Struct LM 

pub struct LM {
    pub api_key: SecretString,
    pub base_url: String,
    pub config: LMConfig,
    pub history: Vec<LMResponse>,
    /* private fields */
}

Fields

api_key: SecretString

base_url: String

config: LMConfig

history: Vec<LMResponse>

Implementations

impl LM

pub fn builder() -> LMBuilder

Create an instance of LM using the builder syntax

Examples found in repository

examples/05-heterogenous-examples.rs (line 16)

async fn main() -> anyhow::Result<()> {
    configure(
        LM::builder()
            .api_key(SecretString::from(std::env::var("OPENAI_API_KEY")?))
            .build(),
        ChatAdapter {},
    );

    let exp = example! {
        "number": "input" => 10,
    };
    let predict = Predict::new(sign! {
        (number: i32) -> number_squared: i32, number_cubed: i32
    });

    let prediction = predict.forward(exp).await?;
    println!("{prediction:?}");

    Ok(())
}

examples/03-evaluate-hotpotqa.rs (line 63)

async fn main() -> anyhow::Result<()> {
    configure(
        LM::builder()
            .api_key(SecretString::from(std::env::var("OPENAI_API_KEY")?))
            .build(),
        ChatAdapter {},
    );

    let examples = DataLoader::load_hf(
        "hotpotqa/hotpot_qa",
        vec!["question".to_string()],
        vec!["answer".to_string()],
        "fullwiki",
        "validation",
        true,
    )?[..128]
        .to_vec();

    let evaluator = QARater::builder().build();
    let metric = evaluator.evaluate(examples).await;

    println!("Metric: {metric}");
    Ok(())
}

examples/01-simple.rs (line 73)

async fn main() -> Result<()> {
    configure(
        LM::builder()
            .api_key(std::env::var("OPENROUTER_API_KEY")?.into())
            .config(LMConfig {
                model: "openrouter/openai/gpt-4o-mini".to_string(),
                ..LMConfig::default()
            })
            .build(),
        ChatAdapter,
    );

    let example = example! {
        "question": "input" => "What is the capital of France?",
    };

    let qa_rater = QARater::builder().build();
    let prediction = qa_rater.forward(example).await.unwrap();
    println!("{prediction:?}");

    Ok(())
}

examples/07-inspect-history.rs (line 31)

async fn main() {
    let lm = LM::builder()
        .api_key(std::env::var("OPENAI_API_KEY").unwrap().into())
        .config(LMConfig {
            model: "gpt-4o-mini".to_string(),
            ..LMConfig::default()
        })
        .build();
    configure(lm, ChatAdapter);

    let example = example! {
        "question": "input" => "What is the capital of France?",
    };

    let qa_rater = QARater::builder().build();
    let prediction = qa_rater.forward(example.clone()).await.unwrap();
    println!("Prediction: {prediction:?}");

    let history = get_lm().lock().await.inspect_history(1);
    println!("History: {history:?}");
}

examples/04-optimize-hotpotqa.rs (line 61)

async fn main() -> anyhow::Result<()> {
    configure(
        LM::builder()
            .api_key(SecretString::from(std::env::var("OPENAI_API_KEY")?))
            .build(),
        ChatAdapter {},
    );

    let examples = DataLoader::load_hf(
        "hotpotqa/hotpot_qa",
        vec!["question".to_string()],
        vec!["answer".to_string()],
        "fullwiki",
        "validation",
        true,
    )?[..10]
        .to_vec();

    let mut rater = QARater::builder().build();
    let optimizer = COPRO::builder().breadth(10).depth(1).build();

    println!("Rater: {:?}", rater.answerer.get_signature().instruction());

    optimizer.compile(&mut rater, examples.clone()).await?;

    println!("Rater: {:?}", rater.answerer.get_signature().instruction());

    Ok(())
}

examples/06-oai-compatible-models-batch.rs (line 81)

async fn main() {
    // Anthropic
    configure(
        LM::builder()
            .api_key(SecretString::from(
                std::env::var("ANTHROPIC_API_KEY").unwrap(),
            ))
            .config(LMConfig {
                model: "anthropic/claude-sonnet-4-20250514".to_string(),
                ..LMConfig::default()
            })
            .build(),
        ChatAdapter,
    );

    let example = vec![
        example! {
            "question": "input" => "What is the capital of France?",
        },
        example! {
            "question": "input" => "What is the capital of Germany?",
        },
        example! {
            "question": "input" => "What is the capital of Italy?",
        },
    ];

    let qa_rater = QARater::builder().build();
    let prediction = qa_rater.batch(example.clone(), 2, true).await.unwrap();
    println!("Anthropic: {prediction:?}");

    // Gemini
    configure(
        LM::builder()
            .api_key(SecretString::from(std::env::var("GEMINI_API_KEY").unwrap()))
            .config(LMConfig {
                model: "google/gemini-2.0-flash".to_string(),
                ..LMConfig::default()
            })
            .build(),
        ChatAdapter,
    );

    let prediction = qa_rater.batch(example, 2, true).await.unwrap();
    println!("Gemini: {prediction:?}");
}

Additional examples can be found in:

• examples/08-optimize-mipro.rs

impl LM

pub async fn call( &mut self, messages: Chat, signature: &str, ) -> Result<(Message, LmUsage)>

pub fn inspect_history(&self, n: usize) -> Vec<LMResponse>

Examples found in repository

examples/07-inspect-history.rs (line 48)

async fn main() {
    let lm = LM::builder()
        .api_key(std::env::var("OPENAI_API_KEY").unwrap().into())
        .config(LMConfig {
            model: "gpt-4o-mini".to_string(),
            ..LMConfig::default()
        })
        .build();
    configure(lm, ChatAdapter);

    let example = example! {
        "question": "input" => "What is the capital of France?",
    };

    let qa_rater = QARater::builder().build();
    let prediction = qa_rater.forward(example.clone()).await.unwrap();
    println!("Prediction: {prediction:?}");

    let history = get_lm().lock().await.inspect_history(1);
    println!("History: {history:?}");
}

Trait Implementations

impl Clone for LM

fn clone(&self) -> LM

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.