v13

latestOpenAPI 3.1.0MITraw.githubusercontent.com2026-08-0148123138.3 KB

Chat

Chat Completions

Creates a model response for the given chat conversation.

post/v1/chat/completions

Request body

modelstring required

ID of the model to use. Call /v1/models endpoint to get the list of available models, only text-generation model type is supported.

frequency_penaltynumber 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.

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.

presence_penaltynumber 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.

max_completion_tokensinteger nullable

An upper bound for the number of tokens that can be generated for a completion.

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.

{"stackTrail":"components:schemas:CreateChatCompletion:properties:response_format:anyOf","oasType":"schema","type":"unknown","title":"Response Format","description":"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.<br>**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.","nullable":true}

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 is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.

streamtrue | false nullable

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.

{"stackTrail":"components:schemas:CreateChatCompletion:properties:stream_options:anyOf","oasType":"schema","type":"unknown","title":"Stream Options","description":"Options for streaming response. Only set this when you set `stream: true`.","nullable":true}

temperaturenumber 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_pnumber 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.<br>We generally recommend altering this or temperature but not both.

toolsobject[] nullable

tool_choicestring

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.<br>none is the default when no tools are present. auto is the default if tools are present.

parallel_tool_callsboolean nullable

Whether to call tools in parallel or sequentially. If true, the model will call tools in parallel. If false, the model will call tools sequentially. If None, the model will call tools in parallel if the model supports it, otherwise it will call tools sequentially.

userstring nullable

A unique identifier representing the user.

Response

Successful Response