CreateChatCompletionRequest class abstract

CreateChatCompletionRequest

Properties:

  • model - ID of the model to use. Currently, only gpt-3.5-turbo and gpt-3.5-turbo-0301 are supported.
  • messages - The messages to generate chat completions for, in the chat format.
  • 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. We generally recommend altering this or top_p but not both.
  • topP - 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.
  • n - How many chat completion choices to generate for each input message.
  • stream - 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.
  • stop
  • maxTokens - The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens).
  • presencePenalty - 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.
  • frequencyPenalty - 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.
  • logitBias - 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.
  • user - A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
Annotations
  • @BuiltValue()

Constructors

CreateChatCompletionRequest([void updates(CreateChatCompletionRequestBuilder b)])
factory

Properties

frequencyPenalty → num?
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.
no setter
hashCode → int
The hash code for this object.
no setterinherited
logitBias → JsonObject?
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.
no setter
maxTokens → int?
The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens).
no setter
messages → BuiltList<ChatCompletionRequestMessage>
The messages to generate chat completions for, in the chat format.
no setter
model → String
ID of the model to use. Currently, only gpt-3.5-turbo and gpt-3.5-turbo-0301 are supported.
no setter
n → int?
How many chat completion choices to generate for each input message.
no setter
presencePenalty → num?
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.
no setter
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited
stop → CreateChatCompletionRequestStop?
no setter
stream → bool?
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.
no setter
temperature → num?
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.
no setter
topP → num?
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.
no setter
user → String?
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
no setter

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
rebuild(dynamic updates(CreateChatCompletionRequestBuilder)) → CreateChatCompletionRequest
Rebuilds the instance.
inherited
toBuilder() → CreateChatCompletionRequestBuilder
Converts the instance to a builder B.
inherited
toString() → String
A string representation of this object.
inherited

Operators

operator ==(Object other) → bool
The equality operator.
inherited

Static Properties

serializer → Serializer<CreateChatCompletionRequest>
no setter