See failures, cost, and latency in production
You add traces, usage and cost accounting, cache policy, cancellation, bounded retries, and safe logs. Debug output becomes evidence for tests and operations.
Unit example (nearest native match)
See the idea in context
AxGlobals.setRateLimiter(globalLimiter);
AxGlobals.setTracer(tracer);
AxGlobals.setMeter(meter);
workflow.forward(client, input, Map.of(), new AxRuntimeHooks(callLimiter, tracer, meter));
AxGlobals.setRateLimiter(null); AxGlobals.setTracer(null); AxGlobals.setMeter(null);- Trace the run
tracer connects model and tool activity to the surrounding request.
- Make cancellation possible
abortSignal lets callers stop work that is no longer useful.
- Control repeated work
contextCache makes reuse an explicit operational policy.
Run itIn your own project
// Gradle (build.gradle):
implementation 'dev.axllm:ax:24.0.15'
// Maven (pom.xml):
<dependency>
<groupId>dev.axllm</groupId>
<artifactId>ax</artifactId>
<version>24.0.15</version>
</dependency>
import dev.axllm.ax.Ax;
import java.util.Map;
public class QuickStart {
public static void main(String[] args) throws Exception {
var llm = Ax.ai("openai", Map.of("apiKey", System.getenv("OPENAI_API_KEY")));
var classify = Ax.ax("review:string -> sentiment:class \"positive, negative, neutral\"");
var result = classify.forward(llm, Map.of(
"review", "Useful and boring in the best way."
));
System.out.println("sentiment: " + result.get("sentiment"));
}
}Set OPENAI_APIKEY in your environment before running provider-backed code.
From a clone of the ax repo:
npm run example -- java src/examples/java/long-agents/SmartDefaultsAgentExample.javaActive practice
Answer 2 in a row to learn this · attempt 1