queryMetrics(location, body=None, x__xgafv=None)
Query metrics.

Args:
  location: string, Required. The location of the data. "projects/{project}/locations/{location}" (required)
  body: object, The request body.
    The object takes the form of:

{ # The request for querying metrics.
  "dimensions": [ # The dimensions that determine the grouping key for the query. Defaults to no dimension if this field is unspecified. If a dimension is specified, its key must also be specified. Each dimension's key must be unique. If a time granularity is also specified, metric values in the dimension will be bucketed by this granularity. Up to one dimension is supported for now.
    { # A dimension determines the grouping key for the query. In SQL terms, these would be part of both the "SELECT" and "GROUP BY" clauses.
      "agentDimensionMetadata": { # Metadata about the agent dimension. # Output only. Metadata about the agent dimension.
        "agentDisplayName": "A String", # Optional. The agent's name
        "agentId": "A String", # Optional. A user-specified string representing the agent.
        "agentTeam": "A String", # Optional. A user-specified string representing the agent's team.
      },
      "dimensionKey": "A String", # The key of the dimension.
      "issueDimensionMetadata": { # Metadata about the issue dimension. # Output only. Metadata about the issue dimension.
        "issueDisplayName": "A String", # The issue display name.
        "issueId": "A String", # The issue ID.
        "issueModelId": "A String", # The parent issue model ID.
      },
      "qaQuestionAnswerDimensionMetadata": { # Metadata about the QA question-answer dimension. This is useful for showing the answer distribution for questions for a given scorecard. # Output only. Metadata about the QA question-answer dimension.
        "answerValue": "A String", # Optional. The full body of the question.
        "qaQuestionId": "A String", # Optional. The QA question ID.
        "qaScorecardId": "A String", # Optional. The QA scorecard ID.
        "questionBody": "A String", # Optional. The full body of the question.
      },
      "qaQuestionDimensionMetadata": { # Metadata about the QA question dimension. # Output only. Metadata about the QA question dimension.
        "qaQuestionId": "A String", # Optional. The QA question ID.
        "qaScorecardId": "A String", # Optional. The QA scorecard ID.
        "questionBody": "A String", # Optional. The full body of the question.
      },
    },
  ],
  "filter": "A String", # Required. Filter to select a subset of conversations to compute the metrics. Must specify a window of the conversation create time to compute the metrics. The returned metrics will be from the range [DATE(starting create time), DATE(ending create time)).
  "measureMask": "A String", # Measures to return. Defaults to all measures if this field is unspecified. A valid mask should traverse from the `measure` field from the response. For example, a path from a measure mask to get the conversation count is "conversation_measure.count".
  "timeGranularity": "A String", # The time granularity of each data point in the time series. Defaults to NONE if this field is unspecified.
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # This resource represents a long-running operation that is the result of a network API call.
  "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
  "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
    "code": 42, # The status code, which should be an enum value of google.rpc.Code.
    "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        "a_key": "", # Properties of the object. Contains field @type with type URL.
      },
    ],
    "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
    "a_key": "", # Properties of the object. Contains field @type with type URL.
  },
  "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
  "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
    "a_key": "", # Properties of the object. Contains field @type with type URL.
  },
}
Contact Center AI Insights API . projects . locations . authorizedViewSets . authorizedViews

Instance Methods

Method Details
