Get Chat Completions

Creates a model response for the given chat conversation.

POST https://withmartian/api/openai/v1/chat/completions

Request Body

NameTypeDescription

model*

string, List[string]

ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.

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.

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.

messages*

array

A list of messages comprising the conversation so far.

max_tokens

number

The maximum number of tokens to generate in the chat completion.

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.

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.

user

string

NOT SUPPORTED

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

logit_bias

map

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.

response_format

object

An object specifying the format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106.

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.

seed

null, integer

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, array, null

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

stream

boolean, 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

tools

array

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.

tool_choice

string or object

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 {"type": "function", "function": {"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.

functions

array

Deprecated - A list of functions the model may generate JSON inputs for.

function_call

string or object

Deprecated - 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.

extra_body

List[object]

Sets metadata on the requests via a list of objects of form "object_name" : { "field_a" : "value_a", "field_b" : "value_b"}, which can be used to tune the router. For more information, reach out to contact@withmartian.com. Note: need to pass data in extra field Example:

extra_body={
    "extra": {
        "ip": "123.123.123.123",
        "Timezone": "UTC+0",
        "Country": "US",
        "City": "New York",
    }
},

Last updated