POST
/
llm
/
v1
/
chat
/
completions

Creates a chat completion that generates a textual response for one or more messages using a large language model.

Request

model
string
required

Name of the model.

messages
Object[]
required

One or more chat messages.

role
string
required

The role of the message author. One of system, assistant, or user.

content
string
required

The content of the message.

name
string

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

frequency_penalty
number

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim.

logit_bias
Object

Modify the likelihood of specified tokens appearing in the completion.

Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.

logprobs
boolean

Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.

top_logprobs
number

An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.

max_tokens
number

The maximum number of tokens that can be generated in the chat completion.

n
number

How many chat completion choices to generate for each input message.

Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.

presence_penalty
number

Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics.

response_format
Object

An object specifying the format that the model must output.

Setting to { "type": "json_object" } enables JSON mode, which guarantees the message the model generates is valid JSON.

Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly “stuck” request. Also note that the message content may be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.

type
string
required

Must be one of text or json_object.

seed
number

This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.

stop
string[]

Up to 4 sequences where the API will stop generating further tokens.

stream
boolean

If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.

temperature
number

What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

We generally recommend altering this or top_p but not both.

top_p
number

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top `10%“ probability mass are considered.

We generally recommend altering this or temperature but not both.

Response

Returned when stream is false or not set.

id
string

A unique identifier for the chat completion.

choices
Object[]

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

message
Object

A chat completion message generated by the model.

role
string

The role of the author of this message.

content
string

The contents of the message.

finish_reason
string

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.

stop_reason
string

The stop string or token id that caused the completion to stop, null if the completion finished for some other reason including encountering the EOS token

index
number

The index of the choice in the list of choices.

logprobs
Object

Log probability information for the choice.

content
Object[]

A list of message content tokens with log probability information.

token
string

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.

bytes
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.

top_logprobs
Object[]

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.

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.

bytes
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.

created
number

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

model
string

The model used for the chat completion.

system_fingerprint
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.

object
string

The object type, which is always chat.completion.

usage
Object

Usage statistics for the completion 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).

Stream Response

Returned when stream is true.

id
string

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

choices
Object[]

A list of chat completion choices. Can be more than one if n is greater than 1. Can also be empty for the last chunk.

delta
Object

A chat completion delta generated by streamed model responses.

role
string

The role of the author of this message.

content
string

The contents of the chunk message.

finish_reason
string

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.

index
number

The index of the choice in the list of choices.

logprobs
Object

Log probability information for the choice.

content
Object[]

A list of message content tokens with log probability information.

token
string

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.

bytes
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.

top_logprobs
Object[]

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.

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.

bytes
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.

created
number

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

model
string

The model used for the chat completion.

system_fingerprint
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.

object
string

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

usage
Object

it contains a null value except for the last chunk which contains the token usage statistics for the entire 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).