Dialogflow API . projects . conversationModels

Instance Methods

evaluations()

Returns the evaluations Resource.

close()

Close httplib2 connections.

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

Creates a model. This method is a [long-running operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations). The returned `Operation` type has the following method-specific fields: - `metadata`: CreateConversationModelOperationMetadata - `response`: ConversationModel

delete(name, x__xgafv=None)

Deletes a model. This method is a [long-running operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations). The returned `Operation` type has the following method-specific fields: - `metadata`: DeleteConversationModelOperationMetadata - `response`: An [Empty message](https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty)

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

Deploys a model. If a model is already deployed, deploying it has no effect. A model can only serve prediction requests after it gets deployed. For article suggestion, custom model will not be used unless it is deployed. This method is a [long-running operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations). The returned `Operation` type has the following method-specific fields: - `metadata`: DeployConversationModelOperationMetadata - `response`: An [Empty message](https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty)

get(name, x__xgafv=None)

Gets conversation model.

list(parent, pageSize=None, pageToken=None, x__xgafv=None)

Lists conversation models.

list_next()

Retrieves the next page of results.

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

Undeploys a model. If the model is not deployed this method has no effect. If the model is currently being used: - For article suggestion, article suggestion will fallback to the default model if model is undeployed. This method is a [long-running operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations). The returned `Operation` type has the following method-specific fields: - `metadata`: UndeployConversationModelOperationMetadata - `response`: An [Empty message](https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty)

Method Details

close()
Close httplib2 connections.
create(parent, body=None, x__xgafv=None)
Creates a model. This method is a [long-running operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations). The returned `Operation` type has the following method-specific fields: - `metadata`: CreateConversationModelOperationMetadata - `response`: ConversationModel

Args:
  parent: string, The project to create conversation model for. Format: `projects/` (required)
  body: object, The request body.
    The object takes the form of:

{ # Represents a conversation model.
  "articleSuggestionModelMetadata": { # Metadata for article suggestion models. # Metadata for article suggestion models.
    "trainingModelType": "A String", # Optional. Type of the article suggestion model. If not provided, model_type is used.
  },
  "createTime": "A String", # Output only. Creation time of this model.
  "datasets": [ # Required. Datasets used to create model.
    { # InputDataset used to create model or do evaluation. NextID:5
      "dataset": "A String", # Required. ConversationDataset resource name. Format: `projects//locations//conversationDatasets/`
    },
  ],
  "displayName": "A String", # Required. The display name of the model. At most 64 bytes long.
  "languageCode": "A String", # Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag. Example: "en-US".
  "name": "A String", # ConversationModel resource name. Format: `projects//conversationModels/`
  "smartReplyModelMetadata": { # Metadata for smart reply models. # Metadata for smart reply models.
    "trainingModelType": "A String", # Optional. Type of the smart reply model. If not provided, model_type is used.
  },
  "state": "A String", # Output only. State of the model. A model can only serve prediction requests after it gets deployed.
}

  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 a model. This method is a [long-running operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations). The returned `Operation` type has the following method-specific fields: - `metadata`: DeleteConversationModelOperationMetadata - `response`: An [Empty message](https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty)

Args:
  name: string, Required. The conversation model to delete. Format: `projects//conversationModels/` (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 a model. If a model is already deployed, deploying it has no effect. A model can only serve prediction requests after it gets deployed. For article suggestion, custom model will not be used unless it is deployed. This method is a [long-running operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations). The returned `Operation` type has the following method-specific fields: - `metadata`: DeployConversationModelOperationMetadata - `response`: An [Empty message](https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty)

Args:
  name: string, Required. The conversation model to deploy. Format: `projects//conversationModels/` (required)
  body: object, The request body.
    The object takes the form of:

{ # The request message for ConversationModels.DeployConversationModel
}

  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 conversation model.

Args:
  name: string, Required. The conversation model to retrieve. Format: `projects//conversationModels/` (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Represents a conversation model.
  "articleSuggestionModelMetadata": { # Metadata for article suggestion models. # Metadata for article suggestion models.
    "trainingModelType": "A String", # Optional. Type of the article suggestion model. If not provided, model_type is used.
  },
  "createTime": "A String", # Output only. Creation time of this model.
  "datasets": [ # Required. Datasets used to create model.
    { # InputDataset used to create model or do evaluation. NextID:5
      "dataset": "A String", # Required. ConversationDataset resource name. Format: `projects//locations//conversationDatasets/`
    },
  ],
  "displayName": "A String", # Required. The display name of the model. At most 64 bytes long.
  "languageCode": "A String", # Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag. Example: "en-US".
  "name": "A String", # ConversationModel resource name. Format: `projects//conversationModels/`
  "smartReplyModelMetadata": { # Metadata for smart reply models. # Metadata for smart reply models.
    "trainingModelType": "A String", # Optional. Type of the smart reply model. If not provided, model_type is used.
  },
  "state": "A String", # Output only. State of the model. A model can only serve prediction requests after it gets deployed.
}
list(parent, pageSize=None, pageToken=None, x__xgafv=None)
Lists conversation models.

Args:
  parent: string, Required. The project to list all conversation models for. Format: `projects/` (required)
  pageSize: integer, Optional. Maximum number of conversation models to return in a single page. By default 100 and at most 1000.
  pageToken: string, Optional. The next_page_token value returned from a previous list request.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # The response message for ConversationModels.ListConversationModels
  "conversationModels": [ # The list of models to return.
    { # Represents a conversation model.
      "articleSuggestionModelMetadata": { # Metadata for article suggestion models. # Metadata for article suggestion models.
        "trainingModelType": "A String", # Optional. Type of the article suggestion model. If not provided, model_type is used.
      },
      "createTime": "A String", # Output only. Creation time of this model.
      "datasets": [ # Required. Datasets used to create model.
        { # InputDataset used to create model or do evaluation. NextID:5
          "dataset": "A String", # Required. ConversationDataset resource name. Format: `projects//locations//conversationDatasets/`
        },
      ],
      "displayName": "A String", # Required. The display name of the model. At most 64 bytes long.
      "languageCode": "A String", # Language code for the conversation model. If not specified, the language is en-US. Language at ConversationModel should be set for all non en-us languages. This should be a [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag. Example: "en-US".
      "name": "A String", # ConversationModel resource name. Format: `projects//conversationModels/`
      "smartReplyModelMetadata": { # Metadata for smart reply models. # Metadata for smart reply models.
        "trainingModelType": "A String", # Optional. Type of the smart reply model. If not provided, model_type is used.
      },
      "state": "A String", # Output only. State of the model. A model can only serve prediction requests after it gets deployed.
    },
  ],
  "nextPageToken": "A String", # Token to retrieve the next page of results, or empty if there are no more results in the list.
}
list_next()
Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call 'execute()' on to request the next
          page. Returns None if there are no more items in the collection.
        
undeploy(name, body=None, x__xgafv=None)
Undeploys a model. If the model is not deployed this method has no effect. If the model is currently being used: - For article suggestion, article suggestion will fallback to the default model if model is undeployed. This method is a [long-running operation](https://cloud.google.com/dialogflow/es/docs/how/long-running-operations). The returned `Operation` type has the following method-specific fields: - `metadata`: UndeployConversationModelOperationMetadata - `response`: An [Empty message](https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty)

Args:
  name: string, Required. The conversation model to undeploy. Format: `projects//conversationModels/` (required)
  body: object, The request body.
    The object takes the form of:

{ # The request message for ConversationModels.UndeployConversationModel
}

  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.
  },
}