OpenAI

Chat Completion

Creates a model response for the given chat conversation.

Inputs

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Field

Type

Description

model

string

The model name for processing. Defaults to gpt-3.5-turbo.

default: gpt-3.5-turbo

messages [required]

[object]

An array of messages with role and content properties.

role [required]

enum

The role of the author of this message. Allowed enum values: system,user,assistant

content [required]

string

The contents of the message

name

string

The name of the user in a multi-user chat

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. It is generally recommended to alter either the Temperature or Top-P, but not both.

default: 1

topP

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. It is generally recommended to alter either the Temperature or Top-P, but not both.

default: 1

maxTokens

number

The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.

frequencyPenalty

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.

presencePenalty

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.

logitBias

object

Modify the likelihood of specified tokens appearing in the completion. Accepts an 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 mode 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.

Outputs

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Field

Type

Description

message

object

role [required]

enum

The role of the author of this message. Allowed enum values: system,user,assistant

content [required]

string

The contents of the message