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

# aixyz/model/fake

> Deterministic fake language model for testing and development

A drop-in `LanguageModelV3` implementation that maps user messages through a transform function — no API key, no network calls, fully deterministic.

```typescript theme={null}
import { fake, type Prompt } from "aixyz/model";
```

## `fake(transform)`

Creates a fake language model conforming to the Vercel AI SDK `LanguageModelV3` specification. The returned model can be passed directly to `ToolLoopAgent` or any AI SDK function that accepts a `LanguageModel`.

```typescript theme={null}
function fake(transform: (lastMessage: string, prompt: Prompt) => string): LanguageModelV3;
```

### Parameters

| Parameter   | Type                                              | Description                                                                                                |
| ----------- | ------------------------------------------------- | ---------------------------------------------------------------------------------------------------------- |
| `transform` | `(lastMessage: string, prompt: Prompt) => string` | Function that receives the last user message text and the full prompt, and returns the model output string |

The `transform` function receives two arguments:

* **`lastMessage`** — the text content of the most recent user message (empty string if none)
* **`prompt`** — the full `LanguageModelV3Prompt` conversation history, useful for tracking turn count or prior context

### Return value

A `LanguageModelV3` object with:

* `specificationVersion: "v3"`
* `provider: "aixyz/fake"`
* `modelId: "aixyz/fake"`
* `doGenerate()` and `doStream()` that call your transform and report zero token usage

### Examples

Simple echo:

```typescript theme={null}
import { fake } from "aixyz/model";

const model = fake((input) => `You said: ${input}`);
```

Using full prompt context:

```typescript theme={null}
import { fake } from "aixyz/model";

const model = fake((input, prompt) => {
  const turn = prompt.filter((m) => m.role === "user").length;
  return `Turn ${turn}: ${input}`;
});
```

Wiring into an agent:

```typescript title="app/agent.ts" theme={null}
import { fake } from "aixyz/model";
import { ToolLoopAgent } from "ai";

export const model = fake((input) => `Echo: ${input}`);

export default new ToolLoopAgent({
  model,
  instructions: "You echo back whatever the user says.",
});
```

## `Prompt`

Type alias for `LanguageModelV3Prompt` from `@ai-sdk/provider`. This is an array of messages where each message has a `role` and `content`:

```typescript theme={null}
import type { Prompt } from "aixyz/model";
```

Use this type when you need to reference the prompt shape in your transform function or tests:

```typescript theme={null}
import { fake, type Prompt } from "aixyz/model";

const model = fake((_input: string, prompt: Prompt) => {
  return `${prompt.length} messages in history`;
});
```

## Testing with `fake()`

The fake model makes every test deterministic and CI-safe. Export the model from your agent file so tests can call `doGenerate()` directly:

```typescript title="app/agent.test.ts" theme={null}
import { describe, expect, test } from "bun:test";
import { model } from "./agent";
import type { Prompt } from "aixyz/model";

describe("agent (fake model)", () => {
  test("echoes the user message", async () => {
    const prompt: Prompt = [{ role: "user", content: [{ type: "text", text: "hello" }] }];
    const result = await model.doGenerate({ prompt });
    expect(result.content).toEqual([{ type: "text", text: "Echo: hello" }]);
  });
});
```

See the [Testing guide](/getting-started/testing#fully-offline-tests-with-fake) and the [Fake Model Agent template](/templates/advanced/fake-llm) for complete examples.