Module: RubyTodo::AIAssistant::TaskOpenAIQuery

Included in:
TaskCreatorCombined
Defined in:
lib/ruby_todo/ai_assistant/task_creator.rb

Overview

Module for OpenAI query related to task creation

Instance Method Summary collapse

Instance Method Details

#query_openai_for_task_details(task_query, api_key) ⇒ Object

Query OpenAI for task details



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# File 'lib/ruby_todo/ai_assistant/task_creator.rb', line 73

def query_openai_for_task_details(task_query, api_key)
  client = OpenAI::Client.new(access_token: api_key)
  system_prompt = "    You are a task management assistant that generates professional task details.\n\n    Transform simple task descriptions into professional, action-oriented titles that clearly communicate purpose.\n\n    Examples of transformations:\n    - \"add new relic infra to questions-engine\" \u2192 \"Integrate New Relic Infrastructure with Questions Engine\"\n    - \"update docker image for app\" \u2192 \"Update and Standardize Docker Image Configuration for Application\"\n    - \"fix login bug\" \u2192 \"Resolve Authentication Issue in Login System\"\n    - \"add monitoring to service\" \u2192 \"Implement Comprehensive Monitoring Solution for Service\"\n    - \"migrate repo to new org\" \u2192 \"Migrate Repository to New Organization Structure\"\n    - \"add newrelic to the questions engine app\" \u2192 \"Integrate New Relic Monitoring with Questions Engine Application\"\n    - \"create a new task to add newrelic to the questions engine app\" \u2192 \"Implement New Relic Monitoring for Questions Engine Application\"\n\n    Create concise but descriptive titles that use proper capitalization and professional terminology.\n\n    IMPORTANT: For priority field, you MUST use ONLY one of these exact values: \"high\", \"medium\", or \"low\" (lowercase).\n  PROMPT\n\n  messages = [\n    { role: \"system\", content: system_prompt },\n    { role: \"user\", content: task_query }\n  ]\n\n  say \"Generating professional task details...\" if @options[:verbose]\n\n  response = client.chat(parameters: {\n                           model: \"gpt-4o\",\n                           messages: messages,\n                           temperature: 0.6,\n                           max_tokens: 500\n                         })\n\n  response[\"choices\"][0][\"message\"][\"content\"]\nrescue StandardError => e\n  # If gpt-4o fails (not available), fallback to gpt-4o-mini\n  if e.message.include?(\"gpt-4o\")\n    client.chat(parameters: {\n                  model: \"gpt-4o-mini\",\n                  messages: messages,\n                  temperature: 0.6,\n                  max_tokens: 500\n                })[\"choices\"][0][\"message\"][\"content\"]\n  else\n    raise e\n  end\nend\n"