AIFaker.js 🧠🤖

Generate structured fake data using AI (https://console.groq.com/) effortlessly!

This package has initilized with vibe coding in 30 minutes

🚀 Features

• Schema-based generation: Define precise JSON structures.
• AI-powered data: Uses OpenAI's models to generate realistic fake data.
• Multi-language support: Control output language globally.
• Custom prompts: Define per-field prompts for accurate results.

📦 Installation

npm install ai-faker-js

or

yarn add ai-faker-js

🛠️ Usage

1️⃣ Initialize the Library

import { init, generate } from "ai-faker-js";

init({
  apiKey: "gsk_ai0x...",  // Your Groq API key (https://console.groq.com/)
  model: "llama-3.3-70b-versatile",     // AI model to use
  language: "en"      // Default language ("en", "fr", "es", "de", etc.)
});

2️⃣ Basic Text Generation

const fakeBio = await generate("Generate a short biography for a fictional character.");
console.log(fakeBio);

3️⃣ Structured Data Generation

You can define a strict schema to control the AI's output:

const userSchema = {
  object: {
    name: { type: "string", description: "A common first name" },
    age: { type: "number", description: "An age between 18 and 65" },
    email: "string"
  },
  description: "A realistic fictional user"
};

const fakeUser = await generate("Generate a fictional user", userSchema);
console.log(fakeUser);

4️⃣ Array Example: Generating Multiple Items

const productSchema = {
  array: {
    object: {
      id: { type: "string", description: "A unique product identifier" },
      name: "string",
      price: { type: "number", description: "Price in USD" },
    }
  },
  length: 10, // Generate 10 products
  description: "A list of fake products"
};

const fakeProducts = await generate("Generate a list of 10 products", productSchema);
console.log(fakeProducts);

⚙️ API Reference

init(options: FakerAiOptions)

Initialize the library with API credentials and settings.

Parameters:

| Name | Type | Required | Description | |----------|----------|----------|-------------| | apiKey | string | ✅ | OpenAI API key | | model | string | ✅ | AI model (e.g., "gpt-4") | | language | "en" | "fr" | "es" | "de" | ❌ (default "en") | Default output language |

generate(prompt: string, schema?: SchemaType): Promise<any>

Generates data based on a custom prompt and optional schema.

Parameters:

| Name | Type | Required | Description | |-----------|---------------|----------|-------------| | prompt | string | ✅ | Custom AI prompt | | schema | SchemaType | ❌ | Optional strict data structure |

📝 Schema Definition

The schema allows you to enforce a structured JSON output.

Basic Types

| Type | Example | |----------|---------| | "string" | "John Doe" | | "number" | 42 | | "boolean" | true | | "date" | "2025-01-01" |

Object Example

const personSchema = {
  object: {
    firstName: "string",
    lastName: "string",
    age: { type: "number", description: "Between 18 and 60" }
  }
};

Array Example

const usersSchema = {
  array: {
    object: {
      name: "string",
      email: "string"
    }
  },
  length: 5, // Generate 5 users
};

🌎 Multi-Language Support

The library supports multiple output languages.
Set the language in init() to "en", "fr", "es", "de", etc.

init({ apiKey: "sk-xxx", model: "gpt-4", language: "fr" });
const fakeUser = await generate("Génère un utilisateur fictif", userSchema);
console.log(fakeUser);

🏗️ Roadmap

• [ ] Custom field validation
• [ ] Support for enums ("male" | "female" etc.)
• [ ] Custom AI model configuration
• [ ] Improved performance with caching

💡 Why Use AIFaker.js?

✅ No more manually creating fake data 🚀
✅ Ensures realistic and structured outputs 🧠
✅ Fully customizable with AI-powered generation 🤖

🛠️ Contributing

Pull requests are welcome! If you find a bug or want to request a feature, feel free to open an issue.