vectorifyai/vectorify-laravel

Vectorify package for Laravel. The fastest way to ask AI about your data.

1.0.7 2025-07-08 18:33 UTC

Requires

• php: >=8.2
• laravel/framework: ^10.0|^11.0|^12.0
• vectorifyai/vectorify-php: ^1.0

Requires (Dev)

• phpunit/phpunit: ^11.5

MIT

• laravel
• Agent
• vector
• ai
• mcp
• openai
• llm
• rag
• vector database

README

Vectorify is the end-to-end AI connector for Laravel, letting you query and explore your data in natural language in seconds.

Laravel is famous for turning complex web app chores into elegant, artisan-friendly code. Vectorify brings that same spirit to AI-powered data exploration: with one composer install and a single config file, your Laravel app becomes a conversational knowledge base you (and your customers) can query in natural language.

To interact with your data, you have four primary methods to choose from:

1. Use the Chats page within our platform (fastest)
2. Embed the Chatbot into your Laravel app (turn data querying into a product feature)
3. Add the MCP server to ChatGPT, Claude, etc. (use your data anywhere you work)
4. Call the REST API endpoints (build custom integrations and workflows)

Unlike text-to-SQL tools that expose your entire database and take 30+ seconds per query, Vectorify uses proven RAG technology to deliver accurate answers in <4 seconds while keeping your database secure. Head to our blog to learn more about Vectorify.

This package provides seamless integration to automatically extract, transform, and upsert your Laravel application data to Vectorify.

Requirements

• PHP 8.2 or higher
• Laravel 10 or higher

Installation

Install the package via Composer:

composer require vectorifyai/vectorify-laravel

The package automatically registers itself with Laravel through package auto-discovery.

Configuration

1. Publish configuration file

Publish the configuration file to define your collections:

php artisan vendor:publish --tag=vectorify

This will create a config/vectorify.php file in your application.

2. Environment variables

Add the API Key to your .env file:

VECTORIFY_API_KEY=your_api_key_here

You can get your API Key from Vectorify's dashboard.

3. Configure collections

Edit the config/vectorify.php file to define which models (collections) and columns you want to upsert. The simplest collection configuration references a model class:

'collections' => [
    \App\Models\Invoice::class,
]

This approach uses the model's $fillable or a custom $vectorify property as the column list. Read the documentation to learn more about defining the collections.

Upsert

Manual synchronisation

Run the upsert command manually to sync your data:

php artisan vectorify:upsert

Automatic synchronisation

The package automatically schedules the upsert command to run every 6 hours.

Changelog

Please see Releases for more information on what has changed recently.

Contributing

Pull requests are more than welcome. You must follow the PSR coding standards.

Security

Please review our security policy on how to report security vulnerabilities.

License

The MIT License (MIT). Please see LICENSE for more information.