Unit 2 · Make AI outputs predictable

Add richer validation to your fields

You use the fluent builder for limits, nested objects, arrays, optional fields, and richer descriptions. Validation becomes part of the program instead of cleanup after it.

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Unit example (nearest native match)

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var sig = Ax.s("email:string -> priority:class \"high, normal, low\"");

Reject empty input
min(1) makes the text requirement executable.
Bound the score
The output must stay between zero and one.
Build one signature
build() finishes the reusable input and output contract.

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.

In the ax repo

From a clone of the ax repo:

npm run example -- java src/examples/java/generation/StructuredGenerationExample.java

Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1

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