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use super::openai::{openai_build_body, openai_tokens_formula};
use super::{ExtraConfig, LocalAIClient, ModelInfo, PromptKind, PromptType, SendData};
use anyhow::Result;
use async_trait::async_trait;
use reqwest::{Client as ReqwestClient, RequestBuilder};
use serde::Deserialize;
#[derive(Debug, Clone, Deserialize)]
pub struct LocalAIConfig {
pub name: Option<String>,
pub api_base: String,
pub api_key: Option<String>,
pub chat_endpoint: Option<String>,
pub models: Vec<LocalAIModel>,
pub extra: Option<ExtraConfig>,
}
#[derive(Debug, Clone, Deserialize)]
pub struct LocalAIModel {
name: String,
max_tokens: Option<usize>,
}
openai_compatible_client!(LocalAIClient);
impl LocalAIClient {
config_get_fn!(api_key, get_api_key);
pub const PROMPTS: [PromptType<'static>; 4] = [
("api_base", "API Base:", true, PromptKind::String),
("api_key", "API Key:", false, PromptKind::String),
("models[].name", "Model Name:", true, PromptKind::String),
(
"models[].max_tokens",
"Max Tokens:",
false,
PromptKind::Integer,
),
];
pub fn list_models(local_config: &LocalAIConfig, index: usize) -> Vec<ModelInfo> {
let client = Self::name(local_config);
local_config
.models
.iter()
.map(|v| openai_tokens_formula(ModelInfo::new(index, client, &v.name).set_max_tokens(v.max_tokens)))
.collect()
}
fn request_builder(&self, client: &ReqwestClient, data: SendData) -> Result<RequestBuilder> {
let api_key = self.get_api_key().ok();
let body = openai_build_body(data, self.model_info.name.clone());
let chat_endpoint = self
.config
.chat_endpoint
.as_deref()
.unwrap_or("/chat/completions");
let url = format!("{}{chat_endpoint}", self.config.api_base);
let mut builder = client.post(url).json(&body);
if let Some(api_key) = api_key {
builder = builder.bearer_auth(api_key);
}
Ok(builder)
}
}
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