Package software.amazon.awssdk.services.bedrockagentruntime.model

Interface TextInferenceConfig.Builder

All Superinterfaces:

Buildable, CopyableBuilder<TextInferenceConfig.Builder,TextInferenceConfig>, SdkBuilder<TextInferenceConfig.Builder,TextInferenceConfig>, SdkPojo

Enclosing class:

TextInferenceConfig

@Mutable
@NotThreadSafe
public static interface TextInferenceConfig.Builder
extends SdkPojo, CopyableBuilder<TextInferenceConfig.Builder,TextInferenceConfig>

Method Summary

Modifier and Type	Method	Description
TextInferenceConfig.Builder	maxTokens(Integer maxTokens)	The maximum number of tokens to generate in the output text.
TextInferenceConfig.Builder	stopSequences(String... stopSequences)	A list of sequences of characters that, if generated, will cause the model to stop generating further tokens.
TextInferenceConfig.Builder	stopSequences(Collection<String> stopSequences)	A list of sequences of characters that, if generated, will cause the model to stop generating further tokens.
TextInferenceConfig.Builder	temperature(Float temperature)	Controls the random-ness of text generated by the language model, influencing how much the model sticks to the most predictable next words versus exploring more surprising options.
TextInferenceConfig.Builder	topP(Float topP)	A probability distribution threshold which controls what the model considers for the set of possible next tokens.

Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder

copy

Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder

applyMutation, build

Methods inherited from interface software.amazon.awssdk.core.SdkPojo

equalsBySdkFields, sdkFieldNameToField, sdkFields

Method Detail

maxTokens

TextInferenceConfig.Builder maxTokens(Integer maxTokens)

The maximum number of tokens to generate in the output text. Do not use the minimum of 0 or the maximum of 65536. The limit values described here are arbitary values, for actual values consult the limits defined by your specific model.

Parameters:

maxTokens - The maximum number of tokens to generate in the output text. Do not use the minimum of 0 or the maximum of 65536. The limit values described here are arbitary values, for actual values consult the limits defined by your specific model.

Returns:

Returns a reference to this object so that method calls can be chained together.

stopSequences

TextInferenceConfig.Builder stopSequences(Collection<String> stopSequences)

A list of sequences of characters that, if generated, will cause the model to stop generating further tokens. Do not use a minimum length of 1 or a maximum length of 1000. The limit values described here are arbitary values, for actual values consult the limits defined by your specific model.

Parameters:

stopSequences - A list of sequences of characters that, if generated, will cause the model to stop generating further tokens. Do not use a minimum length of 1 or a maximum length of 1000. The limit values described here are arbitary values, for actual values consult the limits defined by your specific model.

Returns:

Returns a reference to this object so that method calls can be chained together.

stopSequences

TextInferenceConfig.Builder stopSequences(String... stopSequences)

A list of sequences of characters that, if generated, will cause the model to stop generating further tokens. Do not use a minimum length of 1 or a maximum length of 1000. The limit values described here are arbitary values, for actual values consult the limits defined by your specific model.

Parameters:

stopSequences - A list of sequences of characters that, if generated, will cause the model to stop generating further tokens. Do not use a minimum length of 1 or a maximum length of 1000. The limit values described here are arbitary values, for actual values consult the limits defined by your specific model.

Returns:

Returns a reference to this object so that method calls can be chained together.

temperature

TextInferenceConfig.Builder temperature(Float temperature)

Controls the random-ness of text generated by the language model, influencing how much the model sticks to the most predictable next words versus exploring more surprising options. A lower temperature value (e.g. 0.2 or 0.3) makes model outputs more deterministic or predictable, while a higher temperature (e.g. 0.8 or 0.9) makes the outputs more creative or unpredictable.

Parameters:

temperature - Controls the random-ness of text generated by the language model, influencing how much the model sticks to the most predictable next words versus exploring more surprising options. A lower temperature value (e.g. 0.2 or 0.3) makes model outputs more deterministic or predictable, while a higher temperature (e.g. 0.8 or 0.9) makes the outputs more creative or unpredictable.

Returns:

Returns a reference to this object so that method calls can be chained together.

topP

TextInferenceConfig.Builder topP(Float topP)

A probability distribution threshold which controls what the model considers for the set of possible next tokens. The model will only consider the top p% of the probability distribution when generating the next token.

Parameters:

topP - A probability distribution threshold which controls what the model considers for the set of possible next tokens. The model will only consider the top p% of the probability distribution when generating the next token.

Returns:

Returns a reference to this object so that method calls can be chained together.