Struct StartSpeakingPlan

pub struct StartSpeakingPlan {
    pub wait_seconds: Option<f64>,
    pub smart_endpointing_enabled: Option<StartSpeakingPlanSmartEndpointingEnabled>,
    pub smart_endpointing_plan: Option<StartSpeakingPlanSmartEndpointingPlan>,
    pub custom_endpointing_rules: Option<Vec<StartSpeakingPlanCustomEndpointingRulesInner>>,
    pub transcription_endpointing_plan: Option<TranscriptionEndpointingPlan>,
}

Fields

wait_seconds: Option<f64>

This is how long assistant waits before speaking. Defaults to 0.4. This is the minimum it will wait but if there is latency is the pipeline, this minimum will be exceeded. This is intended as a stopgap in case the pipeline is moving too fast. Example: - If model generates tokens and voice generates bytes within 100ms, the pipeline still waits 300ms before outputting speech. Usage: - If the customer is taking long pauses, set this to a higher value. - If the assistant is accidentally jumping in too much, set this to a higher value. @default 0.4

smart_endpointing_enabled: Option<StartSpeakingPlanSmartEndpointingEnabled>

smart_endpointing_plan: Option<StartSpeakingPlanSmartEndpointingPlan>

custom_endpointing_rules: Option<Vec<StartSpeakingPlanCustomEndpointingRulesInner>>

These are the custom endpointing rules to set an endpointing timeout based on a regex on the customer’s speech or the assistant’s last message. Usage: - If you have yes/no questions like "are you interested in a loan?", you can set a shorter timeout. - If you have questions where the customer may pause to look up information like "what’s my account number?", you can set a longer timeout. - If you want to wait longer while customer is enumerating a list of numbers, you can set a longer timeout. These rules have the highest precedence and will override both smartEndpointingPlan and transcriptionEndpointingPlan when a rule is matched. The rules are evaluated in order and the first one that matches will be used. Order of precedence for endpointing: 1. customEndpointingRules (if any match) 2. smartEndpointingPlan (if set) 3. transcriptionEndpointingPlan @default []

transcription_endpointing_plan: Option<TranscriptionEndpointingPlan>

This determines how a customer speech is considered done (endpointing) using the transcription of customer’s speech. Once an endpoint is triggered, the request is sent to assistant.model. Note: This plan is only used if smartEndpointingPlan is not set. If both are provided, smartEndpointingPlan takes precedence. This plan will also be overridden by any matching customEndpointingRules.

Implementations

impl StartSpeakingPlan

pub fn new() -> StartSpeakingPlan

Trait Implementations

impl Clone for StartSpeakingPlan

fn clone(&self) -> StartSpeakingPlan

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for StartSpeakingPlan

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

Formats the value using the given formatter.

impl Default for StartSpeakingPlan

fn default() -> StartSpeakingPlan

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for StartSpeakingPlan

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for StartSpeakingPlan

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl Serialize for StartSpeakingPlan

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for StartSpeakingPlan