }

content: string or array of ChatCompletionContentPartText { text, type }

The contents of the tool message.

One of the following:

TextContent = string

The contents of the tool message.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type }

An array of content parts with a defined type. For tool messages, only type text is supported.

text: string

The text content.

type: "text"

The type of the content part.

role: "tool"

The role of the messages author, in this case tool.

tool_call_id: string

Tool call that this message is responding to.

ChatCompletionFunctionMessageParam = object { content, name, role }

content: string

The contents of the function message.

The name of the function to call.

role: "function"

The role of the messages author, in this case function.

ChatCompletionMessageToolCall = ChatCompletionMessageFunctionToolCall { id, function, type } or ChatCompletionMessageCustomToolCall { id, custom, type }

A call to a function tool created by the model.

One of the following:

ChatCompletionMessageFunctionToolCall = object { id, function, type }

A call to a function tool created by the model.

id: string

The ID of the tool call.

function: object { arguments, name }

The function that the model called.

arguments: string

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.

The name of the function to call.

type: "function"

The type of the tool. Currently, only function is supported.

ChatCompletionMessageCustomToolCall = object { id, custom, type }

A call to a custom tool created by the model.

id: string

The ID of the tool call.

custom: object { input, name }

The custom tool that the model called.

input: string

The input for the custom tool call generated by the model.

The name of the custom tool to call.

type: "custom"

The type of the tool. Always custom.

ChatCompletionModality = "text" or "audio"

One of the following:

"text"

"audio"

ChatCompletionNamedToolChoice = object { function, type }

Specifies a tool the model should use. Use to force the model to call a specific function.

function: object { name }

The name of the function to call.

type: "function"

For function calling, the type is always function.

ChatCompletionNamedToolChoiceCustom = object { custom, type }

Specifies a tool the model should use. Use to force the model to call a specific custom tool.

custom: object { name }

The name of the custom tool to call.

type: "custom"

For custom tool calling, the type is always custom.

ChatCompletionPredictionContent = object { content, type }

Static predicted output content, such as the content of a text file that is being regenerated.

content: string or array of ChatCompletionContentPartText { text, type }

The content that should be matched when generating a model response. If generated tokens would match this content, the entire model response can be returned much more quickly.

One of the following:

TextContent = string

The content used for a Predicted Output. This is often the text of a file you are regenerating with minor changes.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type }

An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text inputs.

text: string

The text content.

type: "text"

The type of the content part.

type: "content"

The type of the predicted content you want to provide. This type is currently always content.

ChatCompletionRole = "developer" or "system" or "user" or 3 more

The role of the author of a message

One of the following:

"developer"

"system"

"user"

"assistant"

"tool"

"function"

ChatCompletionStoreMessage = ChatCompletionMessage { content, refusal, role, 4 more }

A chat completion message generated by the model.

id: string

The identifier of the chat message.

content_parts: optional array of ChatCompletionContentPartText { text, type } or ChatCompletionContentPartImage { image_url, type }

If a content parts array was provided, this is an array of text and image_url parts. Otherwise, null.

One of the following:

ChatCompletionContentPartText = object { text, type }

Learn about text inputs.

text: string

The text content.

type: "text"

The type of the content part.

ChatCompletionContentPartImage = object { image_url, type }

Learn about image inputs.

image_url: object { url, detail }

url: string

Either a URL of the image or the base64 encoded image data.

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detail: optional "auto" or "low" or "high"

Specifies the detail level of the image. Learn more in the Vision guide.

One of the following:

"auto"

"low"

"high"

type: "image_url"

The type of the content part.

ChatCompletionStreamOptions = object { include_obfuscation, include_usage }

Options for streaming response. Only set this when you set stream: true.

include_obfuscation: optional boolean

When true, stream obfuscation will be enabled. Stream obfuscation adds random characters to an obfuscation field on streaming delta events to normalize payload sizes as a mitigation to certain side-channel attacks. These obfuscation fields are included by default, but add a small amount of overhead to the data stream. You can set include_obfuscation to false to optimize for bandwidth if you trust the network links between your application and the OpenAI API.

include_usage: optional boolean

If set, an additional chunk will be streamed before the data: [DONE] message. The usage field on this chunk shows the token usage statistics for the entire request, and the choices field will always be an empty array.

All other chunks will also include a usage field, but with a null value. NOTE: If the stream is interrupted, you may not receive the final usage chunk which contains the total token usage for the request.

ChatCompletionSystemMessageParam = object { content, role, name }

Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, use developer messages for this purpose instead.

content: string or array of ChatCompletionContentPartText { text, type }

The contents of the system message.

One of the following:

TextContent = string

The contents of the system message.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type }

An array of content parts with a defined type. For system messages, only type text is supported.

text: string

The text content.

type: "text"

The type of the content part.

role: "system"

The role of the messages author, in this case system.

An optional name for the participant. Provides the model information to differentiate between participants of the same role.

ChatCompletionTokenLogprob = object { token, bytes, logprob, top_logprobs }

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

top_logprobs: array of object { token, bytes, logprob }

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.

token: string

The token.

bytes: array of number

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.

logprob: number

The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

ChatCompletionTool = ChatCompletionFunctionTool { function, type } or ChatCompletionCustomTool { custom, type }

A function tool that can be used to generate a response.

One of the following:

ChatCompletionFunctionTool = object { function, type }

A function tool that can be used to generate a response.

function: FunctionDefinition { name, description, parameters, strict }

type: "function"

The type of the tool. Currently, only function is supported.

ChatCompletionCustomTool = object { custom, type }

A custom tool that processes input using a specified format.

custom: object { name, description, format }

Properties of the custom tool.

The name of the custom tool, used to identify it in tool calls.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional object { type } or object { grammar, type }

The input format for the custom tool. Default is unconstrained text.

One of the following:

TextFormat = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

GrammarFormat = object { grammar, type }

A grammar defined by the user.

grammar: object { definition, syntax }

Your chosen grammar.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

type: "custom"

The type of the custom tool. Always custom.

ChatCompletionToolChoiceOption = "none" or "auto" or "required" or ChatCompletionAllowedToolChoice { allowed_tools, type } or ChatCompletionNamedToolChoice { function, type } or ChatCompletionNamedToolChoiceCustom { custom, type }

Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.

none is the default when no tools are present. auto is the default if tools are present.

One of the following:

ToolChoiceMode = "none" or "auto" or "required"

none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools.

One of the following:

"none"

"auto"

"required"

ChatCompletionAllowedToolChoice = object { allowed_tools, type }

Constrains the tools available to the model to a pre-defined set.

allowed_tools: ChatCompletionAllowedTools { mode, tools }

Constrains the tools available to the model to a pre-defined set.

type: "allowed_tools"

Allowed tool configuration type. Always allowed_tools.

ChatCompletionNamedToolChoice = object { function, type }

Specifies a tool the model should use. Use to force the model to call a specific function.

function: object { name }

The name of the function to call.

type: "function"

For function calling, the type is always function.

ChatCompletionNamedToolChoiceCustom = object { custom, type }

Specifies a tool the model should use. Use to force the model to call a specific custom tool.

custom: object { name }

The name of the custom tool to call.

type: "custom"

For custom tool calling, the type is always custom.

ChatCompletionToolMessageParam = object { content, role, tool_call_id }

content: string or array of ChatCompletionContentPartText { text, type }

The contents of the tool message.

One of the following:

TextContent = string

The contents of the tool message.

ArrayOfContentParts = array of ChatCompletionContentPartText { text, type }

An array of content parts with a defined type. For tool messages, only type text is supported.

text: string

The text content.

type: "text"

The type of the content part.

role: "tool"

The role of the messages author, in this case tool.

tool_call_id: string

Tool call that this message is responding to.

ChatCompletionUserMessageParam = object { content, role, name }

Messages sent by an end user, containing prompts or additional context information.

content: string or array of ChatCompletionContentPart

The contents of the user message.

One of the following:

TextContent = string

The text contents of the message.

ArrayOfContentParts = array of ChatCompletionContentPart

An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text, image, or audio inputs.

One of the following:

ChatCompletionContentPartText = object { text, type }

Learn about text inputs.

text: string

The text content.

type: "text"

The type of the content part.

ChatCompletionContentPartImage = object { image_url, type }

Learn about image inputs.

image_url: object { url, detail }

url: string

Either a URL of the image or the base64 encoded image data.

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detail: optional "auto" or "low" or "high"

Specifies the detail level of the image. Learn more in the Vision guide.

One of the following:

"auto"

"low"

"high"

type: "image_url"

The type of the content part.

ChatCompletionContentPartInputAudio = object { input_audio, type }

Learn about audio inputs.

input_audio: object { data, format }

data: string

Base64 encoded audio data.

format: "wav" or "mp3"

The format of the encoded audio data. Currently supports "wav" and "mp3".

One of the following:

"wav"

"mp3"

type: "input_audio"

The type of the content part. Always input_audio.

FileContentPart = object { file, type }

Learn about file inputs for text generation.

file: object { file_data, file_id, filename }

file_data: optional string

The base64 encoded file data, used when passing the file to the model as a string.

file_id: optional string

The ID of an uploaded file to use as input.

filename: optional string

The name of the file, used when passing the file to the model as a string.

type: "file"

The type of the content part. Always file.

role: "user"

The role of the messages author, in this case user.

An optional name for the participant. Provides the model information to differentiate between participants of the same role.

ChatCompletionAllowedTools = object { mode, tools }

Constrains the tools available to the model to a pre-defined set.

mode: "auto" or "required"

Constrains the tools available to the model to a pre-defined set.

auto allows the model to pick from among the allowed tools and generate a message.

required requires the model to call one or more of the allowed tools.

One of the following:

"auto"

"required"

tools: array of map[unknown]

A list of tool definitions that the model should be allowed to call.

For the Chat Completions API, the list of tool definitions might look like:

[
  { "type": "function", "function": { "name": "get_weather" } },
  { "type": "function", "function": { "name": "get_time" } }
]

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