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use llm_connector::{LlmClient, types::{ChatRequest, Message, Role, Tool, Function}};
use serde_json::{json, Value};
use serde::Deserialize;
use std::fs::read_to_string;
#[derive(Deserialize, Clone, Debug)]
struct Config {
base_url: String,
key: String,
model: String,
}
async fn get_horoscope(sign: &str) -> String {
format!("{sign}: Next Tuesday you will befriend a baby otter.")
}
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let config = read_to_string("config.json")?;
let config: Config = serde_json::from_str(&config)?;
let client = LlmClient::openai_with_config(
&config.key,
Some(&config.base_url),
Some(300),
None,
)?;
let mut tools: Vec<Tool> = Vec::new();
tools.push(Tool {
tool_type: "function".into(),
function: Function {
name: "get_horoscope".into(),
description: Some("Get today's horoscope for an astrological sign.".into()),
parameters: json!({
"sign": {
"type": "string",
"description": "An astrological sign like Taurus or Aquarius."
}
}),
},
});
let mut req = ChatRequest {
model: config.model,
messages: vec![
Message::text(Role::System, "You will comply with all horoscope requests using tools."),
Message::text(Role::User, "I am an Aries. What is my horoscope for today?"),
],
tools: Some(tools),
//temperature: Some(0.9),
..Default::default()
};
let mut response = client.chat(&req).await?;
for choice in response.choices.clone() {
if let Some(reason) = choice.finish_reason {
match reason.as_str() {
"tool_calls" => {
if let Some(calls) = choice.message.clone().tool_calls {
for call in calls {
match call.function.name.as_str() {
"get_horoscope" => {
let v: Value = serde_json::from_str(call.function.arguments.as_str())?;
req.messages.push(choice.message.clone());
let v = v["sign"].as_str().unwrap_or_default();
let val: String = get_horoscope(v).await;
req.messages.push(Message::tool(val, call.id));
response = client.chat(&req).await?;
},
_ => (),
}
}
}
},
_ => (),
}
}
}
println!("Response: {}", &response.content);
Ok(())
}
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