Improve how an agent chooses and actsYou evaluate the whole agent pipeline and tune its actor or responder. Good task records exercise tool choice, clarification, delegation, and final quality.rustacademyacademy/topics/agent-optimizewebsite/content-src/academy/course.mjsacademyImprove how an agent chooses and acts
You evaluate the whole agent pipeline and tune its actor or responder. Good task records exercise tool choice, clarification, delegation, and final quality.
optimize()11 focused minutesNot started
Unit example (nearest native match)
See the idea in context
let engine = AxGEPA::new(reflection_client, json!({}));
let result = engine.optimize(request, evaluator);
Run itIn your own project
cargo add axllm
use axllm::{ai, ax};
use serde_json::json;
let llm = ai("openai", json!({"apiKey": std::env::var("OPENAI_API_KEY")?}))?;
let classify = ax("review:string -> sentiment:class \"positive, negative, neutral\"")?;
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/optimization/axgen_optimization.rs