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// Import required modules from the LLM library for Groq 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 Groq API key from environment variable or use test key as fallback
let api_key = std::env::var("GROQ_API_KEY").unwrap_or("gsk-TESTKEY".into());
// Initialize and configure the LLM client
let llm = LLMBuilder::new()
.backend(LLMBackend::Groq) // Use Groq as the LLM provider
.api_key(api_key) // Set the API key
.model("deepseek-r1-distill-llama-70b") // Use deepseek-r1-distill-llama-70b model
.max_tokens(512) // Limit response length
.temperature(0.7) // Control response randomness (0.0-1.0)
.build()
.expect("Failed to build LLM (Groq)");
// Prepare conversation history with example messages
let messages = vec![
ChatMessage::user()
.content("Tell me about quantum computing")
.build(),
ChatMessage::assistant()
.content("Quantum computing is a type of computing that uses quantum phenomena...")
.build(),
ChatMessage::user().content("What are qubits?").build(),
];
// Send chat request and handle the response
match llm.chat(&messages).await {
Ok(text) => println!("Chat response:\n{text}"),
Err(e) => eprintln!("Chat error: {e}"),
}
Ok(())
}