vapi_client/models/
custom_llm_model.rs

1/*
2 * Vapi API
3 *
4 * API for building voice assistants
5 *
6 * The version of the OpenAPI document: 1.0
7 *
8 * Generated by: https://openapi-generator.tech
9 */
10
11use serde::{Deserialize, Serialize};
12
13use crate::models;
14
15#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
16pub struct CustomLlmModel {
17    /// This is the starting state for the conversation.
18    #[serde(rename = "messages", skip_serializing_if = "Option::is_none")]
19    pub messages: Option<Vec<models::OpenAiMessage>>,
20    /// 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.
21    #[serde(rename = "tools", skip_serializing_if = "Option::is_none")]
22    pub tools: Option<Vec<models::AnyscaleModelToolsInner>>,
23    /// 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.
24    #[serde(rename = "toolIds", skip_serializing_if = "Option::is_none")]
25    pub tool_ids: Option<Vec<String>>,
26    #[serde(rename = "knowledgeBase", skip_serializing_if = "Option::is_none")]
27    pub knowledge_base: Option<models::AnyscaleModelKnowledgeBase>,
28    /// This is the ID of the knowledge base the model will use.
29    #[serde(rename = "knowledgeBaseId", skip_serializing_if = "Option::is_none")]
30    pub knowledge_base_id: Option<String>,
31    /// 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.
32    #[serde(rename = "provider")]
33    pub provider: Provider,
34    /// 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`.
35    #[serde(rename = "metadataSendMode", skip_serializing_if = "Option::is_none")]
36    pub metadata_send_mode: Option<MetadataSendMode>,
37    /// These is the URL we'll use for the OpenAI client's `baseURL`. Ex. https://openrouter.ai/api/v1
38    #[serde(rename = "url")]
39    pub url: String,
40    /// This is the name of the model. Ex. cognitivecomputations/dolphin-mixtral-8x7b
41    #[serde(rename = "model")]
42    pub model: String,
43    /// This is the temperature that will be used for calls. Default is 0 to leverage caching for lower latency.
44    #[serde(rename = "temperature", skip_serializing_if = "Option::is_none")]
45    pub temperature: Option<f64>,
46    /// This is the max number of tokens that the assistant will be allowed to generate in each turn of the conversation. Default is 250.
47    #[serde(rename = "maxTokens", skip_serializing_if = "Option::is_none")]
48    pub max_tokens: Option<f64>,
49    /// 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
50    #[serde(
51        rename = "emotionRecognitionEnabled",
52        skip_serializing_if = "Option::is_none"
53    )]
54    pub emotion_recognition_enabled: Option<bool>,
55    /// 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
56    #[serde(rename = "numFastTurns", skip_serializing_if = "Option::is_none")]
57    pub num_fast_turns: Option<f64>,
58}
59
60impl CustomLlmModel {
61    pub fn new(provider: Provider, url: String, model: String) -> CustomLlmModel {
62        CustomLlmModel {
63            messages: None,
64            tools: None,
65            tool_ids: None,
66            knowledge_base: None,
67            knowledge_base_id: None,
68            provider,
69            metadata_send_mode: None,
70            url,
71            model,
72            temperature: None,
73            max_tokens: None,
74            emotion_recognition_enabled: None,
75            num_fast_turns: None,
76        }
77    }
78}
79/// 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.
80#[derive(Clone, Copy, Debug, Eq, PartialEq, Ord, PartialOrd, Hash, Serialize, Deserialize)]
81pub enum Provider {
82    #[serde(rename = "custom-llm")]
83    CustomLlm,
84}
85
86impl Default for Provider {
87    fn default() -> Provider {
88        Self::CustomLlm
89    }
90}
91/// 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`.
92#[derive(Clone, Copy, Debug, Eq, PartialEq, Ord, PartialOrd, Hash, Serialize, Deserialize)]
93pub enum MetadataSendMode {
94    #[serde(rename = "off")]
95    Off,
96    #[serde(rename = "variable")]
97    Variable,
98    #[serde(rename = "destructured")]
99    Destructured,
100}
101
102impl Default for MetadataSendMode {
103    fn default() -> MetadataSendMode {
104        Self::Off
105    }
106}
vapi_client/models/custom_llm_model.rs

vapi_client/models/
custom_llm_model.rs
