ruby-openai

Ruby OpenAI: A Comprehensive Introduction

Ruby OpenAI is a powerful Ruby gem that enables developers to harness the capabilities of the OpenAI API. With this tool, you can engage with cutting-edge AI technologies effortlessly using Ruby, allowing you to create applications that can process text, transcribe and translate audio, and even generate images.

Installation

Ruby OpenAI is easy to install in your Ruby project. You have two primary methods to add it to your application: using Bundler or directly via Rubygems.

Bundler

To use Bundler, add the following line to your Gemfile:

gem "ruby-openai"

Execute the installation with:

$ bundle install

Gem Install

Alternatively, you can install it directly:

$ gem install ruby-openai

Then require it in your Ruby scripts:

require "openai"

Usage

Start by obtaining an API key from OpenAI. You might also need an Organization ID if you are part of multiple organizations. Here's a quick start example showing how to use your access token:

client = OpenAI::Client.new(
  access_token: "access_token_goes_here",
  log_errors: true # This helps to see errors during development.
)

Configuration

For a more secure and maintainable setup, configure the gem with environmental variables managed by a tool like Dotenv. Avoid hardcoding secrets directly into your codebase.

OpenAI.configure do |config|
  config.access_token = ENV.fetch("OPENAI_ACCESS_TOKEN")
  config.organization_id = ENV.fetch("OPENAI_ORGANIZATION_ID")
  config.log_errors = true
end

client = OpenAI::Client.new

Advanced Configuration

• Timeouts and Base URI: Customize the timeout or endpoint URI during initialization for specific requirements.
• Extra Headers: Dynamically add headers to each client object, which is useful for additional integrations or specific proxy settings.
• Logging: Enable logging to catch errors and manage network-related issues efficiently.

API and Models

Ruby OpenAI allows interaction with various AI models, including GPT-4 for chat, Whisper for audio processing, and DALL·E for image generation. Use the library to:

• Generate text responses based on conversational inputs.
• Stream responses in real-time for an engaging user experience.
• Generate textual descriptions of images with GPT-4 Vision.
• Count tokens to manage API call budgets and ensure prompt text fits within limits.

Using Additional Features

Functions

Integrate external functionalities by describing them to the model. It can then smartly generate JSON objects containing arguments to trigger these functions.

def get_current_weather(location:, unit: "fahrenheit")
  "The weather in #{location} is nice 🌞 #{unit}"
end

messages = [
  { role: "user", content: "What is the weather like in San Francisco?" }
]

response = client.chat(
  parameters: {
    model: "gpt-4o",
    messages: messages,
    tools: [
      {
        type: "function",
        function: {
          name: "get_current_weather",
          description: "Get the current weather in a given location"
        }
      }
    ]
  }
)

Image Generation

Leverage DALL·E for creating images. Generate, edit, or explore variations of images seamlessly through simple API calls.

Audio Processing with Whisper

Ruby OpenAI supports Whisper functionalities that enable transcription and translation of audio. It can also handle different speech formats and requirements.

Contribution and Community

Ruby OpenAI is open-source under the MIT license. Contributions to the project are welcome. Developers can engage with the community through the Ruby AI Builders Discord, or check out additional gems such as Anthropic and Midjourney designed to extend AI capabilities.

In conclusion, Ruby OpenAI provides a versatile and comprehensive toolset for Ruby developers looking to integrate advanced AI functionalities into their projects with ease and efficiency.