class Live extends Chat
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- def createChatCompletion(body: CreateChatCompletionRequest): ZIO[Any, OpenAIFailure, CreateChatCompletionResponse]
Creates a model response for the given chat conversation.
- def createChatCompletion(messages: NonEmptyChunk[ChatCompletionRequestMessage], model: Model, frequencyPenalty: Optional[FrequencyPenalty] = Optional.Absent, functionCall: Optional[FunctionCall] = Optional.Absent, functions: Optional[NonEmptyChunk[ChatCompletionFunctions]] = Optional.Absent, logitBias: Optional[LogitBias] = Optional.Absent, maxTokens: Optional[Int] = Optional.Absent, n: Optional[N] = Optional.Absent, presencePenalty: Optional[PresencePenalty] = Optional.Absent, stop: Optional[Stop] = Optional.Absent, temperature: Optional[Temperature] = Optional.Absent, topP: Optional[TopP] = Optional.Absent, user: Optional[String] = Optional.Absent): ZIO[Any, OpenAIFailure, CreateChatCompletionResponse]
Creates a model response for the given chat conversation.
Creates a model response for the given chat conversation.
- messages
A list of messages comprising the conversation so far. [Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
- model
ID of the model to use. See the [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table for details on which models work with the Chat API.
- 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.](/docs/guides/gpt/parameter-details)
- functionCall
Controls how the model calls functions. "none" means the model will not call a function and instead generates a message. "auto" means the model can pick between generating a message or calling a function. Specifying a particular function via
{"name": "my_function"}forces the model to call that function. "none" is the default when no functions are present. "auto" is the default if functions are present.- functions
A list of functions the model may generate JSON inputs for.
- 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.
- maxTokens
The maximum number of [tokens](/tokenizer) 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](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
- n
How many chat completion choices to generate for each input message.
- 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.](/docs/guides/gpt/parameter-details)
- stop
Up to 4 sequences where the API will stop generating further tokens.
- 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_pbut 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
temperaturebut not both.- user
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).
- Definition Classes
- Chat
- def createChatCompletionStreaming(body: CreateChatCompletionRequest): ZStream[Any, OpenAIFailure, CreateChatCompletionStreamResponse]
- def createChatCompletionStreaming(messages: NonEmptyChunk[ChatCompletionRequestMessage], model: Model, frequencyPenalty: Optional[FrequencyPenalty] = Optional.Absent, functionCall: Optional[FunctionCall] = Optional.Absent, functions: Optional[NonEmptyChunk[ChatCompletionFunctions]] = Optional.Absent, logitBias: Optional[LogitBias] = Optional.Absent, maxTokens: Optional[Int] = Optional.Absent, n: Optional[N] = Optional.Absent, presencePenalty: Optional[PresencePenalty] = Optional.Absent, stop: Optional[Stop] = Optional.Absent, temperature: Optional[Temperature] = Optional.Absent, topP: Optional[TopP] = Optional.Absent, user: Optional[String] = Optional.Absent): ZStream[Any, OpenAIFailure, CreateChatCompletionStreamResponse]
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