Download the PHP package endritvs/laravel-ai-toolkit without Composer

Laravel AI Toolkit 🧠

Laravel AI Toolkit is a powerful package designed to seamlessly integrate AI models, such as OpenAI's GPT and AWS's Claude, into your Laravel application. With an easy-to-use interface, this toolkit empowers developers to effortlessly add AI-driven features to their projects.

🚀 Features

• Simple integration with OpenAI and AWS Claude.
• Configurable AI providers.
• Customizable query builder for AI models.
• Exception handling and error reporting.
• Support for multiple AI models and providers, with fallback capabilities.

📋 Requirements

• PHP 8.1 or higher
• Laravel 10.x to 11.x
• openai-php/laravel package
• aws/aws-sdk-php package

🛠️ Installation

To install the package, use Composer:

After installing the package, publish the configuration file:

This will create a configuration file at config/ai.php.

⚙️ Configuration

Environment Variables

Ensure that you set up the following environment variables in your .env file:

Configuration File

The config/ai.php configuration file contains default settings for the package. You can customize these settings as needed:

💻 Usage

Basic Usage Example

You can use the package to interact with AI models as follows:

Explanation:

• addContent('What is the capital of France?'): Sets the question content for the AI model to process.
• setModel('gpt-4o-mini'): Specifies the AI model to be used.
• setMaxTokens(50): Limits the response to a maximum of 50 tokens.
• execute(): Sends the request to the AI model and retrieves the response.

Query Builder Example

The query builder allows you to build queries for AI models:

Explanation:

• Prompt::query(): Creates a new query using the AIQueryBuilder class.
• setModel('anthropic.claude-v2'): Sets the AI model to be used.
• setMaxTokens(100): Limits the response to a maximum of 100 tokens.
• addContent('Tell me a joke'): Adds content to the request.
• execute(): Executes the query and retrieves the result.

Using Different Models Example

You can use different AI models for different tasks:

Explanation:

• Using GPT model:

  • addContent('Explain quantum computing in simple terms.'): Sets the content for GPT to explain.
  • setModel('gpt-4o-mini'): Specifies the GPT model to use.
  • setMaxTokens(150): Limits the response to 150 tokens.
  • execute(): Gets the response from GPT.
• Using Claude model:
  • addContent('What are the latest trends in web development?'): Sets the content for Claude to process.
  • setModel('anthropic.claude-v2'): Specifies the Claude model.
  • setMaxTokens(150): Limits the response to 150 tokens.
  • execute(): Gets the response from Claude.

Using Fallback Providers Example

Specify a fallback provider to use if the primary provider fails:

Explanation:

• addContent('Summarize the latest news on AI technology.'): Sets the content for the request.
• setProvider('gpt'): Sets the primary provider to GPT.
• setModel('gpt-4o-mini'): Specifies the GPT model.
• setMaxTokens(150): Limits the response to 150 tokens.
• fallback('claude'): Configures Claude as the fallback provider if GPT fails.
• execute(): Executes the request, using the fallback provider if necessary.

Set Provider Example

Manually set a different provider for the AI model:

Explanation:

• setProvider('claude'): Manually sets the AI provider to Claude.
• addContent('Describe the principles of machine learning.'): Sets the content to be processed.
• setModel('claude-v2'): Specifies the Claude model.
• setMaxTokens(150): Limits the response to 150 tokens.
• execute(): Sends the request to the specified provider and retrieves the response.

Advanced Query Builder Example

Dynamically build and execute more complex queries:

Explanation:

• setModel('gpt-4o-mini'): Sets the AI model to be used.
• addContent('What are the implications of quantum computing?'): Adds additional content to the request.
• setMaxTokens(200): Limits the response to 200 tokens.
• execute(): Executes the query and processes the response.

Complete Example (Everything Included)

Combines all features into a comprehensive example, demonstrating both GPT and Claude models:

Explanation:

GPT-4 Example:

• addContent('Give a summary of the latest advancements in technology.'): Sets the content for GPT-4.
• setModel('gpt-4'): Specifies GPT-4 as the primary model.
• setMaxTokens(300): Limits the response to 300 tokens.
• fallback('claude'): Uses Claude as the fallback provider if GPT-4 fails.
• execute(): Executes the request, retrieving the response from GPT-4 or Claude.

Claude Example:

• addContent('Discuss the impact of recent technological innovations on society.'): Sets the content for Claude.
• setModel('claude-v2'): Specifies Claude as the model.
• setMaxTokens(300): Limits the response to 300 tokens.
• execute(): Executes the request and retrieves the response from Claude.

Query Builder Example:

• Prompt::query(): Creates a new query builder instance.
• setModel('gpt-4o-mini'): Specifies GPT-4o-mini as the model for the query.
• addContent('What is the future of artificial intelligence?'): Adds additional content to the query.
• setMaxTokens(150): Limits the response to 150 tokens.
• execute(): Executes the query and retrieves the result based on the specified parameters.

🛠️ Contributing

Contributions are welcome! If you'd like to contribute to this package, please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/new-feature).
3. Commit your changes (git commit -m 'Add new feature').
4. Push to the branch (git push origin feature/new-feature).
5. Open a pull request.

🛡️ Security Vulnerabilities

If you discover a security vulnerability within this package, please send an email to [[email protected]]. All security vulnerabilities will be promptly addressed.

📄 License

This package is licensed under the MIT License. See the LICENSE file for more information.

💡 Tips & Tricks

• Use environment-specific configuration to tweak AI model behavior depending on your deployment environment.
• Monitor the usage and response times of your AI models to optimize performance.
• Experiment with different AI models to find the one that best suits your application's needs.

📬 Support

If you have any questions or need further assistance, feel free to reach out via email or open an issue on GitHub.