Method
executeConversationAgent POST
Copy POST

Executes a deployed AI agent function using the arguments as keyword arguments to the agent execute function.

Arguments:

REQUIRED KEY TYPE DESCRIPTION
Yes deploymentToken str The deployment token used to authenticate access to created deployments. This token is only authorized to predict on deployments in this project, so it is safe to embed this model inside of an application or website.
Yes deploymentId str A unique string identifier for the deployment created under the project.
No arguments list Positional arguments to the agent execute function.
No keywordArguments dict A dictionary where each 'key' represents the paramter name and its corresponding 'value' represents the value of that parameter for the agent execute function.
No deploymentConversationId str A unique string identifier for the deployment conversation used for the conversation.
No externalSessionId str A unique string identifier for the session used for the conversation. If both deployment_conversation_id and external_session_id are not provided, a new session will be created.
No regenerate bool If True, will regenerate the response from the last query.
No docInfos list An optional list of documents use for the conversation. A keyword 'doc_id' is expected to be present in each document for retrieving contents from docstore.
No agentWorkflowNodeId str An optional agent workflow node id to trigger agent execution from an intermediate node.
Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.

Response:

KEY TYPE DESCRIPTION
success Boolean true if the call succeeded, false if there was an error
response String
deploymentConversationId Unique String Identifier

Exceptions:

TYPE WHEN
DataNotFoundError

deploymentId is not found.
DataNotFoundError

deploymentConversationId is not found.
DataNotFoundError

externalSessionId is not found.
DataNotFoundError

agentWorkflowNodeId is not found.
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