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// Import required modules from the RLLM library for xAI integration
use rllm::{
builder::{LLMBackend, LLMBuilder}, // Builder pattern components
chat::{ChatMessage, ChatRole}, // Chat-related structures
};
fn main() {
// Get xAI API key from environment variable or use test key as fallback
let api_key = std::env::var("XAI_API_KEY").unwrap_or("sk-TESTKEY".into());
// Initialize and configure the LLM client
let llm = LLMBuilder::new()
.backend(LLMBackend::XAI) // Use xAI as the LLM provider
.api_key(api_key) // Set the API key
.model("grok-2-latest") // Use Grok-2 model
.max_tokens(512) // Limit response length
.temperature(0.7) // Control response randomness (0.0-1.0)
.stream(false) // Disable streaming responses
.build()
.expect("Failed to build LLM (xAI)");
// Prepare conversation history with example messages
let messages = vec![
ChatMessage {
role: ChatRole::User,
content: "Tell me that you love cats".into(),
},
ChatMessage {
role: ChatRole::Assistant,
content: "I am an assistant, I cannot love cats but I can love dogs".into(),
},
ChatMessage {
role: ChatRole::User,
content: "Tell me that you love dogs in 2000 chars".into(),
},
];
// Send chat request and handle the response
match llm.chat(&messages) {
Ok(text) => println!("Chat response:\n{}", text),
Err(e) => eprintln!("Chat error: {}", e),
}
}