aixyz/model/fake

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

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.

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:

import { fake } from "aixyz/model";

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

Using full prompt context:

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:

app/agent.ts

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:

import type { Prompt } from "aixyz/model";

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

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:

app/agent.test.ts

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 and the Fake Model Agent template for complete examples.

Getting Started

CLI

Config

File-system layout

Functions

Protocols

aixyz/model/fake

`fake(transform)`

Parameters

Return value

Examples

`Prompt`

Testing with `fake()`

​fake(transform)

​Parameters

​Return value

​Examples

​Prompt

​Testing with fake()

`fake(transform)`

Parameters

Return value

Examples

`Prompt`

Testing with `fake()`