class

LLM::CLI::OpenAI::CreateChatCompletion

Inherits JSON::Serializable / Reference / Object

POST https://api.openai.com/v1/chat/completions

Constructors

new(model : String, messages : Array(LLM::CLI::Chat::Message))
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new(pull : JSON::PullParser)
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new(*, __pull_for_json_serializable pull : JSON::PullParser)
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Instance methods

frequency_penalty

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.

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frequency_penalty=(frequency_penalty : Float64)

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.

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logit_bias

Modify the likelihood of specified tokens appearing in the completion. You can use this tokenizer tool (which works for both GPT-2 and GPT-3) to convert text to token IDs

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logit_bias=(logit_bias : Hash(String, Float64) | Nil)

Modify the likelihood of specified tokens appearing in the completion. You can use this tokenizer tool (which works for both GPT-2 and GPT-3) to convert text to token IDs

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messages
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messages=(messages : Array(Chat::Message))
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model

the model id

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model=(model : String)

the model id

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num_completions

How many completions to generate for each prompt.

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num_completions=(num_completions : Int32)

How many completions to generate for each prompt.

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presence_penalty

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.

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presence_penalty=(presence_penalty : Float64)

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.

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stop

Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

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stop=(stop : String | Array(String) | Nil)

Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

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stream

Whether to stream back partial progress.

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stream=(stream : Bool)

Whether to stream back partial progress.

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temperature

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.

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temperature=(temperature : Float64)

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.

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top_p

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. Alter this or temperature but not both.

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top_p=(top_p : Float64)

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. Alter this or temperature but not both.

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user

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

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user=(user : String | Nil)

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

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