gem "ruby_llm-agents"

# config/initializers/ruby_llm_agents.rb RubyLLM::Agents.configure do |config| config.openai_api_key = ENV["OPENAI_API_KEY"] config.anthropic_api_key = ENV["ANTHROPIC_API_KEY"] config.gemini_api_key = ENV["GOOGLE_API_KEY"] config.default_model = "gpt-4o" end

class SummarizerAgent < ApplicationAgent model "gemini-2.0-flash" temperature 0.0 param :max_length, default: 500 system "You are a summarization assistant. Create concise summaries  that capture the key points while staying under the word limit." user "Summarize the following text in under {max_length} words:\n\n{text}" end

# In your Rails console or controller result = SummarizerAgent.call( text: "Long article text here...", max_length: 200 ) # Access the response puts result.content # The summary text # Access metadata puts result.total_tokens # => 150 puts result.total_cost # => 0.00025 puts result.duration_ms # => 850 puts result.model_id # => "gemini-2.0-flash"

agent = SummarizerAgent.new(max_length: 200) result = agent.ask("Summarize this article about climate change...") puts result.content # Follow up naturally result = agent.ask("Now make it shorter, under 50 words.") puts result.content

class SummarizerAgent < ApplicationAgent model "gemini-2.0-flash" temperature 0.0 param :max_length, default: 500 system "You are a summarization assistant. Return JSON with keys: summary, word_count." user "Summarize the following text in under {max_length} words:\n\n{text}" assistant "{" # Forces the model to start its reply with "{", ensuring JSON output end