Interface CreateChatCompletionRequest

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CreateChatCompletionRequest

Hierarchy

  • CreateChatCompletionRequest

Properties

frequency_penalty? function_call? functions? logit_bias? max_tokens? messages model n? presence_penalty? stop? stream? temperature? top_p? user?

Properties

Optional frequency_penalty

frequency_penalty?: null | 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. See more information about frequency and presence penalties.

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CreateChatCompletionRequest

Optional function_call

function_call?: CreateChatCompletionRequestFunctionCall

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CreateChatCompletionRequest

Optional functions

functions?: ChatCompletionFunctions[]

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

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CreateChatCompletionRequest

Optional logit_bias

logit_bias?: null | object

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.

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CreateChatCompletionRequest

Optional max_tokens

max_tokens?: number

The maximum number of tokens to generate in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length. Example Python code for counting tokens.

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CreateChatCompletionRequest

messages

messages: ChatCompletionRequestMessage[]

A list of messages comprising the conversation so far. Example Python code.

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CreateChatCompletionRequest

model

model: string

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

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CreateChatCompletionRequest

Optional n

n?: null | number

How many chat completion choices to generate for each input message.

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CreateChatCompletionRequest

Optional presence_penalty

presence_penalty?: null | 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. See more information about frequency and presence penalties.

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CreateChatCompletionRequest

Optional stop

stop?: CreateChatCompletionRequestStop

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CreateChatCompletionRequest

Optional stream

stream?: null | boolean

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.

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CreateChatCompletionRequest

Optional temperature

temperature?: null | 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.

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CreateChatCompletionRequest

Optional top_p

top_p?: null | 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.

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CreateChatCompletionRequest

Optional user

user?: string

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.

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CreateChatCompletionRequest

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