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Chat

ChatCompletions

Given a list of messages comprising a conversation, the model will return a response.

Create chat completion
chat.completions.create(CompletionCreateParams**kwargs) -> ChatCompletion
POST/chat/completions
List Chat Completions
chat.completions.list(CompletionListParams**kwargs) -> SyncCursorPage[ChatCompletion]
GET/chat/completions
Get chat completion
chat.completions.retrieve(strcompletion_id) -> ChatCompletion
GET/chat/completions/{completion_id}
Update chat completion
chat.completions.update(strcompletion_id, CompletionUpdateParams**kwargs) -> ChatCompletion
POST/chat/completions/{completion_id}
Delete chat completion
chat.completions.delete(strcompletion_id) -> ChatCompletionDeleted
DELETE/chat/completions/{completion_id}
ModelsExpand Collapse
class ChatCompletion: …

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

id: str

A unique identifier for the chat completion.

choices: List[Choice]

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

finish_reason: Literal["stop", "length", "tool_calls", 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: int

The index of the choice in the list of choices.

logprobs: Optional[ChoiceLogprobs]

Log probability information for the choice.

content: Optional[List[ChatCompletionTokenLogprob]]

A list of message content tokens with log probability information.

token: str

The token.

bytes: Optional[List[int]]

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: float

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: List[TopLogprob]

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: str

The token.

bytes: Optional[List[int]]

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: float

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: Optional[List[ChatCompletionTokenLogprob]]

A list of message refusal tokens with log probability information.

token: str

The token.

bytes: Optional[List[int]]

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: float

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: List[TopLogprob]

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: str

The token.

bytes: Optional[List[int]]

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: float

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

A chat completion message generated by the model.

created: int

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

model: str

The model used for the chat completion.

object: Literal["chat.completion"]

The object type, which is always chat.completion.

service_tier: Optional[Literal["auto", "default", "flex", 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[str]

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]

Usage statistics for the completion request.

class ChatCompletionAllowedToolChoice: …

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

allowed_tools: ChatCompletionAllowedTools

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

type: Literal["allowed_tools"]

Allowed tool configuration type. Always allowed_tools.

class ChatCompletionAssistantMessageParam: …

Messages sent by the model in response to user messages.

role: Literal["assistant"]

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

audio: Optional[Audio]

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

id: str

Unique identifier for a previous audio response from the model.

content: Optional[Union[str, List[ContentArrayOfContentPart], null]]

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

One of the following:
str

The contents of the assistant message.

List[ContentArrayOfContentPart]

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:
class ChatCompletionContentPartText: …

Learn about text inputs.

text: str

The text content.

type: Literal["text"]

The type of the content part.

class ChatCompletionContentPartRefusal: …
refusal: str

The refusal message generated by the model.

type: Literal["refusal"]

The type of the content part.

Deprecatedfunction_call: Optional[FunctionCall]

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

arguments: str

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.

name: str

The name of the function to call.

name: Optional[str]

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

refusal: Optional[str]

The refusal message by the assistant.

tool_calls: Optional[List[ChatCompletionMessageToolCallUnion]]

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

One of the following:
class ChatCompletionMessageFunctionToolCall: …

A call to a function tool created by the model.

id: str

The ID of the tool call.

function: Function

The function that the model called.

arguments: str

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.

name: str

The name of the function to call.

type: Literal["function"]

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

class ChatCompletionMessageCustomToolCall: …

A call to a custom tool created by the model.

id: str

The ID of the tool call.

custom: Custom

The custom tool that the model called.

input: str

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

name: str

The name of the custom tool to call.

type: Literal["custom"]

The type of the tool. Always custom.

class ChatCompletionAudio: …

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

id: str

Unique identifier for this audio response.

data: str

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

expires_at: int

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: str

Transcript of the audio generated by the model.

class ChatCompletionAudioParam: …

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

format: Literal["wav", "aac", "mp3", 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: Voice

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:
str
Literal["alloy", "ash", "ballad", 7 more]
One of the following:
"alloy"
"ash"
"ballad"
"coral"
"echo"
"sage"
"shimmer"
"verse"
"marin"
"cedar"
class VoiceID: …

Custom voice reference.

id: str

The custom voice ID, e.g. voice_1234.

class ChatCompletionChunk: …

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

id: str

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

choices: List[Choice]

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: ChoiceDelta

A chat completion delta generated by streamed model responses.

content: Optional[str]

The contents of the chunk message.

Deprecatedfunction_call: Optional[ChoiceDeltaFunctionCall]

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

arguments: Optional[str]

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.

name: Optional[str]

The name of the function to call.

refusal: Optional[str]

The refusal message generated by the model.

role: Optional[Literal["developer", "system", "user", 2 more]]

The role of the author of this message.

One of the following:
"developer"
"system"
"user"
"assistant"
"tool"
tool_calls: Optional[List[ChoiceDeltaToolCall]]
index: int
id: Optional[str]

The ID of the tool call.

function: Optional[ChoiceDeltaToolCallFunction]
arguments: Optional[str]

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.

name: Optional[str]

The name of the function to call.

type: Optional[Literal["function"]]

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

finish_reason: Optional[Literal["stop", "length", "tool_calls", 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: int

The index of the choice in the list of choices.

logprobs: Optional[ChoiceLogprobs]

Log probability information for the choice.

content: Optional[List[ChatCompletionTokenLogprob]]

A list of message content tokens with log probability information.

token: str

The token.

bytes: Optional[List[int]]

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: float

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: List[TopLogprob]

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: str

The token.

bytes: Optional[List[int]]

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: float

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: Optional[List[ChatCompletionTokenLogprob]]

A list of message refusal tokens with log probability information.

token: str

The token.

bytes: Optional[List[int]]

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: float

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: List[TopLogprob]

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: str

The token.

bytes: Optional[List[int]]

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: float

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: int

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

model: str

The model to generate the completion.

object: Literal["chat.completion.chunk"]

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

service_tier: Optional[Literal["auto", "default", "flex", 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[str]

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]

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

Learn about text inputs.

One of the following:
class ChatCompletionContentPartText: …

Learn about text inputs.

text: str

The text content.

type: Literal["text"]

The type of the content part.

class ChatCompletionContentPartImage: …

Learn about image inputs.

image_url: ImageURL
url: str

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

formaturi
detail: Optional[Literal["auto", "low", "high"]]

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

One of the following:
"auto"
"low"
"high"
type: Literal["image_url"]

The type of the content part.

class ChatCompletionContentPartInputAudio: …

Learn about audio inputs.

input_audio: InputAudio
data: str

Base64 encoded audio data.

format: Literal["wav", "mp3"]

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

One of the following:
"wav"
"mp3"
type: Literal["input_audio"]

The type of the content part. Always input_audio.

class File: …

Learn about file inputs for text generation.

file: FileFile
file_data: Optional[str]

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

file_id: Optional[str]

The ID of an uploaded file to use as input.

filename: Optional[str]

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

type: Literal["file"]

The type of the content part. Always file.

class ChatCompletionContentPartImage: …

Learn about image inputs.

image_url: ImageURL
url: str

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

formaturi
detail: Optional[Literal["auto", "low", "high"]]

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

One of the following:
"auto"
"low"
"high"
type: Literal["image_url"]

The type of the content part.

class ChatCompletionContentPartInputAudio: …

Learn about audio inputs.

input_audio: InputAudio
data: str

Base64 encoded audio data.

format: Literal["wav", "mp3"]

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

One of the following:
"wav"
"mp3"
type: Literal["input_audio"]

The type of the content part. Always input_audio.

class ChatCompletionContentPartRefusal: …
refusal: str

The refusal message generated by the model.

type: Literal["refusal"]

The type of the content part.

class ChatCompletionContentPartText: …

Learn about text inputs.

text: str

The text content.

type: Literal["text"]

The type of the content part.

class ChatCompletionCustomTool: …

A custom tool that processes input using a specified format.

custom: Custom

Properties of the custom tool.

name: str

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

description: Optional[str]

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

format: Optional[CustomFormat]

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

One of the following:
class CustomFormatText: …

Unconstrained free-form text.

type: Literal["text"]

Unconstrained text format. Always text.

class CustomFormatGrammar: …

A grammar defined by the user.

grammar: CustomFormatGrammarGrammar

Your chosen grammar.

definition: str

The grammar definition.

syntax: Literal["lark", "regex"]

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

One of the following:
"lark"
"regex"
type: Literal["grammar"]

Grammar format. Always grammar.

type: Literal["custom"]

The type of the custom tool. Always custom.

class ChatCompletionDeleted: …
id: str

The ID of the chat completion that was deleted.

deleted: bool

Whether the chat completion was deleted.

object: Literal["chat.completion.deleted"]

The type of object being deleted.

class ChatCompletionDeveloperMessageParam: …

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: Union[str, List[ChatCompletionContentPartText]]

The contents of the developer message.

One of the following:
str

The contents of the developer message.

List[ChatCompletionContentPartText]

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

text: str

The text content.

type: Literal["text"]

The type of the content part.

role: Literal["developer"]

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

name: Optional[str]

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

class ChatCompletionFunctionCallOption: …

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

name: str

The name of the function to call.

class ChatCompletionFunctionMessageParam: …
content: Optional[str]

The contents of the function message.

name: str

The name of the function to call.

role: Literal["function"]

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

class ChatCompletionFunctionTool: …

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

type: Literal["function"]

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

class ChatCompletionMessage: …

A chat completion message generated by the model.

content: Optional[str]

The contents of the message.

refusal: Optional[str]

The refusal message generated by the model.

role: Literal["assistant"]

The role of the author of this message.

annotations: Optional[List[Annotation]]

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

type: Literal["url_citation"]

The type of the URL citation. Always url_citation.

url_citation: AnnotationURLCitation

A URL citation when using web search.

end_index: int

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

start_index: int

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

title: str

The title of the web resource.

url: str

The URL of the web resource.

audio: Optional[ChatCompletionAudio]

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

Deprecatedfunction_call: Optional[FunctionCall]

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

arguments: str

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.

name: str

The name of the function to call.

tool_calls: Optional[List[ChatCompletionMessageToolCallUnion]]

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

One of the following:
class ChatCompletionMessageFunctionToolCall: …

A call to a function tool created by the model.

id: str

The ID of the tool call.

function: Function

The function that the model called.

arguments: str

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.

name: str

The name of the function to call.

type: Literal["function"]

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

class ChatCompletionMessageCustomToolCall: …

A call to a custom tool created by the model.

id: str

The ID of the tool call.

custom: Custom

The custom tool that the model called.

input: str

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

name: str

The name of the custom tool to call.

type: Literal["custom"]

The type of the tool. Always custom.

class ChatCompletionMessageCustomToolCall: …

A call to a custom tool created by the model.

id: str

The ID of the tool call.

custom: Custom

The custom tool that the model called.

input: str

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

name: str

The name of the custom tool to call.

type: Literal["custom"]

The type of the tool. Always custom.

class ChatCompletionMessageFunctionToolCall: …

A call to a function tool created by the model.

id: str

The ID of the tool call.

function: Function

The function that the model called.

arguments: str

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.

name: str

The name of the function to call.

type: Literal["function"]

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

ChatCompletionMessageParam

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:
class ChatCompletionDeveloperMessageParam: …

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: Union[str, List[ChatCompletionContentPartText]]

The contents of the developer message.

One of the following:
str

The contents of the developer message.

List[ChatCompletionContentPartText]

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

text: str

The text content.

type: Literal["text"]

The type of the content part.

role: Literal["developer"]

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

name: Optional[str]

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

class ChatCompletionSystemMessageParam: …

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: Union[str, List[ChatCompletionContentPartText]]

The contents of the system message.

One of the following:
str

The contents of the system message.

List[ChatCompletionContentPartText]

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

text: str

The text content.

type: Literal["text"]

The type of the content part.

role: Literal["system"]

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

name: Optional[str]

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

class ChatCompletionUserMessageParam: …

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

content: Union[str, List[ChatCompletionContentPart]]

The contents of the user message.

One of the following:
str

The text contents of the message.

List[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:
class ChatCompletionContentPartText: …

Learn about text inputs.

text: str

The text content.

type: Literal["text"]

The type of the content part.

class ChatCompletionContentPartImage: …

Learn about image inputs.

image_url: ImageURL
url: str

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

formaturi
detail: Optional[Literal["auto", "low", "high"]]

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

One of the following:
"auto"
"low"
"high"
type: Literal["image_url"]

The type of the content part.

class ChatCompletionContentPartInputAudio: …

Learn about audio inputs.

input_audio: InputAudio
data: str

Base64 encoded audio data.

format: Literal["wav", "mp3"]

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

One of the following:
"wav"
"mp3"
type: Literal["input_audio"]

The type of the content part. Always input_audio.

class File: …

Learn about file inputs for text generation.

file: FileFile
file_data: Optional[str]

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

file_id: Optional[str]

The ID of an uploaded file to use as input.

filename: Optional[str]

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

type: Literal["file"]

The type of the content part. Always file.

role: Literal["user"]

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

name: Optional[str]

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

class ChatCompletionAssistantMessageParam: …

Messages sent by the model in response to user messages.

role: Literal["assistant"]

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

audio: Optional[Audio]

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

id: str

Unique identifier for a previous audio response from the model.

content: Optional[Union[str, List[ContentArrayOfContentPart], null]]

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

One of the following:
str

The contents of the assistant message.

List[ContentArrayOfContentPart]

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:
class ChatCompletionContentPartText: …

Learn about text inputs.

text: str

The text content.

type: Literal["text"]

The type of the content part.

class ChatCompletionContentPartRefusal: …
refusal: str

The refusal message generated by the model.

type: Literal["refusal"]

The type of the content part.

Deprecatedfunction_call: Optional[FunctionCall]

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

arguments: str

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.

name: str

The name of the function to call.

name: Optional[str]

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

refusal: Optional[str]

The refusal message by the assistant.

tool_calls: Optional[List[ChatCompletionMessageToolCallUnion]]

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

One of the following:
class ChatCompletionMessageFunctionToolCall: …

A call to a function tool created by the model.

id: str

The ID of the tool call.

function: Function

The function that the model called.

arguments: str

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.

name: str

The name of the function to call.

type: Literal["function"]

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

class ChatCompletionMessageCustomToolCall: …

A call to a custom tool created by the model.

id: str

The ID of the tool call.

custom: Custom

The custom tool that the model called.

input: str

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

name: str

The name of the custom tool to call.

type: Literal["custom"]

The type of the tool. Always custom.

class ChatCompletionToolMessageParam: …
content: Union[str, List[ChatCompletionContentPartText]]

The contents of the tool message.

One of the following:
str

The contents of the tool message.

List[ChatCompletionContentPartText]

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

text: str

The text content.

type: Literal["text"]

The type of the content part.

role: Literal["tool"]

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

tool_call_id: str

Tool call that this message is responding to.

class ChatCompletionFunctionMessageParam: …
content: Optional[str]

The contents of the function message.

name: str

The name of the function to call.

role: Literal["function"]

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

ChatCompletionMessageToolCallUnion

A call to a function tool created by the model.

One of the following:
class ChatCompletionMessageFunctionToolCall: …

A call to a function tool created by the model.

id: str

The ID of the tool call.

function: Function

The function that the model called.

arguments: str

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.

name: str

The name of the function to call.

type: Literal["function"]

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

class ChatCompletionMessageCustomToolCall: …

A call to a custom tool created by the model.

id: str

The ID of the tool call.

custom: Custom

The custom tool that the model called.

input: str

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

name: str

The name of the custom tool to call.

type: Literal["custom"]

The type of the tool. Always custom.

Literal["text", "audio"]
One of the following:
"text"
"audio"
class ChatCompletionNamedToolChoice: …

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

function: Function
name: str

The name of the function to call.

type: Literal["function"]

For function calling, the type is always function.

class ChatCompletionNamedToolChoiceCustom: …

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

custom: Custom
name: str

The name of the custom tool to call.

type: Literal["custom"]

For custom tool calling, the type is always custom.

class ChatCompletionPredictionContent: …

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

content: Union[str, List[ChatCompletionContentPartText]]

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:
str

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

List[ChatCompletionContentPartText]

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: str

The text content.

type: Literal["text"]

The type of the content part.

type: Literal["content"]

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

Literal["developer", "system", "user", 3 more]

The role of the author of a message

One of the following:
"developer"
"system"
"user"
"assistant"
"tool"
"function"
class ChatCompletionStoreMessage: …

A chat completion message generated by the model.

id: str

The identifier of the chat message.

content_parts: Optional[List[ChatCompletionStoreMessageContentPart]]

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

One of the following:
class ChatCompletionContentPartText: …

Learn about text inputs.

text: str

The text content.

type: Literal["text"]

The type of the content part.

class ChatCompletionContentPartImage: …

Learn about image inputs.

image_url: ImageURL
url: str

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

formaturi
detail: Optional[Literal["auto", "low", "high"]]

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

One of the following:
"auto"
"low"
"high"
type: Literal["image_url"]

The type of the content part.

class ChatCompletionStreamOptions: …

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

include_obfuscation: Optional[bool]

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[bool]

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.

class ChatCompletionSystemMessageParam: …

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: Union[str, List[ChatCompletionContentPartText]]

The contents of the system message.

One of the following:
str

The contents of the system message.

List[ChatCompletionContentPartText]

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

text: str

The text content.

type: Literal["text"]

The type of the content part.

role: Literal["system"]

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

name: Optional[str]

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

class ChatCompletionTokenLogprob: …
token: str

The token.

bytes: Optional[List[int]]

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: float

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: List[TopLogprob]

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: str

The token.

bytes: Optional[List[int]]

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: float

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.

ChatCompletionToolUnion

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

One of the following:
class ChatCompletionFunctionTool: …

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

type: Literal["function"]

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

class ChatCompletionCustomTool: …

A custom tool that processes input using a specified format.

custom: Custom

Properties of the custom tool.

name: str

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

description: Optional[str]

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

format: Optional[CustomFormat]

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

One of the following:
class CustomFormatText: …

Unconstrained free-form text.

type: Literal["text"]

Unconstrained text format. Always text.

class CustomFormatGrammar: …

A grammar defined by the user.

grammar: CustomFormatGrammarGrammar

Your chosen grammar.

definition: str

The grammar definition.

syntax: Literal["lark", "regex"]

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

One of the following:
"lark"
"regex"
type: Literal["grammar"]

Grammar format. Always grammar.

type: Literal["custom"]

The type of the custom tool. Always custom.

ChatCompletionToolChoiceOption

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:
Literal["none", "auto", "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"
class ChatCompletionAllowedToolChoice: …

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

allowed_tools: ChatCompletionAllowedTools

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

type: Literal["allowed_tools"]

Allowed tool configuration type. Always allowed_tools.

class ChatCompletionNamedToolChoice: …

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

function: Function
name: str

The name of the function to call.

type: Literal["function"]

For function calling, the type is always function.

class ChatCompletionNamedToolChoiceCustom: …

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

custom: Custom
name: str

The name of the custom tool to call.

type: Literal["custom"]

For custom tool calling, the type is always custom.

class ChatCompletionToolMessageParam: …
content: Union[str, List[ChatCompletionContentPartText]]

The contents of the tool message.

One of the following:
str

The contents of the tool message.

List[ChatCompletionContentPartText]

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

text: str

The text content.

type: Literal["text"]

The type of the content part.

role: Literal["tool"]

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

tool_call_id: str

Tool call that this message is responding to.

class ChatCompletionUserMessageParam: …

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

content: Union[str, List[ChatCompletionContentPart]]

The contents of the user message.

One of the following:
str

The text contents of the message.

List[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:
class ChatCompletionContentPartText: …

Learn about text inputs.

text: str

The text content.

type: Literal["text"]

The type of the content part.

class ChatCompletionContentPartImage: …

Learn about image inputs.

image_url: ImageURL
url: str

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

formaturi
detail: Optional[Literal["auto", "low", "high"]]

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

One of the following:
"auto"
"low"
"high"
type: Literal["image_url"]

The type of the content part.

class ChatCompletionContentPartInputAudio: …

Learn about audio inputs.

input_audio: InputAudio
data: str

Base64 encoded audio data.

format: Literal["wav", "mp3"]

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

One of the following:
"wav"
"mp3"
type: Literal["input_audio"]

The type of the content part. Always input_audio.

class File: …

Learn about file inputs for text generation.

file: FileFile
file_data: Optional[str]

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

file_id: Optional[str]

The ID of an uploaded file to use as input.

filename: Optional[str]

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

type: Literal["file"]

The type of the content part. Always file.

role: Literal["user"]

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

name: Optional[str]

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

class ChatCompletionAllowedTools: …

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

mode: Literal["auto", "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: List[Dict[str, object]]

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" } }
]

ChatCompletionsMessages

Given a list of messages comprising a conversation, the model will return a response.

Get chat messages
chat.completions.messages.list(strcompletion_id, MessageListParams**kwargs) -> SyncCursorPage[ChatCompletionStoreMessage]
GET/chat/completions/{completion_id}/messages