Google Cloud Dialogflow V2 Client - Class ConversationModelEvaluation (1.17.1)

Reference documentation and code samples for the Google Cloud Dialogflow V2 Client class ConversationModelEvaluation.

Represents evaluation result of a conversation model.

Generated from protobuf message google.cloud.dialogflow.v2.ConversationModelEvaluation

Namespace

Google \ Cloud \ Dialogflow \ V2

Methods

__construct

Constructor.

Parameters
Name Description
data array

Optional. Data for populating the Message object.

↳ name string

The resource name of the evaluation. Format: projects/<Project ID>/conversationModels/<Conversation Model ID>/evaluations/<Evaluation ID>

↳ display_name string

Optional. The display name of the model evaluation. At most 64 bytes long.

↳ evaluation_config EvaluationConfig

Optional. The configuration of the evaluation task.

↳ create_time Google\Protobuf\Timestamp

Output only. Creation time of this model.

↳ smart_reply_metrics SmartReplyMetrics

Output only. Only available when model is for smart reply.

↳ raw_human_eval_template_csv string

Output only. Human eval template in csv format. It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context.

getName

The resource name of the evaluation. Format: projects/<Project ID>/conversationModels/<Conversation Model ID>/evaluations/<Evaluation ID>

Returns
Type Description
string

setName

The resource name of the evaluation. Format: projects/<Project ID>/conversationModels/<Conversation Model ID>/evaluations/<Evaluation ID>

Parameter
Name Description
var string
Returns
Type Description
$this

getDisplayName

Optional. The display name of the model evaluation. At most 64 bytes long.

Returns
Type Description
string

setDisplayName

Optional. The display name of the model evaluation. At most 64 bytes long.

Parameter
Name Description
var string
Returns
Type Description
$this

getEvaluationConfig

Optional. The configuration of the evaluation task.

Returns
Type Description
EvaluationConfig|null

hasEvaluationConfig

clearEvaluationConfig

setEvaluationConfig

Optional. The configuration of the evaluation task.

Parameter
Name Description
var EvaluationConfig
Returns
Type Description
$this

getCreateTime

Output only. Creation time of this model.

Returns
Type Description
Google\Protobuf\Timestamp|null

hasCreateTime

clearCreateTime

setCreateTime

Output only. Creation time of this model.

Parameter
Name Description
var Google\Protobuf\Timestamp
Returns
Type Description
$this

getSmartReplyMetrics

Output only. Only available when model is for smart reply.

Returns
Type Description
SmartReplyMetrics|null

hasSmartReplyMetrics

setSmartReplyMetrics

Output only. Only available when model is for smart reply.

Parameter
Name Description
var SmartReplyMetrics
Returns
Type Description
$this

getRawHumanEvalTemplateCsv

Output only. Human eval template in csv format.

It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context.

Returns
Type Description
string

setRawHumanEvalTemplateCsv

Output only. Human eval template in csv format.

It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context.

Parameter
Name Description
var string
Returns
Type Description
$this

getMetrics

Returns
Type Description
string