vapi_client/models/custom_llm_model.rs
1/*
2 * Vapi API
3 *
4 * Voice AI for developers.
5 *
6 * The version of the OpenAPI document: 1.0
7 *
8 * Generated by: https://openapi-generator.tech
9 */
10
11use crate::models;
12use serde::{Deserialize, Serialize};
13
14#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
15pub struct CustomLlmModel {
16 /// This is the starting state for the conversation.
17 #[serde(rename = "messages", skip_serializing_if = "Option::is_none")]
18 pub messages: Option<Vec<models::OpenAiMessage>>,
19 /// 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.
20 #[serde(rename = "tools", skip_serializing_if = "Option::is_none")]
21 pub tools: Option<Vec<models::AnyscaleModelToolsInner>>,
22 /// 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.
23 #[serde(rename = "toolIds", skip_serializing_if = "Option::is_none")]
24 pub tool_ids: Option<Vec<String>>,
25 #[serde(rename = "knowledgeBase", skip_serializing_if = "Option::is_none")]
26 pub knowledge_base: Option<Box<models::AnyscaleModelKnowledgeBase>>,
27 /// This is the ID of the knowledge base the model will use.
28 #[serde(rename = "knowledgeBaseId", skip_serializing_if = "Option::is_none")]
29 pub knowledge_base_id: Option<String>,
30 /// 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.
31 #[serde(rename = "provider")]
32 pub provider: Provider,
33 /// 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`.
34 #[serde(rename = "metadataSendMode", skip_serializing_if = "Option::is_none")]
35 pub metadata_send_mode: Option<MetadataSendMode>,
36 /// These is the URL we'll use for the OpenAI client's `baseURL`. Ex. https://openrouter.ai/api/v1
37 #[serde(rename = "url")]
38 pub url: String,
39 /// This sets the timeout for the connection to the custom provider without needing to stream any tokens back. Default is 20 seconds.
40 #[serde(rename = "timeoutSeconds", skip_serializing_if = "Option::is_none")]
41 pub timeout_seconds: Option<f64>,
42 /// This is the name of the model. Ex. cognitivecomputations/dolphin-mixtral-8x7b
43 #[serde(rename = "model")]
44 pub model: String,
45 /// This is the temperature that will be used for calls. Default is 0 to leverage caching for lower latency.
46 #[serde(rename = "temperature", skip_serializing_if = "Option::is_none")]
47 pub temperature: Option<f64>,
48 /// This is the max number of tokens that the assistant will be allowed to generate in each turn of the conversation. Default is 250.
49 #[serde(rename = "maxTokens", skip_serializing_if = "Option::is_none")]
50 pub max_tokens: Option<f64>,
51 /// 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
52 #[serde(rename = "emotionRecognitionEnabled", skip_serializing_if = "Option::is_none")]
53 pub emotion_recognition_enabled: Option<bool>,
54 /// 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
55 #[serde(rename = "numFastTurns", skip_serializing_if = "Option::is_none")]
56 pub num_fast_turns: Option<f64>,
57}
58
59impl CustomLlmModel {
60 pub fn new(provider: Provider, url: String, model: String) -> CustomLlmModel {
61 CustomLlmModel {
62 messages: None,
63 tools: None,
64 tool_ids: None,
65 knowledge_base: None,
66 knowledge_base_id: None,
67 provider,
68 metadata_send_mode: None,
69 url,
70 timeout_seconds: None,
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}
107