Class ChatRequest.Builder
java.lang.Object
io.github.stefanbratanov.jvm.openai.ChatRequest.Builder
- Enclosing class:
- ChatRequest
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionbuild()
frequencyPenalty
(double frequencyPenalty) logprobs
(boolean logprobs) maxTokens
(int maxTokens) message
(ChatMessage message) messages
(List<ChatMessage> messages) n
(int n) presencePenalty
(double presencePenalty) responseFormat
(ChatRequest.ResponseFormat responseFormat) Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message.seed
(int seed) stream
(boolean stream) temperature
(double temperature) toolChoice
(ToolChoice toolChoice) toolChoice
(String toolChoice) topLogprobs
(int topLogprobs) topP
(double topP)
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Constructor Details
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Builder
public Builder()
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Method Details
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model
- Parameters:
model
- ID of the model to use
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message
- Parameters:
message
- message to append to the list of messages comprising the conversation so far
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messages
- Parameters:
messages
- messages to append to the list of messages comprising the conversation so far
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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.
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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.
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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.
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topLogprobs
- Parameters:
topLogprobs
- An integer between 0 and 5 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.
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maxTokens
- Parameters:
maxTokens
- The total length of input tokens and generated tokens is limited by the model's context length
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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.
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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.
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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.
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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.
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stop
- Parameters:
stop
- Up to 4 sequences where the API will stop generating further tokens.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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user
- Parameters:
user
- A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
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build
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