@aws-cdk/aws-bedrock-alpha.InferenceConfiguration

Experimental

@aws-cdk/aws-bedrock-alpha is an experimental (alpha) package: its API may change in any release, without a major version bump.

InferenceConfiguration Struct

LLM inference configuration.

Stability

Experimental

Source

bedrock/agents/prompt-override.ts

Example

const agent = new bedrock.Agent(this, 'Agent', {
  foundationModel: bedrock.BedrockFoundationModel.AMAZON_NOVA_LITE_V1,
  instruction: 'You are a helpful assistant.',
  promptOverrideConfiguration: bedrock.PromptOverrideConfiguration.fromSteps([
    {
      stepType: bedrock.AgentStepType.PRE_PROCESSING,
      stepEnabled: true,
      customPromptTemplate: 'Your custom prompt template here',
      inferenceConfig: {
        temperature: 0.0,
        topP: 1,
        topK: 250,
        maximumLength: 1,
        stopSequences: ["\n\nHuman:"],
      },
    }
  ])
});

Properties

maximumLengthnumbermaximum_lengthint | floatmaximumLengthNumberMaximumLengthdoubleMaximumLength*float64required#

The maximum number of tokens to generate in the response.

Integer

min 0 max 4096

stopSequencesstring[]stop_sequencestyping.List[str]stopSequencesList<String>StopSequencesstring[]StopSequences*[]*stringrequired#

A list of stop sequences.

A stop sequence is a sequence of characters that causes the model to stop generating the response.

length 0-4

temperaturenumbertemperatureint | floattemperatureNumberTemperaturedoubleTemperature*float64required#

The likelihood of the model selecting higher-probability options while generating a response.

A lower value makes the model more likely to choose higher-probability options, while a higher value makes the model more likely to choose lower-probability options.

Floating point

min 0 max 1

topKnumbertop_kint | floattopKNumberTopKdoubleTopK*float64required#

While generating a response, the model determines the probability of the following token at each point of generation.

notes

The value that you set for topK is the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you set topK to 50, the model selects the next token from among the top 50 most likely choices.

Integer

min 0 max 500

topPnumbertop_pint | floattopPNumberTopPdoubleTopP*float64required#

While generating a response, the model determines the probability of the following token at each point of generation.

notes

The value that you set for Top P determines the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you set topP to 80, the model only selects the next token from the top 80% of the probability distribution of next tokens.

Floating point

min 0 max 1