Streaming

Stream Chat Completions in real time. Receive chunks of completions returned from the model using server-sent events. Learn more.

Streaming events

event

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.

name: optional string

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.

name: optional string

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.

completion_tokens: number

Number of tokens in the generated completion.

prompt_tokens: number

Number of tokens in the prompt.

total_tokens: number

Total number of tokens used in the request (prompt + completion).

completion_tokens_details: optional object { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

Breakdown of tokens used in a completion.

accepted_prediction_tokens: optional number

When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

audio_tokens: optional number

Audio input tokens generated by the model.

reasoning_tokens: optional number

Tokens generated by the model for reasoning.

rejected_prediction_tokens: optional number

When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

prompt_tokens_details: optional object { audio_tokens, cached_tokens }

Breakdown of tokens used in the prompt.

audio_tokens: optional number

Audio input tokens present in the prompt.

cached_tokens: optional number

Cached tokens present in the prompt.

OBJECT

event

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}

....

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}