CreateChatCompletionRequest
objectOne Of>= 1 items
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.
Show Child Parameters
Any OfID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.
Example:gpt-4o
Whether or not to store the output of this chat completion request for
use in our model distillation or
evals products.
Default:false
o1 and o3-mini models only
Constrains effort on reasoning for
reasoning models.
Currently supported values are low, medium, and high. Reducing
reasoning effort can result in faster responses and fewer tokens used
on reasoning in a response.
Allowed values:lowmediumhigh
Default:medium
Set of 16 key-value pairs that can be attached to an object. This can be
useful for storing additional information about the object in a structured
format, and querying for objects via API or the dashboard.
Keys are strings with a maximum length of 64 characters. Values are strings
with a maximum length of 512 characters.
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.
Default:0
>= -2<= 2
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.
Default:null
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.
Default:false
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.
>= 0<= 20
The maximum number of tokens that can be generated in the
chat completion. This value can be used to control
costs for text generated via API.
This value is now deprecated in favor of max_completion_tokens, and is
not compatible with o1 series models.
An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.
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.
Default:1
>= 1<= 128
Example:1
Output types that you would like the model to generate for this request.
Most models are capable of generating text, which is the default:
["text"]
The gpt-4o-audio-preview model can also be used to generate audio. To
request that this model generate both text and audio responses, you can
use:
["text", "audio"]
Allowed values:textaudio
One OfConfiguration for a Predicted Output,
which can greatly improve response times when large parts of the model
response are known ahead of time. This is most common when you are
regenerating a file with only minor changes to most of the content.
Static predicted output content, such as the content of a text file that is
being regenerated.
Show Child Parameters
Parameters for audio output. Required when audio output is requested with
modalities: ["audio"]. Learn more.
Show Child Parameters
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.
Default:0
>= -2<= 2
One OfAn object specifying the format that the model must output.
Setting to { "type": "json_schema", "json_schema": {...} } enables
Structured Outputs which ensures the model will match your supplied JSON
schema. Learn more in the Structured Outputs
guide.
Setting to { "type": "json_object" } enables JSON mode, which ensures
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.
Show Child Parameters
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.
Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service:
- If set to ‘auto’, and the Project is Scale tier enabled, the system will utilize scale tier credits until they are exhausted.
- If set to ‘auto’, and the Project is not Scale tier enabled, the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.
- If set to ‘default’, the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.
- When not set, the default behavior is ‘auto’.
Allowed values:autodefault
Default:auto
One OfUp to 4 sequences where the API will stop generating further tokens.
Default:null
If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message. Example Python code.
Default:false
Options for streaming response. Only set this when you set stream: true.
Default:null
Show Child Parameters
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.
Default:1
>= 0<= 2
Example:1
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.
Default:1
>= 0<= 1
Example:1
A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
Show Child Parameters
One OfControls 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.
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.
Allowed values:noneautorequired
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
Example:user-1234
One OfDeprecated in favor of tool_choice.
Controls which (if any) function is called by the model.
none means the model will not call a function and instead generates a
message.
auto means the model can pick between generating a message or calling a
function.
Specifying a particular function via {"name": "my_function"} forces the
model to call that function.
none is the default when no functions are present. auto is the default
if functions are present.
none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function.
Allowed values:noneauto
Deprecated in favor of tools.
A list of functions the model may generate JSON inputs for.
>= 1 items<= 128 items
Show Child Parameters
CreateChatCompletionResponse
objectRepresents a chat completion response returned by model, based on the provided input.
A unique identifier for the chat completion.
A list of chat completion choices. Can be more than one if n is greater than 1.
Show Child Parameters
The Unix timestamp (in seconds) of when the chat completion was created.
The model used for the chat completion.
The service tier used for processing the request.
Allowed values:scaledefault
Example:scale
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.
The object type, which is always chat.completion.
Allowed values:chat.completion
Usage statistics for the completion request.
Show Child Parameters
CreateChatCompletionStreamResponse
objectRepresents a streamed chunk of a chat completion response returned by model, based on the provided input.
A unique identifier for the chat completion. Each chunk has the same ID.
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}.
Show Child Parameters
The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same timestamp.
The model to generate the completion.
The service tier used for processing the request.
Allowed values:scaledefault
Example:scale
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.
The object type, which is always chat.completion.chunk.
Allowed values:chat.completion.chunk
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.
Show Child Parameters
CreateCompletionRequest
objectAny OfID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.
One OfThe prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays.
Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document.
Default:<|endoftext|>
Default:
Example:This is a test.
Generates best_of completions server-side and returns the “best” (the one with the highest log probability per token). Results cannot be streamed.
When used with n, best_of controls the number of candidate completions and n specifies how many to return – best_of must be greater than n.
Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop.
Default:1
>= 0<= 20
Echo back the prompt in addition to the completion
Default:false
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.
See more information about frequency and presence penalties.
Default:0
>= -2<= 2
Modify the likelihood of specified tokens appearing in the completion.
Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this tokenizer tool to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
As an example, you can pass {"50256": -100} to prevent the <|endoftext|> token from being generated.
Default:null
Include the log probabilities on the logprobs most likely output tokens, as well the chosen tokens. For example, if logprobs is 5, the API will return a list of the 5 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response.
The maximum value for logprobs is 5.
Default:null
>= 0<= 5
The maximum number of tokens that can be generated in the completion.
The token count of your prompt plus max_tokens cannot exceed the model’s context length. Example Python code for counting tokens.
Default:16
>= 0
Example:16
How many completions to generate for each prompt.
Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop.
Default:1
>= 1<= 128
Example:1
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.
See more information about frequency and presence penalties.
Default:0
>= -2<= 2
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.
One OfUp to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
Default:null
Default:<|endoftext|>
Example:
Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message. Example Python code.
Default:false
Options for streaming response. Only set this when you set stream: true.
Default:null
Show Child Parameters
The suffix that comes after a completion of inserted text.
This parameter is only supported for gpt-3.5-turbo-instruct.
Default:null
Example:test.
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.
Default:1
>= 0<= 2
Example:1
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.
Default:1
>= 0<= 1
Example:1
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
Example:user-1234
CreateCompletionResponse
objectRepresents a completion response from the API. Note: both the streamed and non-streamed response objects share the same shape (unlike the chat endpoint).
A unique identifier for the completion.
The list of completion choices the model generated for the input prompt.
Show Child Parameters
The Unix timestamp (in seconds) of when the completion was created.
The model used for completion.
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.
The object type, which is always “text_completion”
Allowed values:text_completion
Usage statistics for the completion request.