Initial commit: Add logistics and order_detail message types

- Add Logistics component with progress tracking
- Add OrderDetail component for order information
- Support data-driven steps and actions
- Add blue color scale to widget SCSS
- Fix node overflow and progress bar rendering issues
- Add English translations for dashboard components

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

lib/integrations/openai/processor_service.rb

@@ -0,0 +1,138 @@
+class Integrations::Openai::ProcessorService < Integrations::LlmBaseService
+  AGENT_INSTRUCTION = 'You are a helpful support agent.'.freeze
+  LANGUAGE_INSTRUCTION = 'Ensure that the reply should be in user language.'.freeze
+  def reply_suggestion_message
+    make_api_call(reply_suggestion_body)
+  end
+
+  def summarize_message
+    make_api_call(summarize_body)
+  end
+
+  def rephrase_message
+    make_api_call(build_api_call_body("#{AGENT_INSTRUCTION} Please rephrase the following response. " \
+                                      "#{LANGUAGE_INSTRUCTION}"))
+  end
+
+  def fix_spelling_grammar_message
+    make_api_call(build_api_call_body("#{AGENT_INSTRUCTION} Please fix the spelling and grammar of the following response. " \
+                                      "#{LANGUAGE_INSTRUCTION}"))
+  end
+
+  def shorten_message
+    make_api_call(build_api_call_body("#{AGENT_INSTRUCTION} Please shorten the following response. " \
+                                      "#{LANGUAGE_INSTRUCTION}"))
+  end
+
+  def expand_message
+    make_api_call(build_api_call_body("#{AGENT_INSTRUCTION} Please expand the following response. " \
+                                      "#{LANGUAGE_INSTRUCTION}"))
+  end
+
+  def make_friendly_message
+    make_api_call(build_api_call_body("#{AGENT_INSTRUCTION} Please make the following response more friendly. " \
+                                      "#{LANGUAGE_INSTRUCTION}"))
+  end
+
+  def make_formal_message
+    make_api_call(build_api_call_body("#{AGENT_INSTRUCTION} Please make the following response more formal. " \
+                                      "#{LANGUAGE_INSTRUCTION}"))
+  end
+
+  def simplify_message
+    make_api_call(build_api_call_body("#{AGENT_INSTRUCTION} Please simplify the following response. " \
+                                      "#{LANGUAGE_INSTRUCTION}"))
+  end
+
+  private
+
+  def prompt_from_file(file_name, enterprise: false)
+    path = enterprise ? 'enterprise/lib/enterprise/integrations/openai_prompts' : 'lib/integrations/openai/openai_prompts'
+    Rails.root.join(path, "#{file_name}.txt").read
+  end
+
+  def build_api_call_body(system_content, user_content = event['data']['content'])
+    {
+      model: GPT_MODEL,
+      messages: [
+        { role: 'system', content: system_content },
+        { role: 'user', content: user_content }
+      ]
+    }.to_json
+  end
+
+  def conversation_messages(in_array_format: false)
+    messages = init_messages_body(in_array_format)
+
+    add_messages_until_token_limit(conversation, messages, in_array_format)
+  end
+
+  def add_messages_until_token_limit(conversation, messages, in_array_format, start_from = 0)
+    character_count = start_from
+    conversation.messages.where(message_type: [:incoming, :outgoing]).where(private: false).reorder('id desc').each do |message|
+      character_count, message_added = add_message_if_within_limit(character_count, message, messages, in_array_format)
+      break unless message_added
+    end
+    messages
+  end
+
+  def add_message_if_within_limit(character_count, message, messages, in_array_format)
+    content = message.content_for_llm
+    if valid_message?(content, character_count)
+      add_message_to_list(message, messages, in_array_format, content)
+      character_count += content.length
+      [character_count, true]
+    else
+      [character_count, false]
+    end
+  end
+
+  def valid_message?(content, character_count)
+    content.present? && character_count + content.length <= TOKEN_LIMIT
+  end
+
+  def add_message_to_list(message, messages, in_array_format, content)
+    formatted_message = format_message(message, in_array_format, content)
+    messages.prepend(formatted_message)
+  end
+
+  def init_messages_body(in_array_format)
+    in_array_format ? [] : ''
+  end
+
+  def format_message(message, in_array_format, content)
+    in_array_format ? format_message_in_array(message, content) : format_message_in_string(message, content)
+  end
+
+  def format_message_in_array(message, content)
+    { role: (message.incoming? ? 'user' : 'assistant'), content: content }
+  end
+
+  def format_message_in_string(message, content)
+    sender_type = message.incoming? ? 'Customer' : 'Agent'
+    "#{sender_type} #{message.sender&.name} : #{content}\n"
+  end
+
+  def summarize_body
+    {
+      model: GPT_MODEL,
+      messages: [
+        { role: 'system',
+          content: prompt_from_file('summary', enterprise: false) },
+        { role: 'user', content: conversation_messages }
+      ]
+    }.to_json
+  end
+
+  def reply_suggestion_body
+    {
+      model: GPT_MODEL,
+      messages: [
+        { role: 'system',
+          content: prompt_from_file('reply', enterprise: false) }
+      ].concat(conversation_messages(in_array_format: true))
+    }.to_json
+  end
+end
+
+Integrations::Openai::ProcessorService.prepend_mod_with('Integrations::OpenaiProcessorService')