Package io.github.stefanbratanov.jvm.openai

Class CreateChatCompletionRequest.Builder

java.lang.Object
io.github.stefanbratanov.jvm.openai.CreateChatCompletionRequest.Builder
Enclosing class:
CreateChatCompletionRequest
public static class CreateChatCompletionRequest.Builder extends Object

  • Constructor Details

    • Builder

      public Builder()

  • Method Details

    • message

      public CreateChatCompletionRequest.Builder message(ChatMessage message)
      Parameters:
      message - message to append to the list of messages comprising the conversation so far

    • messages

      public CreateChatCompletionRequest.Builder messages(List<ChatMessage> messages)
      Parameters:
      messages - messages to append to the list of messages comprising the conversation so far

    • model

      public CreateChatCompletionRequest.Builder model(String model)
      Parameters:
      model - ID of the model to use

    • model

      public CreateChatCompletionRequest.Builder model(OpenAIModel model)
      Parameters:
      model - OpenAIModel to use

    • frequencyPenalty

      public CreateChatCompletionRequest.Builder frequencyPenalty(double frequencyPenalty)
      Parameters:
      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.

    • logitBias

      public CreateChatCompletionRequest.Builder logitBias(Map<Integer,Integer> logitBias)
      Parameters:
      logitBias - A map 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.

    • logprobs

      public CreateChatCompletionRequest.Builder logprobs(boolean logprobs)
      Parameters:
      logprobs - Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.

    • topLogprobs

      public CreateChatCompletionRequest.Builder topLogprobs(int topLogprobs)
      Parameters:
      topLogprobs - An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to `true` if this parameter is used.

    • maxTokens

      public CreateChatCompletionRequest.Builder maxTokens(int maxTokens)
      Parameters:
      maxTokens - The total length of input tokens and generated tokens is limited by the model's context length

    • n

      public CreateChatCompletionRequest.Builder n(int n)
      Parameters:
      n - How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.

    • presencePenalty

      public CreateChatCompletionRequest.Builder presencePenalty(double presencePenalty)
      Parameters:
      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.

    • responseFormat

      public CreateChatCompletionRequest.Builder responseFormat(CreateChatCompletionRequest.ResponseFormat responseFormat)
      Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message.
      Parameters:
      responseFormat - An object specifying the format that the model must output.

    • seed

      public CreateChatCompletionRequest.Builder seed(int seed)
      Parameters:
      seed - If specified, the system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.

    • stop

      public CreateChatCompletionRequest.Builder stop(String... stop)
      Parameters:
      stop - Up to 4 sequences where the API will stop generating further tokens.

    • stream

      public CreateChatCompletionRequest.Builder stream(boolean stream)
      Parameters:
      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.

    • temperature

      public CreateChatCompletionRequest.Builder temperature(double temperature)
      Parameters:
      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.

    • topP

      public CreateChatCompletionRequest.Builder topP(double topP)
      Parameters:
      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.

    • tool

      public CreateChatCompletionRequest.Builder tool(Tool tool)
      Parameters:
      tool - tool to append to the list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for.

    • tools

      public CreateChatCompletionRequest.Builder tools(List<Tool> tools)
      Parameters:
      tools - tools to append to the list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for.

    • toolChoice

      public CreateChatCompletionRequest.Builder toolChoice(String toolChoice)
      Parameters:
      toolChoice - Controls which (if any) function is called by the model. 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 {"type": "function", "function": {"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.

    • toolChoice

      public CreateChatCompletionRequest.Builder toolChoice(ToolChoice toolChoice)
      Parameters:
      toolChoice - Controls which (if any) function is called by the model. 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 {"type": "function", "function": {"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.

    • user

      public CreateChatCompletionRequest.Builder user(String user)
      Parameters:
      user - A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.

    • build

      public CreateChatCompletionRequest build()