vapi-client 0.4.2

/*
 * Vapi API
 *
 * Voice AI for developers.
 *
 * The version of the OpenAPI document: 1.0
 *
 * Generated by: https://openapi-generator.tech
 */

use crate::models;
use serde::{Deserialize, Serialize};

#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
pub struct CustomLlmModel {
    /// This is the starting state for the conversation.
    #[serde(rename = "messages", skip_serializing_if = "Option::is_none")]
    pub messages: Option<Vec<models::OpenAiMessage>>,
    /// These are the tools that the assistant can use during the call. To use existing tools, use `toolIds`.  Both `tools` and `toolIds` can be used together.
    #[serde(rename = "tools", skip_serializing_if = "Option::is_none")]
    pub tools: Option<Vec<models::AnyscaleModelToolsInner>>,
    /// These are the tools that the assistant can use during the call. To use transient tools, use `tools`.  Both `tools` and `toolIds` can be used together.
    #[serde(rename = "toolIds", skip_serializing_if = "Option::is_none")]
    pub tool_ids: Option<Vec<String>>,
    #[serde(rename = "knowledgeBase", skip_serializing_if = "Option::is_none")]
    pub knowledge_base: Option<models::CreateCustomKnowledgeBaseDto>,
    /// This is the ID of the knowledge base the model will use.
    #[serde(rename = "knowledgeBaseId", skip_serializing_if = "Option::is_none")]
    pub knowledge_base_id: Option<String>,
    /// This is the provider that will be used for the model. Any service, including your own server, that is compatible with the OpenAI API can be used.
    #[serde(rename = "provider")]
    pub provider: ProviderTrue,
    /// This determines whether metadata is sent in requests to the custom provider.  - `off` will not send any metadata. payload will look like `{ messages }` - `variable` will send `assistant.metadata` as a variable on the payload. payload will look like `{ messages, metadata }` - `destructured` will send `assistant.metadata` fields directly on the payload. payload will look like `{ messages, ...metadata }`  Further, `variable` and `destructured` will send `call`, `phoneNumber`, and `customer` objects in the payload.  Default is `variable`.
    #[serde(rename = "metadataSendMode", skip_serializing_if = "Option::is_none")]
    pub metadata_send_mode: Option<MetadataSendModeTrue>,
    /// These is the URL we'll use for the OpenAI client's `baseURL`. Ex. https://openrouter.ai/api/v1
    #[serde(rename = "url")]
    pub url: String,
    /// This sets the timeout for the connection to the custom provider without needing to stream any tokens back. Default is 20 seconds.
    #[serde(rename = "timeoutSeconds", skip_serializing_if = "Option::is_none")]
    pub timeout_seconds: Option<f64>,
    /// This is the name of the model. Ex. cognitivecomputations/dolphin-mixtral-8x7b
    #[serde(rename = "model")]
    pub model: String,
    /// This is the temperature that will be used for calls. Default is 0 to leverage caching for lower latency.
    #[serde(rename = "temperature", skip_serializing_if = "Option::is_none")]
    pub temperature: Option<f64>,
    /// This is the max number of tokens that the assistant will be allowed to generate in each turn of the conversation. Default is 250.
    #[serde(rename = "maxTokens", skip_serializing_if = "Option::is_none")]
    pub max_tokens: Option<f64>,
    /// This determines whether we detect user's emotion while they speak and send it as an additional info to model.  Default `false` because the model is usually are good at understanding the user's emotion from text.  @default false
    #[serde(
        rename = "emotionRecognitionEnabled",
        skip_serializing_if = "Option::is_none"
    )]
    pub emotion_recognition_enabled: Option<bool>,
    /// This sets how many turns at the start of the conversation to use a smaller, faster model from the same provider before switching to the primary model. Example, gpt-3.5-turbo if provider is openai.  Default is 0.  @default 0
    #[serde(rename = "numFastTurns", skip_serializing_if = "Option::is_none")]
    pub num_fast_turns: Option<f64>,
}

impl CustomLlmModel {
    pub fn new(provider: ProviderTrue, url: String, model: String) -> CustomLlmModel {
        CustomLlmModel {
            messages: None,
            tools: None,
            tool_ids: None,
            knowledge_base: None,
            knowledge_base_id: None,
            provider,
            metadata_send_mode: None,
            url,
            timeout_seconds: None,
            model,
            temperature: None,
            max_tokens: None,
            emotion_recognition_enabled: None,
            num_fast_turns: None,
        }
    }
}
/// This is the provider that will be used for the model. Any service, including your own server, that is compatible with the OpenAI API can be used.
#[derive(Clone, Copy, Debug, Eq, PartialEq, Ord, PartialOrd, Hash, Serialize, Deserialize)]
pub enum ProviderTrue {
    #[serde(rename = "custom-llm")]
    CustomLlm,
}

impl Default for ProviderTrue {
    fn default() -> ProviderTrue {
        Self::CustomLlm
    }
}
/// This determines whether metadata is sent in requests to the custom provider.  - `off` will not send any metadata. payload will look like `{ messages }` - `variable` will send `assistant.metadata` as a variable on the payload. payload will look like `{ messages, metadata }` - `destructured` will send `assistant.metadata` fields directly on the payload. payload will look like `{ messages, ...metadata }`  Further, `variable` and `destructured` will send `call`, `phoneNumber`, and `customer` objects in the payload.  Default is `variable`.
#[derive(Clone, Copy, Debug, Eq, PartialEq, Ord, PartialOrd, Hash, Serialize, Deserialize)]
pub enum MetadataSendModeTrue {
    #[serde(rename = "off")]
    Off,
    #[serde(rename = "variable")]
    Variable,
    #[serde(rename = "destructured")]
    Destructured,
}

impl Default for MetadataSendModeTrue {
    fn default() -> MetadataSendModeTrue {
        Self::Off
    }
}