Struct google_api_proto::google::cloud::dialogflow::v2::ConversationModelEvaluation

pub struct ConversationModelEvaluation {
    pub name: String,
    pub display_name: String,
    pub evaluation_config: Option<EvaluationConfig>,
    pub create_time: Option<Timestamp>,
    pub raw_human_eval_template_csv: String,
    pub metrics: Option<Metrics>,
}

Represents evaluation result of a conversation model.

Fields

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: Option<EvaluationConfig>

Optional. The configuration of the evaluation task.

create_time: Option<Timestamp>

Output only. Creation time of this model.

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.

metrics: Option<Metrics>

Metrics details.

Trait Implementations

impl Clone for ConversationModelEvaluation

fn clone(&self) -> ConversationModelEvaluation

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ConversationModelEvaluation

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for ConversationModelEvaluation

fn default() -> Self

Returns the “default value” for a type.

impl Message for ConversationModelEvaluation

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for ConversationModelEvaluation

fn eq(&self, other: &ConversationModelEvaluation) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for ConversationModelEvaluation