list_spans ¶

def list_spans(
    self,
    assistant_id: "capo_qconnect.types.uuid_or_arn.UuidOrArn",
    session_id: "capo_qconnect.types.uuid_or_arn.UuidOrArn",
    *,
    config_overrides: Optional[QConnectClientConfig] = None,
    next_token: Optional["capo_qconnect.types.next_token.NextToken"] = None,
    max_results: Optional["capo_qconnect.types.max_results.MaxResults"] = None,
) -> "capo_qconnect.types.list_spans_response.ListSpansResponse":
    """<p>Retrieves AI agent execution traces for a session, providing granular visibility into agent orchestration flows, LLM interactions, and tool invocations.</p>

    Args:
        assistant_id: <p>UUID or ARN of the Connect AI Assistant resource</p>
        session_id: <p>UUID or ARN of the Connect AI Session resource</p>
        next_token: <p>Pagination token for retrieving the next page of results</p>
        max_results: <p>Maximum number of spans to return per page</p>

    Raises:
        capo_qconnect.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_qconnect.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource does not exist.</p>
        capo_qconnect.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by a service.</p>
        capo_qconnect.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_qconnect.types.list_spans_request.ListSpansRequest]",
    ) -> OperationResponse[
        "capo_qconnect.types.list_spans_response.ListSpansResponse"
    ]:
        import capo_qconnect._operations.wisdom_service.list_spans

        output, http_response = (
            capo_qconnect._operations.wisdom_service.list_spans.list_spans(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_output(
        output: "capo_qconnect.types.list_spans_response.ListSpansResponse",
    ) -> dict[str, Any]:
        import capo_qconnect.types.list_spans_response

        return capo_qconnect.types.list_spans_response.redact_sensitive(output)

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("ListSpans", redact_output=_redact_output),
    )
    input_: capo_qconnect.types.list_spans_request.ListSpansRequest = {
        "assistant_id": assistant_id,
        "session_id": session_id,
    }
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output