> ## Documentation Index
> Fetch the complete documentation index at: https://docs.gaussia.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Schemas

> The Zod-derived data model exported from @gaussia/sdk/schemas.

The SDK's public types are Zod schemas, exported from `@gaussia/sdk/schemas`. Each schema is a single source of truth: it validates values at runtime, and its TypeScript type is inferred from the schema rather than hand-written. Build values through the schemas so they are validated as you create them.

```ts theme={null}
import { Batch, Dataset } from "@gaussia/sdk/schemas";

const batch = Batch.parse({
  qaId: "q-1",
  query: "Say hello",
  assistant: "Hello!",
  groundTruthAssistant: "Hello!",
});
```

`Batch.parse` returns a validated, fully typed value and throws on invalid input.

## Core data model

These describe the evaluation input consumed by the [`Gaussia`](/concepts/evaluators) base class.

* `Dataset` — one evaluation session: `sessionId`, `assistantId`, `context`, a `conversation` of `Batch[]`, and an optional `language`.
* `Batch` — one query/answer unit: `qaId`, `query`, `assistant`, `groundTruthAssistant`, and an optional `weight`.
* `IterationLevel` — `full_dataset`, `stream_sessions`, or `stream_batches`; selects how a retriever's data is consumed.
* `SessionMetadata` and `StreamedBatch` — the streaming shapes used by the streaming iteration levels.
* `Logprobs` — token log-probability data passed through evaluation.

## Generator schemas

These describe the structured output of [generators](/generators/overview).

* `Chunk` — a unit of context produced by a loader.
* `GeneratedQuery` and `GeneratedQueriesOutput` — single-turn generation output.
* `ConversationTurn` and `GeneratedConversationOutput` — multi-turn generation output.

## Prompt-optimizer schemas

These describe the result of [GEPA optimization](/prompt-optimizer/gepa).

* `OptimizationResult` — the final result: optimized prompt, initial and final scores, and history.
* `IterationResult` and `CandidateResult` — per-iteration detail in the history.
* `FailingExample` — an example that scored below threshold and drove candidate generation.

## Why Zod

Deriving types from schemas keeps the static type and the runtime check in lockstep. Structured model output uses the same approach: `generateObject` on a [`LanguageModel`](/concepts/language-models) validates the model's response against the Zod schema you pass.