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

mermaid := `flowchart TD
  %%ax classify: request:string -> route:class "support, sales"
  classify{route}`
program := axllm.NewFlow(mermaid)
fmt.Println(program.String())

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

go get github.com/ax-llm/ax/packages/go

package main

import (
    "context"
    "fmt"
    "os"

    axllm "github.com/ax-llm/ax/packages/go"
)

func main() {
    client := axllm.NewAI("openai", map[string]axllm.Value{"apiKey": os.Getenv("OPENAI_API_KEY")})
    classify := axllm.NewAx("review:string -> sentiment:class \"positive, negative, neutral\"", nil)
    result, err := classify.Forward(context.Background(), client, map[string]axllm.Value{
        "review": "Useful and boring in the best way."
    }, nil)
    if err != nil {
        panic(err)
    }

    fmt.Println("sentiment:", result.(map[string]axllm.Value)["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 -- go src/examples/go/flows/branch_flow.go

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

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