The Lodash for GenAI: Consistent + Model-Agnostic

ActiveGenie is an enabler for creating reliable GenAI features, offering powerful, model-agnostic tools across any provider. It allows you to settle subjective comparisons with a ActibeGenie::Comparator module that stages a political debate, get accurate scores from an AI jury using ActiveGenie::Scorer, and rank large datasets using ActiveGenie::Ranker's tournament-style system. This reliability is built on three core pillars:

• Custom Benchmarking: Testing for consistency with every new version and model update.
• Reasoning Prompting: Utilizing human reasoning techniques (like debate and jury review) to control a model's reasoning.
• Overfitting Prompts: Highly specialized, and potentially model-specific, prompt for each module's purpose.

For full documentation, visit activegenie.ai.

1. Add to your Gemfile:

gem 'active_genie'

2. Install the gem:

bundle install

3. Generate the configuration:

echo "ActiveGenie.load_tasks" >> Rakefile
rails active_genie:install

4. Configure your credentials in config/initializers/active_genie.rb:

ActiveGenie.configure do |config|
  config.providers.openai.api_key = ENV['OPENAI_API_KEY']
end

Extract structured data from text using AI-powered analysis, handling informal language and complex expressions.

text = "Nike Air Max 90 - Size 42 - $199.99"
schema = {
  brand: {
    type: 'string',
    enum: ["Nike", "Adidas", "Puma"]
  },
  price: {
    type: 'number',
    minimum: 0
  },
  size: {
    type: 'number',
    minimum: 35,
    maximum: 46
  }
}

result = ActiveGenie::Extractor.call(
  text,
  schema,
  config: { provider_name: :openai, model: 'gpt-4.1-mini' } # optional
)
# => {
#      brand: "Nike",
#      brand_explanation: "Brand name found at start of text",
#      price: 199.99,
#      price_explanation: "Price found in USD format at end",
#      size: 42,
#      size_explanation: "Size explicitly stated in the middle"
#    }

For full documentation, visit activegenie.ai.

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

This project is licensed under the Apache License 2.0 License - see the LICENSE file for details.