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

# Config

# Config

Configuration types for controlling model behavior.

## Config

The `Config` function creates a Zod schema for parsing model configuration. All fields are optional and provider-specific.

```typescript theme={null}
import { Config } from "@adaline/types";

const config = Config().parse({
  temperature: 0.7,
  maxTokens: 500,
  topP: 0.9,
  frequencyPenalty: 0,
  presencePenalty: 0,
  stop: ["\n"],
});
```

### Common Fields

**temperature** `number`

Controls randomness. `0` is deterministic, higher values are more creative. Range: `0` to `2`.

**maxTokens** `number`

Maximum number of tokens to generate.

**topP** `number`

Nucleus sampling threshold. Range: `0` to `1`.

**frequencyPenalty** `number`

Penalize tokens based on frequency. Range: `-2` to `2`.

**presencePenalty** `number`

Penalize tokens based on presence. Range: `-2` to `2`.

**stop** `string[]`

Stop sequences that halt generation.

**seed** `number`

Random seed for deterministic outputs (provider support varies).

## Embedding Config

For embedding models, the config supports:

```typescript theme={null}
const embeddingConfig = Config().parse({
  encodingFormat: "float",
  dimensions: 256,
});
```

**encodingFormat** `string`

The encoding format for embeddings. Common values: `"float"`, `"base64"`.

**dimensions** `number`

The number of dimensions for the output embeddings.


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