# Terminal
bundle add ruby-openai
bin/rails credentials:edit
bin/rails g model products name stock:integer
bin/rails g controller assistants index

# config/initializers/openai.rb
OpenAI.configure do |config|
  config.access_token = Rails.application.credentials.dig(:openai, :access_token)
end

# config/routes.rb
Rails.application.routes.draw do
  resources :assistants, only: [ :index, :create ]
  root to: "assistants#index"
  get "up" => "rails/health#show", as: :rails_health_check
end

# Credentials File
openai:
  access_token: YOURTOKEN

# app/controllers/assistants_controller.rb
class AssistantsController < ApplicationController
  def index
  end

  def create
    @question = params[:question]
    @answer = Assistant.new.ask(@question)
    render :index, status: :see_other
  end
end

# app/views/assistants/index.html.erb
<div class="mx-auto mt-16 max-w-xl px-4">
  <h1 class="text-2xl font-bold">Inventory Assistant</h1>

  <%= form_with url: assistants_path, method: :post, class: "mt-6 glex gap-2" do |form| %>
    <%= form.text_field :question,
          value: @question,
          placeholder: "How many road helmets do we have?",
          class: "flex-1 rounded border border-gray-300 px-3 py-2" %>
    <%= form.submit "Ask", class: "rounded bg-blue-600 px-4 py-2 font-medium text-white cursor-pointer" %>
  <% end %>

  <% if @answer %>
    <div class="mt-6 rounded border border-gray-200 bg-gray-50 p-4">
      <%= @answer %>
    </div>
  <% end %>
</div>

# app/models/assistant.rb
class Assistant
  SYSTEM_PROMPT = "You are an inventory assistant for our store. " \
    "Always use the check_inventory tool to answer questions about products " \
    "and stock levels. Only discuss products that the tool returns."

  TOOLS = [
    {
      type: "function",
      function: {
        name: "check_inventory",
        description: "Search the store's products by name and return matching products with their stock levels. Use a broad term like 'helmet' to list all helmets.",
        parameters: {
          type: "object",
          properties: { product_name: { type: "string" } },
          required: [ "product_name" ]
        }
      }
    }
  ]

  def initialize
    @client = OpenAI::Client.new
  end

  def ask(question)
    messages = [
      { role: "system", content: SYSTEM_PROMPT },
      { role: "user", content: question }
    ]
    message = chat(messages).dig("choices", 0, "message")

    if (tool_call = message.dig("tool_calls", 0))
      Rails.logger.info "✅✅✅✅✅✅ #{tool_call}"
      messages << message
      messages << tool_result(tool_call)
      message = chat(messages).dig("choices", 0, "message")
    end

    message["content"]
  end

  private

  def chat(messages)
    @client.chat(parameters: { model: "gpt-4o-mini", messages:, tools: TOOLS })
  end

  def tool_result(tool_call)
    args = JSON.parse(tool_call.dig("function", "arguments"))
    products = Product.where("name LIKE ?", "%#{args["product_name"]}%")

    {
      role: "tool",
      tool_call_id: tool_call["id"],
      content: products.any? ? products.map { |p| "#{p.name}: #{p.stock} in stock" }.join("\n") : "not found"
    }
  end
end