feat: separate service for editor tasks
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@@ -0,0 +1,175 @@
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class Captain::BaseEditorService
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include Integrations::LlmInstrumentation
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# gpt-4o-mini supports 128,000 tokens
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# 1 token is approx 4 characters
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# sticking with 120000 to be safe
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# 120000 * 4 = 480,000 characters (rounding off downwards to 400,000 to be safe)
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TOKEN_LIMIT = 400_000
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GPT_MODEL = Llm::Config::DEFAULT_MODEL
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ALLOWED_EVENT_NAMES = %w[fix_spelling_grammar casual professional friendly confident
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straightforward improve].freeze
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CACHEABLE_EVENTS = %w[].freeze
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pattr_initialize [:account!, :event!]
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def perform
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return nil unless valid_event_name?
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return value_from_cache if value_from_cache.present?
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response = send("#{event_name}_message")
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save_to_cache(response) if response.present?
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response
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end
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private
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def event_name
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event['name']
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end
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def cache_key
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return nil unless event_is_cacheable?
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return nil unless conversation
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# since the value from cache depends on the conversation last_activity_at, it will always be fresh
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format(::Redis::Alfred::OPENAI_CONVERSATION_KEY, event_name: event_name, conversation_id: conversation.id,
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updated_at: conversation.last_activity_at.to_i)
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end
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def value_from_cache
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return nil unless event_is_cacheable?
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return nil if cache_key.blank?
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deserialize_cached_value(Redis::Alfred.get(cache_key))
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end
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def deserialize_cached_value(value)
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return nil if value.blank?
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JSON.parse(value, symbolize_names: true)
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rescue JSON::ParserError
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# If json parse failed, returning the value as is will fail too
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# since we access the keys as symbols down the line
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# So it's best to return nil
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nil
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end
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def save_to_cache(response)
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return nil unless event_is_cacheable?
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# Serialize to JSON
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# This makes parsing easy when response is a hash
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Redis::Alfred.setex(cache_key, response.to_json)
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end
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def conversation
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@conversation ||= account.conversations.find_by(display_id: event['data']['conversation_display_id'])
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end
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def valid_event_name?
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# self.class::ALLOWED_EVENT_NAMES is way to access ALLOWED_EVENT_NAMES defined in the class hierarchy of the current object.
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# This ensures that if ALLOWED_EVENT_NAMES is updated elsewhere in it's ancestors, we access the latest value.
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self.class::ALLOWED_EVENT_NAMES.include?(event_name)
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end
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def event_is_cacheable?
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# self.class::CACHEABLE_EVENTS is way to access CACHEABLE_EVENTS defined in the class hierarchy of the current object.
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# This ensures that if CACHEABLE_EVENTS is updated elsewhere in it's ancestors, we access the latest value.
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self.class::CACHEABLE_EVENTS.include?(event_name)
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end
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def api_base
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endpoint = InstallationConfig.find_by(name: 'CAPTAIN_OPEN_AI_ENDPOINT')&.value.presence || 'https://api.openai.com/'
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endpoint = endpoint.chomp('/')
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"#{endpoint}/v1"
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end
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def make_api_call(body)
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parsed_body = JSON.parse(body)
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instrumentation_params = build_instrumentation_params(parsed_body)
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instrument_llm_call(instrumentation_params) do
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execute_ruby_llm_request(parsed_body)
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end
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end
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def execute_ruby_llm_request(parsed_body)
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messages = parsed_body['messages']
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model = parsed_body['model']
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Llm::Config.with_api_key(api_key, api_base: api_base) do |context|
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chat = context.chat(model: model)
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setup_chat_with_messages(chat, messages)
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end
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rescue StandardError => e
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ChatwootExceptionTracker.new(e, account: account).capture_exception
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build_error_response_from_exception(e, messages)
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end
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def setup_chat_with_messages(chat, messages)
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apply_system_instructions(chat, messages)
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response = send_conversation_messages(chat, messages)
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return { error: 'No conversation messages provided', error_code: 400, request_messages: messages } if response.nil?
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build_ruby_llm_response(response, messages)
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end
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def apply_system_instructions(chat, messages)
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system_msg = messages.find { |m| m['role'] == 'system' }
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chat.with_instructions(system_msg['content']) if system_msg
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end
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def send_conversation_messages(chat, messages)
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conversation_messages = messages.reject { |m| m['role'] == 'system' }
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return nil if conversation_messages.empty?
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return chat.ask(conversation_messages.first['content']) if conversation_messages.length == 1
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add_conversation_history(chat, conversation_messages[0...-1])
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chat.ask(conversation_messages.last['content'])
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end
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def add_conversation_history(chat, messages)
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messages.each do |msg|
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chat.add_message(role: msg['role'].to_sym, content: msg['content'])
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end
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end
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def build_ruby_llm_response(response, messages)
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{
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message: response.content,
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usage: {
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'prompt_tokens' => response.input_tokens,
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'completion_tokens' => response.output_tokens,
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'total_tokens' => (response.input_tokens || 0) + (response.output_tokens || 0)
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},
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request_messages: messages
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}
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end
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def build_instrumentation_params(parsed_body)
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{
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span_name: "llm.#{event_name}",
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account_id: account.id,
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conversation_id: conversation&.display_id,
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feature_name: event_name,
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model: parsed_body['model'],
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messages: parsed_body['messages'],
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temperature: parsed_body['temperature']
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}
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end
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def build_error_response_from_exception(error, messages)
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{ error: error.message, request_messages: messages }
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end
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# To be overridden by child class
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def api_key
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raise NotImplementedError, 'Subclasses must implement api_key method'
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end
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end
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@@ -0,0 +1,78 @@
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class Captain::EditorService < Captain::BaseEditorService
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def fix_spelling_grammar_message
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call_llm_with_prompt(fix_spelling_grammar_prompt)
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end
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def confident_message
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call_llm_with_prompt(tone_rewrite_prompt('confident'))
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end
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def straightforward_message
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call_llm_with_prompt(tone_rewrite_prompt('straightforward'))
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end
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def casual_message
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call_llm_with_prompt(tone_rewrite_prompt('casual'))
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end
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def friendly_message
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call_llm_with_prompt(tone_rewrite_prompt('friendly'))
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end
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def professional_message
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call_llm_with_prompt(tone_rewrite_prompt('professional'))
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end
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def improve_message
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template = prompt_from_file('improve')
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system_prompt = render_liquid_template(template, {
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'conversation_context' => conversation.to_llm_text(include_contact_details: true),
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'draft_message' => event['data']['content']
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})
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call_llm_with_prompt(system_prompt, event['data']['content'])
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end
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private
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def api_key
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@api_key ||= openai_hook&.settings&.dig('api_key') || system_api_key
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end
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def openai_hook
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@openai_hook ||= account.hooks.find_by(app_id: 'openai', status: 'enabled')
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end
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def system_api_key
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@system_api_key ||= InstallationConfig.find_by(name: 'CAPTAIN_OPEN_AI_API_KEY')&.value
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end
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def call_llm_with_prompt(system_content, user_content = event['data']['content'])
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body = {
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model: GPT_MODEL,
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messages: [
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{ role: 'system', content: system_content },
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{ role: 'user', content: user_content }
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]
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}.to_json
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make_api_call(body)
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end
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def prompt_from_file(file_name)
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Rails.root.join('lib/integrations/openai/openai_prompts', "#{file_name}.liquid").read
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end
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def render_liquid_template(template_content, variables = {})
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Liquid::Template.parse(template_content).render(variables)
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end
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def tone_rewrite_prompt(tone)
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template = prompt_from_file('tone_rewrite')
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render_liquid_template(template, 'tone' => tone)
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end
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def fix_spelling_grammar_prompt
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prompt_from_file('fix_spelling_grammar')
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end
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end
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