Type-Safe AI Responses

Structured Output

Get validated, typed responses from any model. Define your schema, and Veska ensures every response matches — with automatic retry when validation fails.

Live Demo

See the difference

Raw text vs validated, structured output — watch validation happen in real-time, including automatic retry on type errors.

Raw AI Response
AI
Unstructured, no type guarantees
Structured Output
V
{
"name":...,
"version":...,
"language":...,
"agents":...,
"streaming":...,
"license":...
}
Validated, typed, auto-retried

How It Works

Three steps to type safety

Step 1

Define Your Schema

Use Pydantic models to describe the exact shape you want. Fields, types, constraints — all defined in Python.

Step 2

Agent Generates

The agent sends your prompt to the model. The response is parsed and mapped against your schema automatically.

Step 3

Validate & Retry

Pydantic validates every field. If anything fails, Veska automatically retries with the error feedback until it passes.

Benefits

Why structured output matters

Type Safety

Every response matches your schema. No more parsing JSON strings or hoping the model follows instructions.

Auto-Retry

When validation fails, Veska sends the error back to the model and retries automatically. No manual error handling needed.

Any Model

Works with every provider Veska supports. Same schema, same validation, regardless of which model powers your agent.

Nested Schemas

Support for complex objects, lists, enums, optional fields, and deeply nested structures out of the box.

Architecture

Validation flow

Every response passes through automatic validation. Failed fields trigger a retry loop with error context.

AgentRaw OutputValidatorTypedValidation FailedRetry with error context

Never parse raw text again

Define your schema, let Veska handle validation and retries.