Invoke Inline Agent
| bedrockagentruntime_invoke_inline_agent | R Documentation |
Invokes an inline Amazon Bedrock agent using the configurations you provide with the request¶
Description¶
Invokes an inline Amazon Bedrock agent using the configurations you provide with the request.
-
Specify the following fields for security purposes.
-
(Optional)
customerEncryptionKeyArn– The Amazon Resource Name (ARN) of a KMS key to encrypt the creation of the agent. -
(Optional)
idleSessionTTLinSeconds– Specify the number of seconds for which the agent should maintain session information. After this time expires, the subsequentinvoke_inline_agentrequest begins a new session.
-
-
To override the default prompt behavior for agent orchestration and to use advanced prompts, include a
promptOverrideConfigurationobject. For more information, see Advanced prompts. -
The agent instructions will not be honored if your agent has only one knowledge base, uses default prompts, has no action group, and user input is disabled.
Usage¶
bedrockagentruntime_invoke_inline_agent(actionGroups,
bedrockModelConfigurations, customerEncryptionKeyArn, enableTrace,
endSession, foundationModel, guardrailConfiguration,
idleSessionTTLInSeconds, inlineSessionState, inputText, instruction,
knowledgeBases, promptOverrideConfiguration, sessionId,
streamingConfigurations)
Arguments¶
actionGroups |
A list of action groups with each action group defining the action the inline agent needs to carry out. |
bedrockModelConfigurations |
Model settings for the request. |
customerEncryptionKeyArn |
The Amazon Resource Name (ARN) of the Amazon Web Services KMS key to use to encrypt your inline agent. |
enableTrace |
Specifies whether to turn on the trace or not to track the agent's reasoning process. For more information, see Using trace. |
endSession |
Specifies whether to end the session with the inline agent or not. |
foundationModel |
[required] The model
identifier (ID) of the model to use for orchestration by the inline
agent. For example, |
guardrailConfiguration |
The guardrails to assign to the inline agent. |
idleSessionTTLInSeconds |
The number of seconds for which the inline agent should maintain
session information. After this time expires, the subsequent
A user interaction remains active for the amount of time specified. If no conversation occurs during this time, the session expires and the data provided before the timeout is deleted. |
inlineSessionState |
Parameters that specify the various attributes of a sessions. You can include attributes for the session or prompt or, if you configured an action group to return control, results from invocation of the action group. For more information, see Control session context. If you include |
inputText |
The prompt text to send to the agent. If you include |
instruction |
[required] The instructions that tell the inline agent what it should do and how it should interact with users. |
knowledgeBases |
Contains information of the knowledge bases to associate with. |
promptOverrideConfiguration |
Configurations for advanced prompts used to override the default prompts to enhance the accuracy of the inline agent. |
sessionId |
[required] The unique identifier of the session. Use the same value across requests to continue the same conversation. |
streamingConfigurations |
Specifies the configurations for streaming. To use agent streaming, you need permissions to perform the
|
Value¶
A list with the following syntax:
list(
completion = list(
accessDeniedException = list(
message = "string"
),
badGatewayException = list(
message = "string",
resourceName = "string"
),
chunk = list(
attribution = 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()
)
)
)
)
)
),
bytes = raw
),
conflictException = list(
message = "string"
),
dependencyFailedException = list(
message = "string",
resourceName = "string"
),
files = list(
files = list(
list(
bytes = raw,
name = "string",
type = "string"
)
)
),
internalServerException = list(
message = "string",
reason = "string"
),
resourceNotFoundException = list(
message = "string"
),
returnControl = list(
invocationId = "string",
invocationInputs = list(
list(
apiInvocationInput = list(
actionGroup = "string",
actionInvocationType = "RESULT"|"USER_CONFIRMATION"|"USER_CONFIRMATION_AND_RESULT",
agentId = "string",
apiPath = "string",
collaboratorName = "string",
httpMethod = "string",
parameters = list(
list(
name = "string",
type = "string",
value = "string"
)
),
requestBody = list(
content = list(
list(
properties = list(
list(
name = "string",
type = "string",
value = "string"
)
)
)
)
)
),
functionInvocationInput = list(
actionGroup = "string",
actionInvocationType = "RESULT"|"USER_CONFIRMATION"|"USER_CONFIRMATION_AND_RESULT",
agentId = "string",
collaboratorName = "string",
function = "string",
parameters = list(
list(
name = "string",
type = "string",
value = "string"
)
)
)
)
)
),
serviceQuotaExceededException = list(
message = "string"
),
throttlingException = list(
message = "string"
),
trace = list(
sessionId = "string",
trace = list(
customOrchestrationTrace = list(
event = list(
text = "string"
),
traceId = "string"
),
failureTrace = list(
failureReason = "string",
traceId = "string"
),
guardrailTrace = list(
action = "INTERVENED"|"NONE",
inputAssessments = list(
list(
contentPolicy = list(
filters = list(
list(
action = "BLOCKED",
confidence = "NONE"|"LOW"|"MEDIUM"|"HIGH",
type = "INSULTS"|"HATE"|"SEXUAL"|"VIOLENCE"|"MISCONDUCT"|"PROMPT_ATTACK"
)
)
),
sensitiveInformationPolicy = list(
piiEntities = list(
list(
action = "BLOCKED"|"ANONYMIZED",
match = "string",
type = "ADDRESS"|"AGE"|"AWS_ACCESS_KEY"|"AWS_SECRET_KEY"|"CA_HEALTH_NUMBER"|"CA_SOCIAL_INSURANCE_NUMBER"|"CREDIT_DEBIT_CARD_CVV"|"CREDIT_DEBIT_CARD_EXPIRY"|"CREDIT_DEBIT_CARD_NUMBER"|"DRIVER_ID"|"EMAIL"|"INTERNATIONAL_BANK_ACCOUNT_NUMBER"|"IP_ADDRESS"|"LICENSE_PLATE"|"MAC_ADDRESS"|"NAME"|"PASSWORD"|"PHONE"|"PIN"|"SWIFT_CODE"|"UK_NATIONAL_HEALTH_SERVICE_NUMBER"|"UK_NATIONAL_INSURANCE_NUMBER"|"UK_UNIQUE_TAXPAYER_REFERENCE_NUMBER"|"URL"|"USERNAME"|"US_BANK_ACCOUNT_NUMBER"|"US_BANK_ROUTING_NUMBER"|"US_INDIVIDUAL_TAX_IDENTIFICATION_NUMBER"|"US_PASSPORT_NUMBER"|"US_SOCIAL_SECURITY_NUMBER"|"VEHICLE_IDENTIFICATION_NUMBER"
)
),
regexes = list(
list(
action = "BLOCKED"|"ANONYMIZED",
match = "string",
name = "string",
regex = "string"
)
)
),
topicPolicy = list(
topics = list(
list(
action = "BLOCKED",
name = "string",
type = "DENY"
)
)
),
wordPolicy = list(
customWords = list(
list(
action = "BLOCKED",
match = "string"
)
),
managedWordLists = list(
list(
action = "BLOCKED",
match = "string",
type = "PROFANITY"
)
)
)
)
),
outputAssessments = list(
list(
contentPolicy = list(
filters = list(
list(
action = "BLOCKED",
confidence = "NONE"|"LOW"|"MEDIUM"|"HIGH",
type = "INSULTS"|"HATE"|"SEXUAL"|"VIOLENCE"|"MISCONDUCT"|"PROMPT_ATTACK"
)
)
),
sensitiveInformationPolicy = list(
piiEntities = list(
list(
action = "BLOCKED"|"ANONYMIZED",
match = "string",
type = "ADDRESS"|"AGE"|"AWS_ACCESS_KEY"|"AWS_SECRET_KEY"|"CA_HEALTH_NUMBER"|"CA_SOCIAL_INSURANCE_NUMBER"|"CREDIT_DEBIT_CARD_CVV"|"CREDIT_DEBIT_CARD_EXPIRY"|"CREDIT_DEBIT_CARD_NUMBER"|"DRIVER_ID"|"EMAIL"|"INTERNATIONAL_BANK_ACCOUNT_NUMBER"|"IP_ADDRESS"|"LICENSE_PLATE"|"MAC_ADDRESS"|"NAME"|"PASSWORD"|"PHONE"|"PIN"|"SWIFT_CODE"|"UK_NATIONAL_HEALTH_SERVICE_NUMBER"|"UK_NATIONAL_INSURANCE_NUMBER"|"UK_UNIQUE_TAXPAYER_REFERENCE_NUMBER"|"URL"|"USERNAME"|"US_BANK_ACCOUNT_NUMBER"|"US_BANK_ROUTING_NUMBER"|"US_INDIVIDUAL_TAX_IDENTIFICATION_NUMBER"|"US_PASSPORT_NUMBER"|"US_SOCIAL_SECURITY_NUMBER"|"VEHICLE_IDENTIFICATION_NUMBER"
)
),
regexes = list(
list(
action = "BLOCKED"|"ANONYMIZED",
match = "string",
name = "string",
regex = "string"
)
)
),
topicPolicy = list(
topics = list(
list(
action = "BLOCKED",
name = "string",
type = "DENY"
)
)
),
wordPolicy = list(
customWords = list(
list(
action = "BLOCKED",
match = "string"
)
),
managedWordLists = list(
list(
action = "BLOCKED",
match = "string",
type = "PROFANITY"
)
)
)
)
),
traceId = "string"
),
orchestrationTrace = list(
invocationInput = list(
actionGroupInvocationInput = list(
actionGroupName = "string",
apiPath = "string",
executionType = "LAMBDA"|"RETURN_CONTROL",
function = "string",
invocationId = "string",
parameters = list(
list(
name = "string",
type = "string",
value = "string"
)
),
requestBody = list(
content = list(
list(
list(
name = "string",
type = "string",
value = "string"
)
)
)
),
verb = "string"
),
agentCollaboratorInvocationInput = list(
agentCollaboratorAliasArn = "string",
agentCollaboratorName = "string",
input = list(
returnControlResults = list(
invocationId = "string",
returnControlInvocationResults = list(
list(
apiResult = list(
actionGroup = "string",
agentId = "string",
apiPath = "string",
confirmationState = "CONFIRM"|"DENY",
httpMethod = "string",
httpStatusCode = 123,
responseBody = list(
list(
body = "string"
)
),
responseState = "FAILURE"|"REPROMPT"
),
functionResult = list(
actionGroup = "string",
agentId = "string",
confirmationState = "CONFIRM"|"DENY",
function = "string",
responseBody = list(
list(
body = "string"
)
),
responseState = "FAILURE"|"REPROMPT"
)
)
)
),
text = "string",
type = "TEXT"|"RETURN_CONTROL"
)
),
codeInterpreterInvocationInput = list(
code = "string",
files = list(
"string"
)
),
invocationType = "ACTION_GROUP"|"KNOWLEDGE_BASE"|"FINISH"|"ACTION_GROUP_CODE_INTERPRETER"|"AGENT_COLLABORATOR",
knowledgeBaseLookupInput = list(
knowledgeBaseId = "string",
text = "string"
),
traceId = "string"
),
modelInvocationInput = list(
foundationModel = "string",
inferenceConfiguration = list(
maximumLength = 123,
stopSequences = list(
"string"
),
temperature = 123.0,
topK = 123,
topP = 123.0
),
overrideLambda = "string",
parserMode = "DEFAULT"|"OVERRIDDEN",
promptCreationMode = "DEFAULT"|"OVERRIDDEN",
text = "string",
traceId = "string",
type = "PRE_PROCESSING"|"ORCHESTRATION"|"KNOWLEDGE_BASE_RESPONSE_GENERATION"|"POST_PROCESSING"|"ROUTING_CLASSIFIER"
),
modelInvocationOutput = list(
metadata = list(
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
rawResponse = list(
content = "string"
),
traceId = "string"
),
observation = list(
actionGroupInvocationOutput = list(
text = "string"
),
agentCollaboratorInvocationOutput = list(
agentCollaboratorAliasArn = "string",
agentCollaboratorName = "string",
output = list(
returnControlPayload = list(
invocationId = "string",
invocationInputs = list(
list(
apiInvocationInput = list(
actionGroup = "string",
actionInvocationType = "RESULT"|"USER_CONFIRMATION"|"USER_CONFIRMATION_AND_RESULT",
agentId = "string",
apiPath = "string",
collaboratorName = "string",
httpMethod = "string",
parameters = list(
list(
name = "string",
type = "string",
value = "string"
)
),
requestBody = list(
content = list(
list(
properties = list(
list(
name = "string",
type = "string",
value = "string"
)
)
)
)
)
),
functionInvocationInput = list(
actionGroup = "string",
actionInvocationType = "RESULT"|"USER_CONFIRMATION"|"USER_CONFIRMATION_AND_RESULT",
agentId = "string",
collaboratorName = "string",
function = "string",
parameters = list(
list(
name = "string",
type = "string",
value = "string"
)
)
)
)
)
),
text = "string",
type = "TEXT"|"RETURN_CONTROL"
)
),
codeInterpreterInvocationOutput = list(
executionError = "string",
executionOutput = "string",
executionTimeout = TRUE|FALSE,
files = list(
"string"
)
),
finalResponse = list(
text = "string"
),
knowledgeBaseLookupOutput = list(
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()
)
)
)
),
repromptResponse = list(
source = "ACTION_GROUP"|"KNOWLEDGE_BASE"|"PARSER",
text = "string"
),
traceId = "string",
type = "ACTION_GROUP"|"AGENT_COLLABORATOR"|"KNOWLEDGE_BASE"|"FINISH"|"ASK_USER"|"REPROMPT"
),
rationale = list(
text = "string",
traceId = "string"
)
),
postProcessingTrace = list(
modelInvocationInput = list(
foundationModel = "string",
inferenceConfiguration = list(
maximumLength = 123,
stopSequences = list(
"string"
),
temperature = 123.0,
topK = 123,
topP = 123.0
),
overrideLambda = "string",
parserMode = "DEFAULT"|"OVERRIDDEN",
promptCreationMode = "DEFAULT"|"OVERRIDDEN",
text = "string",
traceId = "string",
type = "PRE_PROCESSING"|"ORCHESTRATION"|"KNOWLEDGE_BASE_RESPONSE_GENERATION"|"POST_PROCESSING"|"ROUTING_CLASSIFIER"
),
modelInvocationOutput = list(
metadata = list(
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
parsedResponse = list(
text = "string"
),
rawResponse = list(
content = "string"
),
traceId = "string"
)
),
preProcessingTrace = list(
modelInvocationInput = list(
foundationModel = "string",
inferenceConfiguration = list(
maximumLength = 123,
stopSequences = list(
"string"
),
temperature = 123.0,
topK = 123,
topP = 123.0
),
overrideLambda = "string",
parserMode = "DEFAULT"|"OVERRIDDEN",
promptCreationMode = "DEFAULT"|"OVERRIDDEN",
text = "string",
traceId = "string",
type = "PRE_PROCESSING"|"ORCHESTRATION"|"KNOWLEDGE_BASE_RESPONSE_GENERATION"|"POST_PROCESSING"|"ROUTING_CLASSIFIER"
),
modelInvocationOutput = list(
metadata = list(
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
parsedResponse = list(
isValid = TRUE|FALSE,
rationale = "string"
),
rawResponse = list(
content = "string"
),
traceId = "string"
)
),
routingClassifierTrace = list(
invocationInput = list(
actionGroupInvocationInput = list(
actionGroupName = "string",
apiPath = "string",
executionType = "LAMBDA"|"RETURN_CONTROL",
function = "string",
invocationId = "string",
parameters = list(
list(
name = "string",
type = "string",
value = "string"
)
),
requestBody = list(
content = list(
list(
list(
name = "string",
type = "string",
value = "string"
)
)
)
),
verb = "string"
),
agentCollaboratorInvocationInput = list(
agentCollaboratorAliasArn = "string",
agentCollaboratorName = "string",
input = list(
returnControlResults = list(
invocationId = "string",
returnControlInvocationResults = list(
list(
apiResult = list(
actionGroup = "string",
agentId = "string",
apiPath = "string",
confirmationState = "CONFIRM"|"DENY",
httpMethod = "string",
httpStatusCode = 123,
responseBody = list(
list(
body = "string"
)
),
responseState = "FAILURE"|"REPROMPT"
),
functionResult = list(
actionGroup = "string",
agentId = "string",
confirmationState = "CONFIRM"|"DENY",
function = "string",
responseBody = list(
list(
body = "string"
)
),
responseState = "FAILURE"|"REPROMPT"
)
)
)
),
text = "string",
type = "TEXT"|"RETURN_CONTROL"
)
),
codeInterpreterInvocationInput = list(
code = "string",
files = list(
"string"
)
),
invocationType = "ACTION_GROUP"|"KNOWLEDGE_BASE"|"FINISH"|"ACTION_GROUP_CODE_INTERPRETER"|"AGENT_COLLABORATOR",
knowledgeBaseLookupInput = list(
knowledgeBaseId = "string",
text = "string"
),
traceId = "string"
),
modelInvocationInput = list(
foundationModel = "string",
inferenceConfiguration = list(
maximumLength = 123,
stopSequences = list(
"string"
),
temperature = 123.0,
topK = 123,
topP = 123.0
),
overrideLambda = "string",
parserMode = "DEFAULT"|"OVERRIDDEN",
promptCreationMode = "DEFAULT"|"OVERRIDDEN",
text = "string",
traceId = "string",
type = "PRE_PROCESSING"|"ORCHESTRATION"|"KNOWLEDGE_BASE_RESPONSE_GENERATION"|"POST_PROCESSING"|"ROUTING_CLASSIFIER"
),
modelInvocationOutput = list(
metadata = list(
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
rawResponse = list(
content = "string"
),
traceId = "string"
),
observation = list(
actionGroupInvocationOutput = list(
text = "string"
),
agentCollaboratorInvocationOutput = list(
agentCollaboratorAliasArn = "string",
agentCollaboratorName = "string",
output = list(
returnControlPayload = list(
invocationId = "string",
invocationInputs = list(
list(
apiInvocationInput = list(
actionGroup = "string",
actionInvocationType = "RESULT"|"USER_CONFIRMATION"|"USER_CONFIRMATION_AND_RESULT",
agentId = "string",
apiPath = "string",
collaboratorName = "string",
httpMethod = "string",
parameters = list(
list(
name = "string",
type = "string",
value = "string"
)
),
requestBody = list(
content = list(
list(
properties = list(
list(
name = "string",
type = "string",
value = "string"
)
)
)
)
)
),
functionInvocationInput = list(
actionGroup = "string",
actionInvocationType = "RESULT"|"USER_CONFIRMATION"|"USER_CONFIRMATION_AND_RESULT",
agentId = "string",
collaboratorName = "string",
function = "string",
parameters = list(
list(
name = "string",
type = "string",
value = "string"
)
)
)
)
)
),
text = "string",
type = "TEXT"|"RETURN_CONTROL"
)
),
codeInterpreterInvocationOutput = list(
executionError = "string",
executionOutput = "string",
executionTimeout = TRUE|FALSE,
files = list(
"string"
)
),
finalResponse = list(
text = "string"
),
knowledgeBaseLookupOutput = list(
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()
)
)
)
),
repromptResponse = list(
source = "ACTION_GROUP"|"KNOWLEDGE_BASE"|"PARSER",
text = "string"
),
traceId = "string",
type = "ACTION_GROUP"|"AGENT_COLLABORATOR"|"KNOWLEDGE_BASE"|"FINISH"|"ASK_USER"|"REPROMPT"
)
)
)
),
validationException = list(
message = "string"
)
),
contentType = "string",
sessionId = "string"
)
Request syntax¶
svc$invoke_inline_agent(
actionGroups = list(
list(
actionGroupExecutor = list(
customControl = "RETURN_CONTROL",
lambda = "string"
),
actionGroupName = "string",
apiSchema = list(
payload = "string",
s3 = list(
s3BucketName = "string",
s3ObjectKey = "string"
)
),
description = "string",
functionSchema = list(
functions = list(
list(
description = "string",
name = "string",
parameters = list(
list(
description = "string",
required = TRUE|FALSE,
type = "string"|"number"|"integer"|"boolean"|"array"
)
),
requireConfirmation = "ENABLED"|"DISABLED"
)
)
),
parentActionGroupSignature = "AMAZON.UserInput"|"AMAZON.CodeInterpreter"
)
),
bedrockModelConfigurations = list(
performanceConfig = list(
latency = "standard"|"optimized"
)
),
customerEncryptionKeyArn = "string",
enableTrace = TRUE|FALSE,
endSession = TRUE|FALSE,
foundationModel = "string",
guardrailConfiguration = list(
guardrailIdentifier = "string",
guardrailVersion = "string"
),
idleSessionTTLInSeconds = 123,
inlineSessionState = list(
files = list(
list(
name = "string",
source = list(
byteContent = list(
data = raw,
mediaType = "string"
),
s3Location = list(
uri = "string"
),
sourceType = "S3"|"BYTE_CONTENT"
),
useCase = "CODE_INTERPRETER"|"CHAT"
)
),
invocationId = "string",
promptSessionAttributes = list(
"string"
),
returnControlInvocationResults = list(
list(
apiResult = list(
actionGroup = "string",
agentId = "string",
apiPath = "string",
confirmationState = "CONFIRM"|"DENY",
httpMethod = "string",
httpStatusCode = 123,
responseBody = list(
list(
body = "string"
)
),
responseState = "FAILURE"|"REPROMPT"
),
functionResult = list(
actionGroup = "string",
agentId = "string",
confirmationState = "CONFIRM"|"DENY",
function = "string",
responseBody = list(
list(
body = "string"
)
),
responseState = "FAILURE"|"REPROMPT"
)
)
),
sessionAttributes = list(
"string"
)
),
inputText = "string",
instruction = "string",
knowledgeBases = list(
list(
description = "string",
knowledgeBaseId = "string",
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"
)
)
)
)
),
promptOverrideConfiguration = list(
overrideLambda = "string",
promptConfigurations = list(
list(
additionalModelRequestFields = list(),
basePromptTemplate = "string",
inferenceConfiguration = list(
maximumLength = 123,
stopSequences = list(
"string"
),
temperature = 123.0,
topK = 123,
topP = 123.0
),
parserMode = "DEFAULT"|"OVERRIDDEN",
promptCreationMode = "DEFAULT"|"OVERRIDDEN",
promptState = "ENABLED"|"DISABLED",
promptType = "PRE_PROCESSING"|"ORCHESTRATION"|"KNOWLEDGE_BASE_RESPONSE_GENERATION"|"POST_PROCESSING"|"ROUTING_CLASSIFIER"
)
)
),
sessionId = "string",
streamingConfigurations = list(
applyGuardrailInterval = 123,
streamFinalResponse = TRUE|FALSE
)
)