Invoke Flow
| bedrockagentruntime_invoke_flow | R Documentation |
Invokes an alias of a flow to run the inputs that you specify and return the output of each node as a stream¶
Description¶
Invokes an alias of a flow to run the inputs that you specify and return the output of each node as a stream. If there's an error, the error is returned. For more information, see Test a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
The CLI doesn't support streaming operations in Amazon Bedrock,
including invoke_flow.
Usage¶
bedrockagentruntime_invoke_flow(enableTrace, executionId,
flowAliasIdentifier, flowIdentifier, inputs,
modelPerformanceConfiguration)
Arguments¶
enableTrace |
Specifies whether to return the trace for the flow or not. Traces track inputs and outputs for nodes in the flow. For more information, see Track each step in your prompt flow by viewing its trace in Amazon Bedrock. |
executionId |
The unique identifier for the current flow execution. If you don't provide a value, Amazon Bedrock creates the identifier for you. |
flowAliasIdentifier |
[required] The unique identifier of the flow alias. |
flowIdentifier |
[required] The unique identifier of the flow. |
inputs |
[required] A list of objects, each containing information about an input into the flow. |
modelPerformanceConfiguration |
Model performance settings for the request. |
Value¶
A list with the following syntax:
list(
executionId = "string",
responseStream = list(
accessDeniedException = list(
message = "string"
),
badGatewayException = list(
message = "string",
resourceName = "string"
),
conflictException = list(
message = "string"
),
dependencyFailedException = list(
message = "string",
resourceName = "string"
),
flowCompletionEvent = list(
completionReason = "SUCCESS"|"INPUT_REQUIRED"
),
flowMultiTurnInputRequestEvent = list(
content = list(
document = list()
),
nodeName = "string",
nodeType = "FlowInputNode"|"FlowOutputNode"|"LambdaFunctionNode"|"KnowledgeBaseNode"|"PromptNode"|"ConditionNode"|"LexNode"
),
flowOutputEvent = list(
content = list(
document = list()
),
nodeName = "string",
nodeType = "FlowInputNode"|"FlowOutputNode"|"LambdaFunctionNode"|"KnowledgeBaseNode"|"PromptNode"|"ConditionNode"|"LexNode"
),
flowTraceEvent = list(
trace = list(
conditionNodeResultTrace = list(
nodeName = "string",
satisfiedConditions = list(
list(
conditionName = "string"
)
),
timestamp = as.POSIXct(
"2015-01-01"
)
),
nodeActionTrace = list(
nodeName = "string",
operationName = "string",
operationRequest = list(),
operationResponse = list(),
requestId = "string",
serviceName = "string",
timestamp = as.POSIXct(
"2015-01-01"
)
),
nodeDependencyTrace = list(
nodeName = "string",
timestamp = as.POSIXct(
"2015-01-01"
),
traceElements = list(
agentTraces = list(
list(
agentAliasId = "string",
agentId = "string",
agentVersion = "string",
callerChain = list(
list(
agentAliasArn = "string"
)
),
collaboratorName = "string",
eventTime = as.POSIXct(
"2015-01-01"
),
sessionId = "string",
trace = list(
customOrchestrationTrace = list(
event = list(
text = "string"
),
traceId = "string"
),
failureTrace = list(
failureCode = 123,
failureReason = "string",
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
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"
)
)
)
)
),
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
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",
images = list(
list(
format = "png"|"jpeg"|"gif"|"webp",
source = list(
bytes = raw
)
)
)
)
),
responseState = "FAILURE"|"REPROMPT"
),
functionResult = list(
actionGroup = "string",
agentId = "string",
confirmationState = "CONFIRM"|"DENY",
function = "string",
responseBody = list(
list(
body = "string",
images = list(
list(
format = "png"|"jpeg"|"gif"|"webp",
source = list(
bytes = raw
)
)
)
)
),
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(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
rawResponse = list(
content = "string"
),
reasoningContent = list(
reasoningText = list(
signature = "string",
text = "string"
),
redactedContent = raw
),
traceId = "string"
),
observation = list(
actionGroupInvocationOutput = list(
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
text = "string"
),
agentCollaboratorInvocationOutput = list(
agentCollaboratorAliasArn = "string",
agentCollaboratorName = "string",
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
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"
),
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
)
),
finalResponse = list(
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
text = "string"
),
knowledgeBaseLookupOutput = list(
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
retrievedReferences = list(
list(
content = list(
audio = list(
s3Uri = "string",
transcription = "string"
),
byteContent = "string",
row = list(
list(
columnName = "string",
columnValue = "string",
type = "BLOB"|"BOOLEAN"|"DOUBLE"|"NULL"|"LONG"|"STRING"
)
),
text = "string",
type = "TEXT"|"IMAGE"|"ROW"|"AUDIO"|"VIDEO",
video = list(
s3Uri = "string",
summary = "string"
)
),
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(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
parsedResponse = list(
text = "string"
),
rawResponse = list(
content = "string"
),
reasoningContent = list(
reasoningText = list(
signature = "string",
text = "string"
),
redactedContent = raw
),
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(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
parsedResponse = list(
isValid = TRUE|FALSE,
rationale = "string"
),
rawResponse = list(
content = "string"
),
reasoningContent = list(
reasoningText = list(
signature = "string",
text = "string"
),
redactedContent = raw
),
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",
images = list(
list(
format = "png"|"jpeg"|"gif"|"webp",
source = list(
bytes = raw
)
)
)
)
),
responseState = "FAILURE"|"REPROMPT"
),
functionResult = list(
actionGroup = "string",
agentId = "string",
confirmationState = "CONFIRM"|"DENY",
function = "string",
responseBody = list(
list(
body = "string",
images = list(
list(
format = "png"|"jpeg"|"gif"|"webp",
source = list(
bytes = raw
)
)
)
)
),
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(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
rawResponse = list(
content = "string"
),
traceId = "string"
),
observation = list(
actionGroupInvocationOutput = list(
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
text = "string"
),
agentCollaboratorInvocationOutput = list(
agentCollaboratorAliasArn = "string",
agentCollaboratorName = "string",
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
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"
),
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
)
),
finalResponse = list(
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
text = "string"
),
knowledgeBaseLookupOutput = list(
metadata = list(
clientRequestId = "string",
endTime = as.POSIXct(
"2015-01-01"
),
operationTotalTimeMs = 123,
startTime = as.POSIXct(
"2015-01-01"
),
totalTimeMs = 123,
usage = list(
inputTokens = 123,
outputTokens = 123
)
),
retrievedReferences = list(
list(
content = list(
audio = list(
s3Uri = "string",
transcription = "string"
),
byteContent = "string",
row = list(
list(
columnName = "string",
columnValue = "string",
type = "BLOB"|"BOOLEAN"|"DOUBLE"|"NULL"|"LONG"|"STRING"
)
),
text = "string",
type = "TEXT"|"IMAGE"|"ROW"|"AUDIO"|"VIDEO",
video = list(
s3Uri = "string",
summary = "string"
)
),
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"
)
)
)
)
)
)
),
nodeInputTrace = list(
fields = list(
list(
category = "LoopCondition"|"ReturnValueToLoopStart"|"ExitLoop",
content = list(
document = list()
),
executionChain = list(
list(
index = 123,
nodeName = "string",
type = "Iterator"|"Loop"
)
),
nodeInputName = "string",
source = list(
expression = "string",
nodeName = "string",
outputFieldName = "string"
),
type = "String"|"Number"|"Boolean"|"Object"|"Array"
)
),
nodeName = "string",
timestamp = as.POSIXct(
"2015-01-01"
)
),
nodeOutputTrace = list(
fields = list(
list(
content = list(
document = list()
),
next = list(
list(
inputFieldName = "string",
nodeName = "string"
)
),
nodeOutputName = "string",
type = "String"|"Number"|"Boolean"|"Object"|"Array"
)
),
nodeName = "string",
timestamp = as.POSIXct(
"2015-01-01"
)
)
)
),
internalServerException = list(
message = "string",
reason = "string"
),
resourceNotFoundException = list(
message = "string"
),
serviceQuotaExceededException = list(
message = "string"
),
throttlingException = list(
message = "string"
),
validationException = list(
message = "string"
)
)
)
Request syntax¶
svc$invoke_flow(
enableTrace = TRUE|FALSE,
executionId = "string",
flowAliasIdentifier = "string",
flowIdentifier = "string",
inputs = list(
list(
content = list(
document = list()
),
nodeInputName = "string",
nodeName = "string",
nodeOutputName = "string"
)
),
modelPerformanceConfiguration = list(
performanceConfig = list(
latency = "standard"|"optimized"
)
)
)