io.github.cdklabs.generative_ai_cdk_constructs.bedrock.InferenceConfiguration Maven / Gradle / Ivy
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package io.github.cdklabs.generative_ai_cdk_constructs.bedrock;
/**
* (experimental) LLM inference configuration.
*/
@javax.annotation.Generated(value = "jsii-pacmak/1.103.1 (build bef2dea)", date = "2024-10-01T15:41:28.751Z")
@software.amazon.jsii.Jsii(module = io.github.cdklabs.generative_ai_cdk_constructs.$Module.class, fqn = "@cdklabs/generative-ai-cdk-constructs.bedrock.InferenceConfiguration")
@software.amazon.jsii.Jsii.Proxy(InferenceConfiguration.Jsii$Proxy.class)
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public interface InferenceConfiguration extends software.amazon.jsii.JsiiSerializable {
/**
* (experimental) The maximum number of tokens to generate in the response.
*
* Integer
*
* min 0
* max 4096
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@org.jetbrains.annotations.NotNull java.lang.Number getMaximumLength();
/**
* (experimental) 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
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@org.jetbrains.annotations.NotNull java.util.List getStopSequences();
/**
* (experimental) 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
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@org.jetbrains.annotations.NotNull java.lang.Number getTemperature();
/**
* (experimental) While generating a response, the model determines the probability of the following token at each point of generation.
*
* 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
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@org.jetbrains.annotations.NotNull java.lang.Number getTopK();
/**
* (experimental) While generating a response, the model determines the probability of the following token at each point of generation.
*
* 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
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@org.jetbrains.annotations.NotNull java.lang.Number getTopP();
/**
* @return a {@link Builder} of {@link InferenceConfiguration}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
static Builder builder() {
return new Builder();
}
/**
* A builder for {@link InferenceConfiguration}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public static final class Builder implements software.amazon.jsii.Builder {
java.lang.Number maximumLength;
java.util.List stopSequences;
java.lang.Number temperature;
java.lang.Number topK;
java.lang.Number topP;
/**
* Sets the value of {@link InferenceConfiguration#getMaximumLength}
* @param maximumLength The maximum number of tokens to generate in the response. This parameter is required.
* Integer
*
* min 0
* max 4096
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder maximumLength(java.lang.Number maximumLength) {
this.maximumLength = maximumLength;
return this;
}
/**
* Sets the value of {@link InferenceConfiguration#getStopSequences}
* @param stopSequences A list of stop sequences. This parameter is required.
* A stop sequence is a sequence of characters that
* causes the model to stop generating the response.
*
* length 0-4
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder stopSequences(java.util.List stopSequences) {
this.stopSequences = stopSequences;
return this;
}
/**
* Sets the value of {@link InferenceConfiguration#getTemperature}
* @param temperature The likelihood of the model selecting higher-probability options while generating a response. This parameter is required.
* 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
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder temperature(java.lang.Number temperature) {
this.temperature = temperature;
return this;
}
/**
* Sets the value of {@link InferenceConfiguration#getTopK}
* @param topK While generating a response, the model determines the probability of the following token at each point of generation. This parameter is required.
* 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
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder topK(java.lang.Number topK) {
this.topK = topK;
return this;
}
/**
* Sets the value of {@link InferenceConfiguration#getTopP}
* @param topP While generating a response, the model determines the probability of the following token at each point of generation. This parameter is required.
* 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
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder topP(java.lang.Number topP) {
this.topP = topP;
return this;
}
/**
* Builds the configured instance.
* @return a new instance of {@link InferenceConfiguration}
* @throws NullPointerException if any required attribute was not provided
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@Override
public InferenceConfiguration build() {
return new Jsii$Proxy(this);
}
}
/**
* An implementation for {@link InferenceConfiguration}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@software.amazon.jsii.Internal
final class Jsii$Proxy extends software.amazon.jsii.JsiiObject implements InferenceConfiguration {
private final java.lang.Number maximumLength;
private final java.util.List stopSequences;
private final java.lang.Number temperature;
private final java.lang.Number topK;
private final java.lang.Number topP;
/**
* Constructor that initializes the object based on values retrieved from the JsiiObject.
* @param objRef Reference to the JSII managed object.
*/
protected Jsii$Proxy(final software.amazon.jsii.JsiiObjectRef objRef) {
super(objRef);
this.maximumLength = software.amazon.jsii.Kernel.get(this, "maximumLength", software.amazon.jsii.NativeType.forClass(java.lang.Number.class));
this.stopSequences = software.amazon.jsii.Kernel.get(this, "stopSequences", software.amazon.jsii.NativeType.listOf(software.amazon.jsii.NativeType.forClass(java.lang.String.class)));
this.temperature = software.amazon.jsii.Kernel.get(this, "temperature", software.amazon.jsii.NativeType.forClass(java.lang.Number.class));
this.topK = software.amazon.jsii.Kernel.get(this, "topK", software.amazon.jsii.NativeType.forClass(java.lang.Number.class));
this.topP = software.amazon.jsii.Kernel.get(this, "topP", software.amazon.jsii.NativeType.forClass(java.lang.Number.class));
}
/**
* Constructor that initializes the object based on literal property values passed by the {@link Builder}.
*/
protected Jsii$Proxy(final Builder builder) {
super(software.amazon.jsii.JsiiObject.InitializationMode.JSII);
this.maximumLength = java.util.Objects.requireNonNull(builder.maximumLength, "maximumLength is required");
this.stopSequences = java.util.Objects.requireNonNull(builder.stopSequences, "stopSequences is required");
this.temperature = java.util.Objects.requireNonNull(builder.temperature, "temperature is required");
this.topK = java.util.Objects.requireNonNull(builder.topK, "topK is required");
this.topP = java.util.Objects.requireNonNull(builder.topP, "topP is required");
}
@Override
public final java.lang.Number getMaximumLength() {
return this.maximumLength;
}
@Override
public final java.util.List getStopSequences() {
return this.stopSequences;
}
@Override
public final java.lang.Number getTemperature() {
return this.temperature;
}
@Override
public final java.lang.Number getTopK() {
return this.topK;
}
@Override
public final java.lang.Number getTopP() {
return this.topP;
}
@Override
@software.amazon.jsii.Internal
public com.fasterxml.jackson.databind.JsonNode $jsii$toJson() {
final com.fasterxml.jackson.databind.ObjectMapper om = software.amazon.jsii.JsiiObjectMapper.INSTANCE;
final com.fasterxml.jackson.databind.node.ObjectNode data = com.fasterxml.jackson.databind.node.JsonNodeFactory.instance.objectNode();
data.set("maximumLength", om.valueToTree(this.getMaximumLength()));
data.set("stopSequences", om.valueToTree(this.getStopSequences()));
data.set("temperature", om.valueToTree(this.getTemperature()));
data.set("topK", om.valueToTree(this.getTopK()));
data.set("topP", om.valueToTree(this.getTopP()));
final com.fasterxml.jackson.databind.node.ObjectNode struct = com.fasterxml.jackson.databind.node.JsonNodeFactory.instance.objectNode();
struct.set("fqn", om.valueToTree("@cdklabs/generative-ai-cdk-constructs.bedrock.InferenceConfiguration"));
struct.set("data", data);
final com.fasterxml.jackson.databind.node.ObjectNode obj = com.fasterxml.jackson.databind.node.JsonNodeFactory.instance.objectNode();
obj.set("$jsii.struct", struct);
return obj;
}
@Override
public final boolean equals(final Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
InferenceConfiguration.Jsii$Proxy that = (InferenceConfiguration.Jsii$Proxy) o;
if (!maximumLength.equals(that.maximumLength)) return false;
if (!stopSequences.equals(that.stopSequences)) return false;
if (!temperature.equals(that.temperature)) return false;
if (!topK.equals(that.topK)) return false;
return this.topP.equals(that.topP);
}
@Override
public final int hashCode() {
int result = this.maximumLength.hashCode();
result = 31 * result + (this.stopSequences.hashCode());
result = 31 * result + (this.temperature.hashCode());
result = 31 * result + (this.topK.hashCode());
result = 31 * result + (this.topP.hashCode());
return result;
}
}
}