Authorizations
Bearer authentication header of the form Bearer <token>
, where <token>
is your auth token.
Body
Model ID used to generate the response, like gpt-4o
or o3
. OpenAI
offers a wide range of models with different capabilities, performance
characteristics, and price points. Refer to the model guide
to browse and compare available models.
"gpt-4o"
Output types that you would like the model to generate. 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"]
o-series 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.
low
, medium
, high
An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.
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.
-2 <= x <= 2
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.
-2 <= x <= 2
This tool searches the web for relevant results to use in a response. Learn more about the web search tool.
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 <= x <= 20
An 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 the older JSON mode, which
ensures the message the model generates is valid JSON. Using json_schema
is preferred for models that support it.
Default response format. Used to generate text responses.
Parameters for audio output. Required when audio output is requested with
modalities: ["audio"]
. Learn more.
Whether or not to store the output of this chat completion request for use in our model distillation or evals products.
If set to true, the model response data will be streamed to the client as it is generated using server-sent events. See the Streaming section below for more information, along with the streaming responses guide for more information on how to handle the streaming events.
Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
"\n"
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.
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
.
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 o-series models.
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.
1 <= x <= 128
1
Configuration 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.
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.
-9223372036854776000 <= x <= 9223372036854776000
Options for streaming response. Only set this when you set stream: true
.
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.
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.
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.
none
, auto
, required
Whether to enable parallel function calling during tool use.
Deprecated 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.
none
, auto
Deprecated in favor of tools
.
A list of functions the model may generate JSON inputs for.
1 - 128
elementsSet 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.
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.
0 <= x <= 2
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.
0 <= x <= 1
1
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
"user-1234"
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 guarentee.
- If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee.
- If set to 'economy', the request will be processed with the Economy service tier at the specified price. Economy requests have longer response times and may experience Resource Unavailable errors. See the docs for more information.
- When not set, the default behavior is 'auto'.
When this parameter is set, the response body will include the service_tier
utilized.
auto
, default
, economy
Response
OK
Represents 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.
The Unix timestamp (in seconds) of when the chat completion was created.
The model used for the chat completion.
The object type, which is always chat.completion
.
chat.completion
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 guarentee.
- If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee.
- If set to 'economy', the request will be processed with the Economy service tier at the specified price. Economy requests have longer response times and may experience Resource Unavailable errors. See the docs for more information.
- When not set, the default behavior is 'auto'.
When this parameter is set, the response body will include the service_tier
utilized.
auto
, default
, economy
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 statistics for the completion request.