Structura.AI is an AI-powered API and web application that transforms unstructured text into structured JSON data in under 3 seconds. It's designed to be used by both developers and non-technical users, offering a powerful API and an intuitive interactive playground. Structura.AI leverages Google Gemini's powerful language model to accurately extract key information based on a provided JSON schema.

• High-speed data extraction: Transforms unstructured text into structured data quickly.
• Customizable output: Allows users to specify the desired output format using JSON schema.
• Developer-friendly API: Provides a simple and easy-to-use REST API for integration into various applications.
• Interactive Playground: A user-friendly web interface for testing the API without coding.
• Robust error handling: Includes comprehensive error handling and retry mechanisms.
• Rate limiting: Prevents abuse and ensures fair usage of the API.

The Structura.AI API accepts a POST request with the following JSON payload:

{
  "data": "Your unstructured text here",
  "format": {
    "fieldName1": { "type": "string" },
    "fieldName2": { "type": "number" },
    "fieldName3": { "type": "boolean" }
  }
}

The API will return a JSON response containing the extracted data:

{
  "fieldName1": "value1",
  "fieldName2": 123,
  "fieldName3": true
}

See the /playground route for an interactive demo.

This project is a Next.js application. You'll need Node.js and npm (or yarn, pnpm, bun) installed.

1. Clone the repository:

   git clone https://github.com/ArjunCodess/structura.git

2. Navigate to the project directory:

   cd structura

3. Install dependencies:

   npm install

4. Set environment variables (see Configuration section).
5. Run the development server:

   npm run dev

• Next.js: A React framework for building web applications. Used for the frontend and API.
• React: A JavaScript library for building user interfaces. Used for the frontend components.
• Tailwind CSS: A utility-first CSS framework. Used for styling the application.
• @shadcn/ui: A library of UI components built with Radix UI and Tailwind CSS.
• Google Generative AI: Provides access to the Gemini language model for data extraction.
• Zod: A schema validation library for TypeScript. Used for data validation.
• Redis (optional): Used for rate limiting if configured.
• Prismr-React-Renderer: Used for syntax highlighting in code examples.
• Lucide-React: Used for icon components.

Create a .env.local file in the root directory and add the following environment variables:

• NEXT_PUBLIC_BASE_URL: The base URL of your application (required for frontend links).
• GOOGLE_GENERATIVE_AI_API_KEY: Your Google Gemini API key (required for API functionality).
• UPSTASH_REDIS_REST_URL (optional): Your Upstash Redis URL for rate limiting.
• UPSTASH_REDIS_REST_TOKEN (optional): Your Upstash Redis token for rate limiting.

The API endpoint /api/extract accepts POST requests with application/json content-type. The request body should include data (the unstructured text) and format (the JSON schema). Error responses will include a detailed error message and HTTP status code (400 for bad request, 429 for too many requests, 500 for internal server error). See the Usage section for request/response examples. Rate limiting is implemented; see the rate-limit headers in the 429 response for details.

See the package.json file for a complete list of dependencies and devDependencies.

Contributions are welcome! Please open an issue or submit a pull request.

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