ChatRequestBody

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.

Modify the likelihood of specified tokens appearing in the completion.

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

A list of messages describing the conversation so far.

ID of the model to use.

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

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.

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

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.

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.

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