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// Import required modules from the LLM library for Anthropic integration
use llm::{
builder::{LLMBackend, LLMBuilder}, // Builder pattern components
chat::ChatMessage, // Chat-related structures
};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
// Get Anthropic API key from environment variable or use test key as fallback
let api_key: String = std::env::var("ANTHROPIC_API_KEY").unwrap_or("anthro-key".into());
// Initialize and configure the LLM client
let llm = LLMBuilder::new()
.backend(LLMBackend::Anthropic) // Use Anthropic (Claude) as the LLM provider
.api_key(api_key) // Set the API key
.model("claude-3-7-sonnet-20250219") // Use Claude Instant model
.max_tokens(1500) // Limit response length
.temperature(1.0) // Control response randomness (0.0-1.0)
.reasoning(true)
.reasoning_budget_tokens(1024)
// Uncomment to set system prompt:
// .system("You are a helpful assistant specialized in concurrency.")
.build()
.expect("Failed to build LLM (Anthropic)");
// Prepare conversation history with example message about Rust concurrency
let messages = vec![ChatMessage::user()
.content("How much r in strawberry?")
.build()];
// Send chat request and handle the response
match llm.chat(&messages).await {
Ok(text) => {
if let Some(thinking) = text.thinking() {
println!("Thinking: {thinking}");
}
if let Some(text) = text.text() {
println!("Text: {text}");
}
}
Err(e) => eprintln!("Chat error: {e}"),
}
Ok(())
}