uncloseai.com/public/languages/rust/examples/basic.rs

298 lines
8.6 KiB
Rust

// PUBLIC DOMAIN - NO LICENSE, NO WARRANTY
// Copyright 2025 TimeHexOn & foxhop & russell@unturf
// https://www.permacomputer.com
/// UncloseAI Rust Library - Usage Examples
///
/// Demonstrates how to use the UncloseAI library for:
/// - Model discovery
/// - Non-streaming chat completions
/// - Streaming chat completions
/// - Text-to-speech generation
use uncloseai::{UncloseAI, ChatMessage, ChatOptions, UncloseAIError};
use futures_util::StreamExt;
use std::fs::File;
use std::io::Write;
/// Example: Discover available models
async fn example_model_discovery() -> Result<(), Box<dyn std::error::Error>> {
println!("=== Model Discovery Example ===\n");
// Initialize client (auto-discovers from environment variables)
let client = UncloseAI::new(Some(uncloseai::UncloseAIConfig {
debug: true,
..Default::default()
})).await?;
// List discovered models
let models = client.list_models();
println!("\nDiscovered {} model(s):", models.len());
for model in models {
println!(" - {}", model.id);
println!(" Endpoint: {}", model.endpoint);
println!(" Max tokens: {}", model.max_tokens);
}
println!();
Ok(())
}
/// Example: Non-streaming chat completion
async fn example_chat() -> Result<(), Box<dyn std::error::Error>> {
println!("=== Non-Streaming Chat Example ===\n");
let client = UncloseAI::new(None).await?;
let response = client.chat(
"auto", // Use first available model
vec![
ChatMessage::system("You are a helpful AI assistant."),
ChatMessage::user("Explain quantum computing in one sentence."),
],
Some(ChatOptions {
max_tokens: Some(100),
..Default::default()
})
).await?;
// Extract and print the response
let content = &response.choices[0].message.content;
println!("Assistant: {}\n", content);
Ok(())
}
/// Example: Streaming chat completion
async fn example_chat_streaming() -> Result<(), Box<dyn std::error::Error>> {
println!("=== Streaming Chat Example ===\n");
let client = UncloseAI::new(None).await?;
println!("User: Write a short haiku about programming.\n");
print!("Assistant: ");
let mut stream = client.chat_stream(
"auto",
vec![
ChatMessage::system("You are a poetic AI that writes haikus."),
ChatMessage::user("Write a short haiku about programming."),
],
Some(ChatOptions {
max_tokens: Some(100),
..Default::default()
})
).await?;
// Stream and print chunks
while let Some(chunk) = stream.next().await {
match chunk {
Ok(chunk) => {
if let Some(choice) = chunk.choices.first() {
if let Some(content) = &choice.delta.content {
print!("{}", content);
std::io::stdout().flush()?;
}
}
}
Err(e) => {
println!("\nError: {}", e);
break;
}
}
}
println!("\n");
Ok(())
}
/// Example: Streaming chat with conversation context
async fn example_chat_streaming_with_context() -> Result<(), Box<dyn std::error::Error>> {
println!("=== Streaming Chat with Context ===\n");
let client = UncloseAI::new(None).await?;
// Simulated conversation
let mut messages = vec![
ChatMessage::system("You are a helpful coding assistant."),
ChatMessage::user("What is Rust used for?"),
];
println!("User: What is Rust used for?\n");
print!("Assistant: ");
// First response
let mut full_response = String::new();
let mut stream = client.chat_stream(
"auto",
messages.clone(),
Some(ChatOptions {
max_tokens: Some(150),
..Default::default()
})
).await?;
while let Some(chunk) = stream.next().await {
if let Ok(chunk) = chunk {
if let Some(choice) = chunk.choices.first() {
if let Some(content) = &choice.delta.content {
full_response.push_str(content);
print!("{}", content);
std::io::stdout().flush()?;
}
}
}
}
println!("\n");
// Add assistant response to context
messages.push(ChatMessage::assistant(full_response));
messages.push(ChatMessage::user("Can you give me a simple example?"));
println!("User: Can you give me a simple example?\n");
print!("Assistant: ");
// Second response with context
let mut stream = client.chat_stream(
"auto",
messages,
Some(ChatOptions {
max_tokens: Some(200),
..Default::default()
})
).await?;
while let Some(chunk) = stream.next().await {
if let Ok(chunk) = chunk {
if let Some(choice) = chunk.choices.first() {
if let Some(content) = &choice.delta.content {
print!("{}", content);
std::io::stdout().flush()?;
}
}
}
}
println!("\n");
Ok(())
}
/// Example: Text-to-speech generation
async fn example_tts() -> Result<(), Box<dyn std::error::Error>> {
println!("=== Text-to-Speech Example ===\n");
let client = UncloseAI::new(None).await?;
// Generate speech
let audio_data = client.tts(
"Hello from UncloseAI Rust library! This demonstrates text to speech generation.",
"alloy", // Options: alloy, echo, fable, onyx, nova, shimmer
"tts-1"
).await?;
// Save to file
let mut file = File::create("speech.mp3")?;
file.write_all(&audio_data)?;
println!("[OK] Speech generated: speech.mp3 ({} bytes)\n", audio_data.len());
Ok(())
}
/// Example: Using different models for different tasks
async fn example_multiple_models() -> Result<(), Box<dyn std::error::Error>> {
println!("=== Multiple Models Example ===\n");
let client = UncloseAI::new(None).await?;
let models = client.list_models();
if models.len() < 2 {
println!("Note: Only one model available, using it for both examples\n");
}
// Use first model for general chat
println!("Using first model for general question:");
let response1 = client.chat(
&models[0].id,
vec![ChatMessage::user("What is AI?")],
Some(ChatOptions {
max_tokens: Some(50),
..Default::default()
})
).await?;
println!(" {}\n", response1.choices[0].message.content);
// Use second model (or first if only one available) for coding
let model_idx = if models.len() > 1 { 1 } else { 0 };
println!("Using {} model for coding question:", if model_idx == 1 { "second" } else { "first" });
let response2 = client.chat(
&models[model_idx].id,
vec![
ChatMessage::system("You are a coding expert."),
ChatMessage::user("Write a Rust function to check if a number is prime"),
],
Some(ChatOptions {
max_tokens: Some(200),
..Default::default()
})
).await?;
println!(" {}\n", response2.choices[0].message.content);
Ok(())
}
/// Example: Error handling
async fn example_error_handling() -> Result<(), Box<dyn std::error::Error>> {
println!("=== Error Handling Example ===\n");
let client = UncloseAI::new(None).await?;
// Try to use non-existent model
match client.chat(
"non-existent-model",
vec![ChatMessage::user("Hello")],
None
).await {
Ok(_) => println!("Unexpected success"),
Err(e) => println!("Caught error (expected): {}\n", e),
}
Ok(())
}
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
println!("{}", "=".repeat(60));
println!("UncloseAI Rust Library - Examples");
println!("{}", "=".repeat(60));
println!();
// Run examples
if let Err(e) = example_model_discovery().await {
eprintln!("Model discovery failed: {}", e);
eprintln!("\nMake sure environment variables are set:");
eprintln!(" MODEL_ENDPOINT_1=https://your-endpoint/v1");
eprintln!(" TTS_ENDPOINT_1=https://your-tts-endpoint/v1");
return Err(e);
}
example_chat().await?;
example_chat_streaming().await?;
example_chat_streaming_with_context().await?;
example_multiple_models().await?;
if let Err(e) = example_tts().await {
println!("[ERROR] TTS Error: {}\n", e);
}
example_error_handling().await?;
println!("{}", "=".repeat(60));
println!("All examples completed successfully!");
println!("{}", "=".repeat(60));
Ok(())
}