Unit 3 · Build a reliable AI-powered feature

Recover from invalid model output

You let Ax validate fields and retry with specific correction feedback. Your app can still distinguish generation errors, provider failures, and cancellation.

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Unit example (nearest native match)

See the idea in context

answer := axllm.NewAx("question:string -> answer:string", nil)

Run the program normally
Most valid responses return through the usual typed path.
Catch the specific failure
AxGenerateError identifies a generation or validation failure you can report deliberately.
Preserve useful details
error.details gives logs and UI a concrete repair target.

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/generation/basic_generation.go

Active practice

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