Documentation Index
Fetch the complete documentation index at: https://docs.trymirai.com/llms.txt
Use this file to discover all available pages before exploring further.
In this example, we will get a reply to a specific list of messages from a cloud model.
- Python
- Swift
- TypeScript
- Rust
Paste into main.py
import asyncio
from uzu import ChatConfig, ChatMessage, ChatReplyConfig, Engine, EngineConfig, ReasoningEffort
async def main() -> None:
engine_config = EngineConfig.create().with_openai_api_key("OPENAI_API_KEY")
engine = await Engine.create(engine_config)
model = await engine.model("gpt-5")
if model is None:
raise RuntimeError("Model not found")
messages = [
ChatMessage.system().with_reasoning_effort(ReasoningEffort.Low),
ChatMessage.user().with_text("How LLMs work"),
]
session = await engine.chat(model, ChatConfig.create())
replies = await session.reply(messages, ChatReplyConfig.create())
if replies:
message = replies[0].message
print(f"Reasoning: {message.reasoning}")
print(f"Text: {message.text}")
if __name__ == "__main__":
asyncio.run(main())
Paste the snippet
import Uzu
public func runChatCloud() async throws {
let engineConfig = EngineConfig.create().withOpenaiApiKey(openaiApiKey: "OPENAI_API_KEY")
let engine = try await Engine.create(config: engineConfig)
guard let model = try await engine.model(identifier: "Qwen/Qwen3-0.6B") else {
return
}
let messages = [
ChatMessage.system().withReasoningEffort(reasoningEffort: .low),
ChatMessage.user().withText(text: "How LLMs work")
]
let session = try await engine.chat(model: model, config: .create())
let reply = try await session.reply(input: messages, config: .create())
guard let message = reply.last?.message else {
return
}
print("Reasoning: \(message.reasoning() ?? "empty")")
print("Text: \(message.text() ?? "empty")")
}
Initialize a tsconfig.json
{
"compilerOptions": {
"target": "es2020",
"module": "commonjs",
"moduleResolution": "node",
"strict": true,
"esModuleInterop": true,
"outDir": "dist",
"types": [
"node"
]
},
"include": [
"*.ts"
]
}
Create main.ts
import { ChatConfig, ChatMessage, ChatReplyConfig, Engine, EngineConfig, ReasoningEffort } from '@trymirai/uzu';
async function main() {
let engineConfig = EngineConfig.create().withOpenaiApiKey('OPENAI_API_KEY');
let engine = await Engine.create(engineConfig);
let model = await engine.model('gpt-5');
if (!model) {
throw new Error('Model not found');
}
let messages = [
ChatMessage.system().withReasoningEffort("Low" as ReasoningEffort),
ChatMessage.user().withText('How LLMs work')
];
let session = await engine.chat(model, ChatConfig.create());
let reply = await session.reply(messages, ChatReplyConfig.create());
let message = reply[0]?.message;
if (message) {
console.log('Reasoning: ', message.reasoning);
console.log('Text: ', message.text);
}
}
main().catch((error) => {
console.error(error);
});
Install dependencies
cargo add uzu --git https://github.com/trymirai/uzu
cargo add tokio --features full
Paste into src/main.rs
use uzu::{
engine::{Engine, EngineConfig},
types::{
basic::ReasoningEffort,
session::chat::{ChatConfig, ChatMessage, ChatReplyConfig},
},
};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let engine_config = EngineConfig::default().with_openai_api_key("OPENAI_API_KEY".to_string());
let engine = Engine::new(engine_config).await?;
let model = engine.model("gpt-5".to_string()).await?.ok_or("Model not found")?;
let messages = vec![
ChatMessage::system().with_reasoning_effort(ReasoningEffort::Low),
ChatMessage::user().with_text("How LLMs work".to_string()),
];
let session = engine.chat(model, ChatConfig::default()).await?;
let replies = session.reply(messages, ChatReplyConfig::default()).await?;
if let Some(reply) = replies.first() {
println!("Reasoning: {}", reply.message.reasoning().unwrap_or_default());
println!("Text: {}", reply.message.text().unwrap_or_default());
}
Ok(())
}