Unit 4 · Connect AI steps into a workflow

Build a workflow with explicit steps

You define application-owned state and a visible sequence of typed nodes. Input mappings feed each node, and the return mapping selects the final result.

flow()8 focused minutesNot started

Unit example (nearest native match)

See the idea in context

String mermaid = "flowchart TD\n  %%ax classify: request:string -> route:class \"support, sales\"\n  classify{route}";
AxFlow program = Ax.flow(mermaid);
System.out.println(program);

Declare a typed node
draft states exactly what the AI step receives and returns.
Map state into the node
execute() passes the workflow topic into the draft program.
Choose the public result
returns() exposes only the final text to the caller.

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/flows/BranchFlowExample.java

Active practice

Show that you can use it

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Keep exploring

See the idea in context

Show that you can use it

Source-backed follow-up