Retrieve And Generate

bedrockagentruntime_retrieve_and_generate

R Documentation

Queries a knowledge base and generates responses based on the retrieved results and using the specified foundation model or inference profile

Description

Queries a knowledge base and generates responses based on the retrieved results and using the specified foundation model or inference profile. The response only cites sources that are relevant to the query.

Usage

bedrockagentruntime_retrieve_and_generate(input,
  retrieveAndGenerateConfiguration, sessionConfiguration, sessionId)

Arguments

input

[required] Contains the query to be made to the knowledge base.

retrieveAndGenerateConfiguration

Contains configurations for the knowledge base query and retrieval process. For more information, see Query configurations.

sessionConfiguration

Contains details about the session with the knowledge base.

sessionId

The unique identifier of the session. When you first make a retrieve_and_generate request, Amazon Bedrock automatically generates this value. You must reuse this value for all subsequent requests in the same conversational session. This value allows Amazon Bedrock to maintain context and knowledge from previous interactions. You can't explicitly set the sessionId yourself.

Value

A list with the following syntax:

list(
  citations = list(
    list(
      generatedResponsePart = list(
        textResponsePart = list(
          span = list(
            end = 123,
            start = 123
          ),
          text = "string"
        )
      ),
      retrievedReferences = list(
        list(
          content = list(
            byteContent = "string",
            row = list(
              list(
                columnName = "string",
                columnValue = "string",
                type = "BLOB"|"BOOLEAN"|"DOUBLE"|"NULL"|"LONG"|"STRING"
              )
            ),
            text = "string",
            type = "TEXT"|"IMAGE"|"ROW"
          ),
          location = list(
            confluenceLocation = list(
              url = "string"
            ),
            customDocumentLocation = list(
              id = "string"
            ),
            kendraDocumentLocation = list(
              uri = "string"
            ),
            s3Location = list(
              uri = "string"
            ),
            salesforceLocation = list(
              url = "string"
            ),
            sharePointLocation = list(
              url = "string"
            ),
            sqlLocation = list(
              query = "string"
            ),
            type = "S3"|"WEB"|"CONFLUENCE"|"SALESFORCE"|"SHAREPOINT"|"CUSTOM"|"KENDRA"|"SQL",
            webLocation = list(
              url = "string"
            )
          ),
          metadata = list(
            list()
          )
        )
      )
    )
  ),
  guardrailAction = "INTERVENED"|"NONE",
  output = list(
    text = "string"
  ),
  sessionId = "string"
)

Request syntax

svc$retrieve_and_generate(
  input = list(
    text = "string"
  ),
  retrieveAndGenerateConfiguration = list(
    externalSourcesConfiguration = list(
      generationConfiguration = list(
        additionalModelRequestFields = list(
          list()
        ),
        guardrailConfiguration = list(
          guardrailId = "string",
          guardrailVersion = "string"
        ),
        inferenceConfig = list(
          textInferenceConfig = list(
            maxTokens = 123,
            stopSequences = list(
              "string"
            ),
            temperature = 123.0,
            topP = 123.0
          )
        ),
        performanceConfig = list(
          latency = "standard"|"optimized"
        ),
        promptTemplate = list(
          textPromptTemplate = "string"
        )
      ),
      modelArn = "string",
      sources = list(
        list(
          byteContent = list(
            contentType = "string",
            data = raw,
            identifier = "string"
          ),
          s3Location = list(
            uri = "string"
          ),
          sourceType = "S3"|"BYTE_CONTENT"
        )
      )
    ),
    knowledgeBaseConfiguration = list(
      generationConfiguration = list(
        additionalModelRequestFields = list(
          list()
        ),
        guardrailConfiguration = list(
          guardrailId = "string",
          guardrailVersion = "string"
        ),
        inferenceConfig = list(
          textInferenceConfig = list(
            maxTokens = 123,
            stopSequences = list(
              "string"
            ),
            temperature = 123.0,
            topP = 123.0
          )
        ),
        performanceConfig = list(
          latency = "standard"|"optimized"
        ),
        promptTemplate = list(
          textPromptTemplate = "string"
        )
      ),
      knowledgeBaseId = "string",
      modelArn = "string",
      orchestrationConfiguration = list(
        additionalModelRequestFields = list(
          list()
        ),
        inferenceConfig = list(
          textInferenceConfig = list(
            maxTokens = 123,
            stopSequences = list(
              "string"
            ),
            temperature = 123.0,
            topP = 123.0
          )
        ),
        performanceConfig = list(
          latency = "standard"|"optimized"
        ),
        promptTemplate = list(
          textPromptTemplate = "string"
        ),
        queryTransformationConfiguration = list(
          type = "QUERY_DECOMPOSITION"
        )
      ),
      retrievalConfiguration = list(
        vectorSearchConfiguration = list(
          filter = list(
            andAll = list(
              list()
            ),
            equals = list(
              key = "string",
              value = list()
            ),
            greaterThan = list(
              key = "string",
              value = list()
            ),
            greaterThanOrEquals = list(
              key = "string",
              value = list()
            ),
            in = list(
              key = "string",
              value = list()
            ),
            lessThan = list(
              key = "string",
              value = list()
            ),
            lessThanOrEquals = list(
              key = "string",
              value = list()
            ),
            listContains = list(
              key = "string",
              value = list()
            ),
            notEquals = list(
              key = "string",
              value = list()
            ),
            notIn = list(
              key = "string",
              value = list()
            ),
            orAll = list(
              list()
            ),
            startsWith = list(
              key = "string",
              value = list()
            ),
            stringContains = list(
              key = "string",
              value = list()
            )
          ),
          implicitFilterConfiguration = list(
            metadataAttributes = list(
              list(
                description = "string",
                key = "string",
                type = "STRING"|"NUMBER"|"BOOLEAN"|"STRING_LIST"
              )
            ),
            modelArn = "string"
          ),
          numberOfResults = 123,
          overrideSearchType = "HYBRID"|"SEMANTIC",
          rerankingConfiguration = list(
            bedrockRerankingConfiguration = list(
              metadataConfiguration = list(
                selectionMode = "SELECTIVE"|"ALL",
                selectiveModeConfiguration = list(
                  fieldsToExclude = list(
                    list(
                      fieldName = "string"
                    )
                  ),
                  fieldsToInclude = list(
                    list(
                      fieldName = "string"
                    )
                  )
                )
              ),
              modelConfiguration = list(
                additionalModelRequestFields = list(
                  list()
                ),
                modelArn = "string"
              ),
              numberOfRerankedResults = 123
            ),
            type = "BEDROCK_RERANKING_MODEL"
          )
        )
      )
    ),
    type = "KNOWLEDGE_BASE"|"EXTERNAL_SOURCES"
  ),
  sessionConfiguration = list(
    kmsKeyArn = "string"
  ),
  sessionId = "string"
)