You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: few_shot.rs
    path of file: ./repos/llm-chain/crates/llm-chain-llama/examples
    
    the code of the file until where you have to start completion: use llm_chain::prompt::Conversation;
use llm_chain::{chains::conversation::Chain, executor, parameters, prompt, step::Step};
/// This example demonstrates how to use the llm-chain for few-shot prompting
///
/// This example can be seen as a "chain of thought"
///
/// Usage: cargo run --example few_shot
///
/// Make sure to have the env var 'LLM_CHAIN_MODEL' set
#[tokio::main(flavor = "multi_thread", worker_threads = 1)]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let exec_1 = executor!(llama)?;

    let user_prompt =
        "Take the last letters of the words in '{{ full_name }}' and concatenate them";
    let res = Step::for_prompt_template(prompt!(user: user_prompt))
        .run(&parameters!().with("full_name", "Elon Musk"), &exec_1)
        .await?;
    println!("{} (zero-shot answer)", res.to_immediate().await?); // probably not correct
    let conversation = Conversation::new()
        .with_user_template(
            user_prompt,
            &parameters!().with("full_name", "Saquon Barkley"),
        )?
        .with_assistant("SB".to_string())
        .with_user_template(
            user_prompt,
            &parameters!().with("full_name", "Sean Connery"),
        )?
        .with_assistant("SC".to_string())
        .with_user_template(
            user_prompt,
            &parameters!().with(
    
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let exec_1 = executor!(llama)?;

    let user_prompt =
        "Take the last letters of the words in '{{ full_name }}' and concatenate them";
    let res = Step::for_prompt_template(prompt!(user: user_prompt))
        .run(&parameters!().with("full_name", "Elon Musk"), &exec_1)
        .await?;
    println!("{} (zero-shot answer)", res.to_immediate().await?); // probably not correct
    let conversation = Conversation::new()
        .with_user_template(
            user_prompt,
            &parameters!().with("full_name", "Saquon Barkley"),
        )?
        .with_assistant("SB".to_string())
        .with_user_template(
            user_prompt,
            &parameters!().with("full_name", "Sean Connery"),
        )?
        .with_assistant("SC".to_string())
        .with_user_template(
            user_prompt,
            &parameters!().with("full_name", "Julius Ceasar"),
        )?
        .with_assistant("JC".to_string())
        .with_user_template(user_prompt, &parameters!().with("full_name", "Ding Liren"))?
        .with_assistant("DL".to_string());
    // build a chain, that has the above conversation stored in its state
    let mut chain = Chain::new_with_message_collection(&conversation);
    // Try the Elon Musk problem again
    // Define the step
    let step = Step::for_prompt_template(prompt!(user: user_prompt));
    // Execute the chain.
    let exec_2 = executor!(llama)?;
    let res = chain
        .send_message(step, &parameters!().with("full_name", "Elon Musk"), &exec_2)
        .await?;
    println!("{} (few-shot CoT answer)", res.to_immediate().await?);
    Ok(())
}