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use super::{
Client, ExtraConfig, VertexAIClient, Model, PromptType,
SendData, TokensCountFactors,
};
use super::gemini::{build_body, send_message, send_message_streaming};
use crate::{render::ReplyHandler, utils::PromptKind};
use anyhow::Result;
use async_trait::async_trait;
use reqwest::{Client as ReqwestClient, RequestBuilder};
use serde::Deserialize;
const MODELS: [(&str, usize, &str); 2] = [
("gemini-pro", 32760, "text"),
("gemini-pro-vision", 16384, "text,vision"),
];
const TOKENS_COUNT_FACTORS: TokensCountFactors = (5, 2);
#[derive(Debug, Clone, Deserialize, Default)]
pub struct VertexAIConfig {
pub name: Option<String>,
pub api_base: Option<String>,
pub api_key: Option<String>,
pub extra: Option<ExtraConfig>,
}
#[async_trait]
impl Client for VertexAIClient {
client_common_fns!();
async fn send_message_inner(&self, client: &ReqwestClient, data: SendData) -> Result<String> {
let builder = self.request_builder(client, data)?;
send_message(builder).await
}
async fn send_message_streaming_inner(
&self,
client: &ReqwestClient,
handler: &mut ReplyHandler,
data: SendData,
) -> Result<()> {
let builder = self.request_builder(client, data)?;
send_message_streaming(builder, handler).await
}
}
impl VertexAIClient {
config_get_fn!(api_base, get_api_base);
config_get_fn!(api_key, get_api_key);
pub const PROMPTS: [PromptType<'static>; 2] = [
("api_base", "API Base:", true, PromptKind::String),
("api_key", "API Key:", true, PromptKind::String),
];
pub fn list_models(local_config: &VertexAIConfig) -> Vec<Model> {
let client_name = Self::name(local_config);
MODELS
.into_iter()
.map(|(name, max_tokens, capabilities)| {
Model::new(client_name, name)
.set_capabilities(capabilities.into())
.set_max_tokens(Some(max_tokens))
.set_tokens_count_factors(TOKENS_COUNT_FACTORS)
})
.collect()
}
fn request_builder(&self, client: &ReqwestClient, data: SendData) -> Result<RequestBuilder> {
let api_base = self.get_api_base()?;
let api_key = self.get_api_key()?;
let func = match data.stream {
true => "streamGenerateContent",
false => "generateContent",
};
let body = build_body(data, self.model.name.clone())?;
let model = self.model.name.clone();
let url = format!("{api_base}/{}:{}", model, func);
debug!("VertexAI Request: {url} {body}");
let builder = client.post(url).bearer_auth(api_key).json(&body);
Ok(builder)
}
}
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