calculateIssueModelStats(issueModel, x__xgafv=None)

Gets an issue model's statistics.

Args:
  issueModel: string, Required. The resource name of the issue model to query against. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response of querying an issue model's statistics.
  "currentStats": { # Aggregated statistics about an issue model. # The latest label statistics for the queried issue model. Includes results on both training data and data labeled after deployment.
    "analyzedConversationsCount": "A String", # Number of conversations the issue model has analyzed at this point in time.
    "issueStats": { # Statistics on each issue. Key is the issue's resource name.
      "a_key": { # Aggregated statistics about an issue.
        "displayName": "A String", # Display name of the issue.
        "issue": "A String", # Issue resource. Format: projects/{project}/locations/{location}/issueModels/{issue_model}/issues/{issue}
        "labeledConversationsCount": "A String", # Number of conversations attached to the issue at this point in time.
      },
    },
    "unclassifiedConversationsCount": "A String", # Number of analyzed conversations for which no issue was applicable at this point in time.
  },
}

close()

Close httplib2 connections.

create(parent, body=None, x__xgafv=None)

Creates an issue model.

Args:
  parent: string, Required. The parent resource of the issue model. (required)
  body: object, The request body.
    The object takes the form of:

{ # The issue model resource.
  "createTime": "A String", # Output only. The time at which this issue model was created.
  "displayName": "A String", # The representative name for the issue model.
  "inputDataConfig": { # Configs for the input data used to create the issue model. # Configs for the input data that used to create the issue model.
    "filter": "A String", # A filter to reduce the conversations used for training the model to a specific subset.
    "medium": "A String", # Medium of conversations used in training data. This field is being deprecated. To specify the medium to be used in training a new issue model, set the `medium` field on `filter`.
    "trainingConversationsCount": "A String", # Output only. Number of conversations used in training. Output only.
  },
  "issueCount": "A String", # Output only. Number of issues in this issue model.
  "languageCode": "A String", # Language of the model.
  "modelType": "A String", # Type of the model.
  "name": "A String", # Immutable. The resource name of the issue model. Format: projects/{project}/locations/{location}/issueModels/{issue_model}
  "state": "A String", # Output only. State of the model.
  "trainingStats": { # Aggregated statistics about an issue model. # Output only. Immutable. The issue model's label statistics on its training data.
    "analyzedConversationsCount": "A String", # Number of conversations the issue model has analyzed at this point in time.
    "issueStats": { # Statistics on each issue. Key is the issue's resource name.
      "a_key": { # Aggregated statistics about an issue.
        "displayName": "A String", # Display name of the issue.
        "issue": "A String", # Issue resource. Format: projects/{project}/locations/{location}/issueModels/{issue_model}/issues/{issue}
        "labeledConversationsCount": "A String", # Number of conversations attached to the issue at this point in time.
      },
    },
    "unclassifiedConversationsCount": "A String", # Number of analyzed conversations for which no issue was applicable at this point in time.
  },
  "updateTime": "A String", # Output only. The most recent time at which the issue model was updated.
}

  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.
  },
}

delete(name, x__xgafv=None)

Deletes an issue model.

Args:
name: string, Required. The name of the issue model to delete. (required)
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.
},
}

deploy(name, body=None, x__xgafv=None)

Deploys an issue model. Returns an error if a model is already deployed. An issue model can only be used in analysis after it has been deployed.

Args:
name: string, Required. The issue model to deploy. (required)
body: object, The request body.
The object takes the form of:

{ # The request to deploy an issue model.
"name": "A String", # Required. The issue model to deploy.
}

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.
},
}

export(name, body=None, x__xgafv=None)

Exports an issue model to the provided destination.

Args:
name: string, Required. The issue model to export (required)
body: object, The request body.
The object takes the form of:

{ # Request to export an issue model.
"gcsDestination": { # Google Cloud Storage Object URI to save the issue model to. # Google Cloud Storage URI to export the Issue Model to.
"objectUri": "A String", # Required. Format: `gs:///`
},
"name": "A String", # Required. The issue model to export
}

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.
},
}

get(name, x__xgafv=None)

Gets an issue model.

Args:
  name: string, Required. The name of the issue model to get. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # The issue model resource.
  "createTime": "A String", # Output only. The time at which this issue model was created.
  "displayName": "A String", # The representative name for the issue model.
  "inputDataConfig": { # Configs for the input data used to create the issue model. # Configs for the input data that used to create the issue model.
    "filter": "A String", # A filter to reduce the conversations used for training the model to a specific subset.
    "medium": "A String", # Medium of conversations used in training data. This field is being deprecated. To specify the medium to be used in training a new issue model, set the `medium` field on `filter`.
    "trainingConversationsCount": "A String", # Output only. Number of conversations used in training. Output only.
  },
  "issueCount": "A String", # Output only. Number of issues in this issue model.
  "languageCode": "A String", # Language of the model.
  "modelType": "A String", # Type of the model.
  "name": "A String", # Immutable. The resource name of the issue model. Format: projects/{project}/locations/{location}/issueModels/{issue_model}
  "state": "A String", # Output only. State of the model.
  "trainingStats": { # Aggregated statistics about an issue model. # Output only. Immutable. The issue model's label statistics on its training data.
    "analyzedConversationsCount": "A String", # Number of conversations the issue model has analyzed at this point in time.
    "issueStats": { # Statistics on each issue. Key is the issue's resource name.
      "a_key": { # Aggregated statistics about an issue.
        "displayName": "A String", # Display name of the issue.
        "issue": "A String", # Issue resource. Format: projects/{project}/locations/{location}/issueModels/{issue_model}/issues/{issue}
        "labeledConversationsCount": "A String", # Number of conversations attached to the issue at this point in time.
      },
    },
    "unclassifiedConversationsCount": "A String", # Number of analyzed conversations for which no issue was applicable at this point in time.
  },
  "updateTime": "A String", # Output only. The most recent time at which the issue model was updated.
}

import_(parent, body=None, x__xgafv=None)

Imports an issue model from a Cloud Storage bucket.

Args:
parent: string, Required. The parent resource of the issue model. (required)
body: object, The request body.
The object takes the form of:

{ # Request to import an issue model.
"createNewModel": True or False, # Optional. If set to true, will create a new issue model from the imported file with randomly generated IDs for the issue model and corresponding issues. Otherwise, replaces an existing model with the same ID as the file.
"gcsSource": { # Google Cloud Storage Object URI to get the issue model file from. # Google Cloud Storage source message.
"objectUri": "A String", # Required. Format: `gs:///`
},
"parent": "A String", # Required. The parent resource of the issue model.
}

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.
},
}

list(parent, x__xgafv=None)

Lists issue models.

Args:
  parent: string, Required. The parent resource of the issue model. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # The response of listing issue models.
  "issueModels": [ # The issue models that match the request.
    { # The issue model resource.
      "createTime": "A String", # Output only. The time at which this issue model was created.
      "displayName": "A String", # The representative name for the issue model.
      "inputDataConfig": { # Configs for the input data used to create the issue model. # Configs for the input data that used to create the issue model.
        "filter": "A String", # A filter to reduce the conversations used for training the model to a specific subset.
        "medium": "A String", # Medium of conversations used in training data. This field is being deprecated. To specify the medium to be used in training a new issue model, set the `medium` field on `filter`.
        "trainingConversationsCount": "A String", # Output only. Number of conversations used in training. Output only.
      },
      "issueCount": "A String", # Output only. Number of issues in this issue model.
      "languageCode": "A String", # Language of the model.
      "modelType": "A String", # Type of the model.
      "name": "A String", # Immutable. The resource name of the issue model. Format: projects/{project}/locations/{location}/issueModels/{issue_model}
      "state": "A String", # Output only. State of the model.
      "trainingStats": { # Aggregated statistics about an issue model. # Output only. Immutable. The issue model's label statistics on its training data.
        "analyzedConversationsCount": "A String", # Number of conversations the issue model has analyzed at this point in time.
        "issueStats": { # Statistics on each issue. Key is the issue's resource name.
          "a_key": { # Aggregated statistics about an issue.
            "displayName": "A String", # Display name of the issue.
            "issue": "A String", # Issue resource. Format: projects/{project}/locations/{location}/issueModels/{issue_model}/issues/{issue}
            "labeledConversationsCount": "A String", # Number of conversations attached to the issue at this point in time.
          },
        },
        "unclassifiedConversationsCount": "A String", # Number of analyzed conversations for which no issue was applicable at this point in time.
      },
      "updateTime": "A String", # Output only. The most recent time at which the issue model was updated.
    },
  ],
}

patch(name, body=None, updateMask=None, x__xgafv=None)

Updates an issue model.

Args:
  name: string, Immutable. The resource name of the issue model. Format: projects/{project}/locations/{location}/issueModels/{issue_model} (required)
  body: object, The request body.
    The object takes the form of:

{ # The issue model resource.
  "createTime": "A String", # Output only. The time at which this issue model was created.
  "displayName": "A String", # The representative name for the issue model.
  "inputDataConfig": { # Configs for the input data used to create the issue model. # Configs for the input data that used to create the issue model.
    "filter": "A String", # A filter to reduce the conversations used for training the model to a specific subset.
    "medium": "A String", # Medium of conversations used in training data. This field is being deprecated. To specify the medium to be used in training a new issue model, set the `medium` field on `filter`.
    "trainingConversationsCount": "A String", # Output only. Number of conversations used in training. Output only.
  },
  "issueCount": "A String", # Output only. Number of issues in this issue model.
  "languageCode": "A String", # Language of the model.
  "modelType": "A String", # Type of the model.
  "name": "A String", # Immutable. The resource name of the issue model. Format: projects/{project}/locations/{location}/issueModels/{issue_model}
  "state": "A String", # Output only. State of the model.
  "trainingStats": { # Aggregated statistics about an issue model. # Output only. Immutable. The issue model's label statistics on its training data.
    "analyzedConversationsCount": "A String", # Number of conversations the issue model has analyzed at this point in time.
    "issueStats": { # Statistics on each issue. Key is the issue's resource name.
      "a_key": { # Aggregated statistics about an issue.
        "displayName": "A String", # Display name of the issue.
        "issue": "A String", # Issue resource. Format: projects/{project}/locations/{location}/issueModels/{issue_model}/issues/{issue}
        "labeledConversationsCount": "A String", # Number of conversations attached to the issue at this point in time.
      },
    },
    "unclassifiedConversationsCount": "A String", # Number of analyzed conversations for which no issue was applicable at this point in time.
  },
  "updateTime": "A String", # Output only. The most recent time at which the issue model was updated.
}

  updateMask: string, The list of fields to be updated.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # The issue model resource.
  "createTime": "A String", # Output only. The time at which this issue model was created.
  "displayName": "A String", # The representative name for the issue model.
  "inputDataConfig": { # Configs for the input data used to create the issue model. # Configs for the input data that used to create the issue model.
    "filter": "A String", # A filter to reduce the conversations used for training the model to a specific subset.
    "medium": "A String", # Medium of conversations used in training data. This field is being deprecated. To specify the medium to be used in training a new issue model, set the `medium` field on `filter`.
    "trainingConversationsCount": "A String", # Output only. Number of conversations used in training. Output only.
  },
  "issueCount": "A String", # Output only. Number of issues in this issue model.
  "languageCode": "A String", # Language of the model.
  "modelType": "A String", # Type of the model.
  "name": "A String", # Immutable. The resource name of the issue model. Format: projects/{project}/locations/{location}/issueModels/{issue_model}
  "state": "A String", # Output only. State of the model.
  "trainingStats": { # Aggregated statistics about an issue model. # Output only. Immutable. The issue model's label statistics on its training data.
    "analyzedConversationsCount": "A String", # Number of conversations the issue model has analyzed at this point in time.
    "issueStats": { # Statistics on each issue. Key is the issue's resource name.
      "a_key": { # Aggregated statistics about an issue.
        "displayName": "A String", # Display name of the issue.
        "issue": "A String", # Issue resource. Format: projects/{project}/locations/{location}/issueModels/{issue_model}/issues/{issue}
        "labeledConversationsCount": "A String", # Number of conversations attached to the issue at this point in time.
      },
    },
    "unclassifiedConversationsCount": "A String", # Number of analyzed conversations for which no issue was applicable at this point in time.
  },
  "updateTime": "A String", # Output only. The most recent time at which the issue model was updated.
}

undeploy(name, body=None, x__xgafv=None)

Undeploys an issue model. An issue model can not be used in analysis after it has been undeployed.

Args:
name: string, Required. The issue model to undeploy. (required)
body: object, The request body.
The object takes the form of:

{ # The request to undeploy an issue model.
"name": "A String", # Required. The issue model to undeploy.
}

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.
},
}

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Instance Methods

Method Details