com.amazonaws.services.bedrockagentruntime.model.KnowledgeBaseVectorSearchConfiguration Maven / Gradle / Ivy
/*
* Copyright 2019-2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with
* the License. A copy of the License is located at
*
* http://aws.amazon.com/apache2.0
*
* or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
* CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
* and limitations under the License.
*/
package com.amazonaws.services.bedrockagentruntime.model;
import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.protocol.StructuredPojo;
import com.amazonaws.protocol.ProtocolMarshaller;
/**
*
* Configurations for how to perform the search query and return results. For more information, see Query configurations.
*
*
* This data type is used in the following API operations:
*
*
* -
*
* Retrieve request – in the vectorSearchConfiguration field
*
*
* -
*
* RetrieveAndGenerate request – in the vectorSearchConfiguration field
*
*
*
*
* @see AWS API Documentation
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class KnowledgeBaseVectorSearchConfiguration implements Serializable, Cloneable, StructuredPojo {
/**
*
* Specifies the filters to use on the metadata in the knowledge base data sources before returning results. For
* more information, see Query
* configurations.
*
*/
private RetrievalFilter filter;
/**
*
* The number of source chunks to retrieve.
*
*/
private Integer numberOfResults;
/**
*
* By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch Serverless
* vector store that contains a filterable text field, you can specify whether to query the knowledge base with a
* HYBRID search using both vector embeddings and raw text, or SEMANTIC search using only
* vector embeddings. For other vector store configurations, only SEMANTIC search is available. For
* more information, see Test a knowledge base.
*
*/
private String overrideSearchType;
/**
*
* Specifies the filters to use on the metadata in the knowledge base data sources before returning results. For
* more information, see Query
* configurations.
*
*
* @param filter
* Specifies the filters to use on the metadata in the knowledge base data sources before returning results.
* For more information, see Query configurations.
*/
public void setFilter(RetrievalFilter filter) {
this.filter = filter;
}
/**
*
* Specifies the filters to use on the metadata in the knowledge base data sources before returning results. For
* more information, see Query
* configurations.
*
*
* @return Specifies the filters to use on the metadata in the knowledge base data sources before returning results.
* For more information, see Query configurations.
*/
public RetrievalFilter getFilter() {
return this.filter;
}
/**
*
* Specifies the filters to use on the metadata in the knowledge base data sources before returning results. For
* more information, see Query
* configurations.
*
*
* @param filter
* Specifies the filters to use on the metadata in the knowledge base data sources before returning results.
* For more information, see Query configurations.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public KnowledgeBaseVectorSearchConfiguration withFilter(RetrievalFilter filter) {
setFilter(filter);
return this;
}
/**
*
* The number of source chunks to retrieve.
*
*
* @param numberOfResults
* The number of source chunks to retrieve.
*/
public void setNumberOfResults(Integer numberOfResults) {
this.numberOfResults = numberOfResults;
}
/**
*
* The number of source chunks to retrieve.
*
*
* @return The number of source chunks to retrieve.
*/
public Integer getNumberOfResults() {
return this.numberOfResults;
}
/**
*
* The number of source chunks to retrieve.
*
*
* @param numberOfResults
* The number of source chunks to retrieve.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public KnowledgeBaseVectorSearchConfiguration withNumberOfResults(Integer numberOfResults) {
setNumberOfResults(numberOfResults);
return this;
}
/**
*
* By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch Serverless
* vector store that contains a filterable text field, you can specify whether to query the knowledge base with a
* HYBRID search using both vector embeddings and raw text, or SEMANTIC search using only
* vector embeddings. For other vector store configurations, only SEMANTIC search is available. For
* more information, see Test a knowledge base.
*
*
* @param overrideSearchType
* By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch
* Serverless vector store that contains a filterable text field, you can specify whether to query the
* knowledge base with a HYBRID search using both vector embeddings and raw text, or
* SEMANTIC search using only vector embeddings. For other vector store configurations, only
* SEMANTIC search is available. For more information, see Test a knowledge
* base.
* @see SearchType
*/
public void setOverrideSearchType(String overrideSearchType) {
this.overrideSearchType = overrideSearchType;
}
/**
*
* By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch Serverless
* vector store that contains a filterable text field, you can specify whether to query the knowledge base with a
* HYBRID search using both vector embeddings and raw text, or SEMANTIC search using only
* vector embeddings. For other vector store configurations, only SEMANTIC search is available. For
* more information, see Test a knowledge base.
*
*
* @return By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch
* Serverless vector store that contains a filterable text field, you can specify whether to query the
* knowledge base with a HYBRID search using both vector embeddings and raw text, or
* SEMANTIC search using only vector embeddings. For other vector store configurations, only
* SEMANTIC search is available. For more information, see Test a knowledge
* base.
* @see SearchType
*/
public String getOverrideSearchType() {
return this.overrideSearchType;
}
/**
*
* By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch Serverless
* vector store that contains a filterable text field, you can specify whether to query the knowledge base with a
* HYBRID search using both vector embeddings and raw text, or SEMANTIC search using only
* vector embeddings. For other vector store configurations, only SEMANTIC search is available. For
* more information, see Test a knowledge base.
*
*
* @param overrideSearchType
* By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch
* Serverless vector store that contains a filterable text field, you can specify whether to query the
* knowledge base with a HYBRID search using both vector embeddings and raw text, or
* SEMANTIC search using only vector embeddings. For other vector store configurations, only
* SEMANTIC search is available. For more information, see Test a knowledge
* base.
* @return Returns a reference to this object so that method calls can be chained together.
* @see SearchType
*/
public KnowledgeBaseVectorSearchConfiguration withOverrideSearchType(String overrideSearchType) {
setOverrideSearchType(overrideSearchType);
return this;
}
/**
*
* By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch Serverless
* vector store that contains a filterable text field, you can specify whether to query the knowledge base with a
* HYBRID search using both vector embeddings and raw text, or SEMANTIC search using only
* vector embeddings. For other vector store configurations, only SEMANTIC search is available. For
* more information, see Test a knowledge base.
*
*
* @param overrideSearchType
* By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch
* Serverless vector store that contains a filterable text field, you can specify whether to query the
* knowledge base with a HYBRID search using both vector embeddings and raw text, or
* SEMANTIC search using only vector embeddings. For other vector store configurations, only
* SEMANTIC search is available. For more information, see Test a knowledge
* base.
* @return Returns a reference to this object so that method calls can be chained together.
* @see SearchType
*/
public KnowledgeBaseVectorSearchConfiguration withOverrideSearchType(SearchType overrideSearchType) {
this.overrideSearchType = overrideSearchType.toString();
return this;
}
/**
* Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be
* redacted from this string using a placeholder value.
*
* @return A string representation of this object.
*
* @see java.lang.Object#toString()
*/
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append("{");
if (getFilter() != null)
sb.append("Filter: ").append("***Sensitive Data Redacted***").append(",");
if (getNumberOfResults() != null)
sb.append("NumberOfResults: ").append(getNumberOfResults()).append(",");
if (getOverrideSearchType() != null)
sb.append("OverrideSearchType: ").append(getOverrideSearchType());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof KnowledgeBaseVectorSearchConfiguration == false)
return false;
KnowledgeBaseVectorSearchConfiguration other = (KnowledgeBaseVectorSearchConfiguration) obj;
if (other.getFilter() == null ^ this.getFilter() == null)
return false;
if (other.getFilter() != null && other.getFilter().equals(this.getFilter()) == false)
return false;
if (other.getNumberOfResults() == null ^ this.getNumberOfResults() == null)
return false;
if (other.getNumberOfResults() != null && other.getNumberOfResults().equals(this.getNumberOfResults()) == false)
return false;
if (other.getOverrideSearchType() == null ^ this.getOverrideSearchType() == null)
return false;
if (other.getOverrideSearchType() != null && other.getOverrideSearchType().equals(this.getOverrideSearchType()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getFilter() == null) ? 0 : getFilter().hashCode());
hashCode = prime * hashCode + ((getNumberOfResults() == null) ? 0 : getNumberOfResults().hashCode());
hashCode = prime * hashCode + ((getOverrideSearchType() == null) ? 0 : getOverrideSearchType().hashCode());
return hashCode;
}
@Override
public KnowledgeBaseVectorSearchConfiguration clone() {
try {
return (KnowledgeBaseVectorSearchConfiguration) super.clone();
} catch (CloneNotSupportedException e) {
throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e);
}
}
@com.amazonaws.annotation.SdkInternalApi
@Override
public void marshall(ProtocolMarshaller protocolMarshaller) {
com.amazonaws.services.bedrockagentruntime.model.transform.KnowledgeBaseVectorSearchConfigurationMarshaller.getInstance().marshall(this,
protocolMarshaller);
}
}