shawnveltman/laravel-openai

An OpenAI API wrapper that uses the Laravel Http facade for easier testing


README

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A unified Laravel package for interacting with multiple AI provider APIs (OpenAI, Claude/Anthropic, Gemini, and Mistral). Uses Laravel's HTTP facade for seamless testing and mocking, with built-in cost tracking and support for advanced features like extended thinking and reasoning.

Features

  • ๐Ÿค– Multi-Provider Support: OpenAI, Claude/Anthropic, Gemini, and Mistral
  • ๐Ÿงช Easy Testing: Built on Laravel's HTTP facade for simple mocking
  • ๐Ÿ’ฐ Cost Tracking: Automatic logging of API usage and costs
  • ๐Ÿง  Extended Thinking: Support for Claude's extended thinking and OpenAI's reasoning effort
  • ๐ŸŽฏ Unified Interface: Consistent API across all providers
  • ๐Ÿ–ผ๏ธ Image Support: Send images to vision-capable models
  • ๐Ÿ”„ Retry Logic: Automatic handling of rate limits and token limits

Installation

Install via Composer:

composer require shawnveltman/laravel-openai

Publish and run migrations for cost tracking:

php artisan vendor:publish --tag="laravel-openai-migrations"
php artisan migrate

Publish the config file:

php artisan vendor:publish --tag="laravel-openai-config"

Add your API keys to .env:

OPEN_API_KEY=your-openai-key
ANTHROPIC_API_KEY=your-anthropic-key
GEMINI_API_KEY=your-gemini-key
MISTRAL_API_KEY=your-mistral-key

Usage

Basic Example

use Shawnveltman\LaravelOpenai\ProviderResponseTestClass;

$ai = new ProviderResponseTestClass();

// Works with any supported model
$response = $ai->get_response_from_provider(
    prompt: 'Explain quantum computing in simple terms',
    model: 'gpt-5-nano', // or 'claude-sonnet-4', 'gemini-pro', etc.
);

Using Thinking Effort

Control the reasoning depth with the ThinkingEffort enum:

use Shawnveltman\LaravelOpenai\Enums\ThinkingEffort;

// Minimal thinking for simple tasks (fast, cheaper)
$response = $ai->get_response_from_provider(
    prompt: 'Format this data as JSON',
    model: 'gpt-5-nano',
    thinking_effort: ThinkingEffort::MINIMAL
);

// High thinking for complex reasoning (slower, more thorough)
$response = $ai->get_response_from_provider(
    prompt: 'Solve this complex mathematical proof',
    model: 'claude-sonnet-4',
    thinking_effort: ThinkingEffort::HIGH
);

Thinking Effort Levels:

  • MINIMAL: Fast responses, minimal reasoning (0 tokens for Claude, "minimal" for OpenAI)
  • LOW: Basic reasoning (6,000 tokens / "low")
  • MEDIUM: Standard reasoning - default (16,000 tokens / "medium")
  • HIGH: Deep reasoning (25,000 tokens / "high")

JSON Mode

Force responses in JSON format:

$response = $ai->get_response_from_provider(
    prompt: 'List the top 5 programming languages with descriptions',
    model: 'gpt-5-nano',
    json_mode: true
);

Working with Images

$response = $ai->get_response_from_provider(
    prompt: 'What is in this image?',
    model: 'gpt-4o',
    image_urls: ['https://example.com/image.jpg']
);

System Prompts and Messages

$response = $ai->get_response_from_provider(
    prompt: 'Write a haiku',
    model: 'claude-sonnet-4',
    system_prompt: 'You are a professional poet',
    messages: [
        ['role' => 'user', 'content' => 'Previous message'],
        ['role' => 'assistant', 'content' => 'Previous response'],
    ]
);

Advanced Configuration

$response = $ai->get_response_from_provider(
    prompt: 'Your prompt here',
    model: 'claude-sonnet-4',
    user_id: 123,
    description: 'Marketing copy generation',
    job_uuid: 'unique-job-id',
    temperature: 0.7,
    max_tokens: 4096,
    thinking_effort: ThinkingEffort::MEDIUM
);

Supported Models

OpenAI

  • GPT-5 series: gpt-5, gpt-5-mini, gpt-5-nano
  • GPT-4 series: gpt-4o, gpt-4o-mini, gpt-4-turbo
  • O-series: o1, o1-mini, o3, o3-mini, o4-mini

Anthropic Claude

  • claude-sonnet-4-20250514 (default)
  • claude-opus-4
  • Other Claude models

Google Gemini

  • gemini-pro
  • gemini-1.5-pro

Mistral

  • mistral-large
  • mistral-medium
  • codestral

Cost Tracking

The package automatically logs all API calls to the cost_logs table:

use Shawnveltman\LaravelOpenai\Models\CostLog;

// Get costs for a user
$costs = CostLog::where('user_id', 123)->get();

// Get costs by model
$costs = CostLog::where('model', 'gpt-5-nano')->sum('input_tokens');

Testing

composer test

Changelog

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

Contributing

Please see CONTRIBUTING for details.

Security Vulnerabilities

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

Credits

License

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