SUsudoapp
router

Create a model response for the given string of prompts.

post/v1/chat/completions

Request

  • Base URL
    https://docs.sudoapp.dev (the document declares no server; this is the origin it was published from)
  • Auth
    HTTP bearer

Request body

frequency_penaltynumber float nullable

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_biasobject nullable

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.

logprobsboolean nullable

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.

max_completion_tokensinteger nullable

An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.

metadataobject nullable

Developer-defined tags and values used for filtering completions in the stored completions dashboard.

modalitiesstring[] nullable

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"].

modelstring required

Model name used to generate the response, like gpt-4o or deepseek-reasoner. Sudo offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the docs to browse and compare available models.

ninteger nullable

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.

parallel_tool_callsboolean nullable

Whether to enable parallel function calling during tool use.

presence_penaltynumber float nullable

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.

prompt_cache_keystring nullable

A unique identifier for caching prompts to improve response times for repeated requests.

reasoning_effort'low' | 'medium' | 'high' nullable

o1 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.

seedinteger nullable

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 isn't guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.

service_tier'auto' | 'default' nullable

Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service.

stopstring[] nullable

Not supported with latest reasoning models o3 and o4-mini. Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

storeboolean nullable

Whether or not to store the output of this chat completion request for use in our model distillation or evaluation products.

streamfalse

If set, partial message deltas will be sent, like in ChatGPT. For JSON responses, this must be false.

temperaturenumber float nullable

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_logprobsinteger nullable

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.

top_pnumber float nullable

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

Chat completion created successfully

createdinteger required
idstring required
modelstring required
objectstring required
service_tierstring nullable
system_fingerprintstring nullable
metadataobject nullable

Developer-defined metadata attached to the completion.

Changes

No recorded changes to this operation across all 1 revision of this API.