Unit 6 · Solve long and complex tasks

Keep bulky evidence out of the prompt

You place large inputs in the runtime and expose only a preview and shape to the model. Declared contextFields keep the full value available by reference.

contextFields9 focused minutesNot started

Unit example (nearest native match)

See the idea in context

let investigator = agent_with_options(signature, json!({
    "contextFields": ["logs"],
    "contextPolicy": {"preset": "lean", "budget": "balanced"},
    "runtime": {"language": "JavaScript"},
}))?.with_runtime(Box::new(QuickJsCodeRuntime::new()))?;

Run itIn your own project

cargo add axllm

use axllm::{ai, ax, AxResult};
use serde_json::json;

fn main() -> AxResult<()> {
    let mut llm = ai("openai", json!({"apiKey": std::env::var("OPENAI_API_KEY")?}))?;
    let mut classify = ax("review:string -> sentiment:class \"positive, negative, neutral\"")?;
    let result = classify.forward(&mut llm, json!({
        "review": "Useful and boring in the best way."
    }))?;

    println!("sentiment: {}", result["sentiment"].as_str().unwrap_or_default());
    Ok(())
}

Set OPENAI_APIKEY in your environment before running provider-backed code.

In the ax repo

From a clone of the ax repo:

npm run example -- rust src/examples/rust/long-agents/incident_log_forensics.rs

Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1

Keep exploring

See the idea in context

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Source-backed follow-up