Files
clientsflow/research/chatwoot/enterprise/app/services/messages/audio_transcription_service.rb

112 lines
2.9 KiB
Ruby

class Messages::AudioTranscriptionService< Llm::LegacyBaseOpenAiService
include Integrations::LlmInstrumentation
WHISPER_MODEL = 'whisper-1'.freeze
attr_reader :attachment, :message, :account
def initialize(attachment)
super()
@attachment = attachment
@message = attachment.message
@account = message.account
end
def perform
return { error: 'Transcription limit exceeded' } unless can_transcribe?
return { error: 'Message not found' } if message.blank?
transcriptions = transcribe_audio
Rails.logger.info "Audio transcription successful: #{transcriptions}"
{ success: true, transcriptions: transcriptions }
end
private
def can_transcribe?
return false unless account.feature_enabled?('captain_integration')
return false if account.audio_transcriptions.blank?
account.usage_limits[:captain][:responses][:current_available].positive?
end
def fetch_audio_file
blob = attachment.file.blob
temp_dir = Rails.root.join('tmp/uploads/audio-transcriptions')
FileUtils.mkdir_p(temp_dir)
temp_file_name = "#{blob.key}-#{blob.filename}"
if blob.filename.extension_without_delimiter.blank?
extension = extension_from_content_type(blob.content_type)
temp_file_name = "#{temp_file_name}.#{extension}" if extension.present?
end
temp_file_path = File.join(temp_dir, temp_file_name)
File.open(temp_file_path, 'wb') do |file|
blob.open do |blob_file|
IO.copy_stream(blob_file, file)
end
end
temp_file_path
end
def transcribe_audio
transcribed_text = attachment.meta&.[]('transcribed_text') || ''
return transcribed_text if transcribed_text.present?
temp_file_path = fetch_audio_file
transcribed_text = nil
File.open(temp_file_path, 'rb') do |file|
response = @client.audio.transcribe(
parameters: {
model: WHISPER_MODEL,
file: file,
temperature: 0.4
}
)
transcribed_text = response['text']
end
update_transcription(transcribed_text)
transcribed_text
ensure
FileUtils.rm_f(temp_file_path) if temp_file_path.present?
end
def instrumentation_params(file_path)
{
span_name: 'llm.messages.audio_transcription',
model: WHISPER_MODEL,
account_id: account&.id,
feature_name: 'audio_transcription',
file_path: file_path
}
end
def update_transcription(transcribed_text)
return if transcribed_text.blank?
attachment.update!(meta: { transcribed_text: transcribed_text })
message.reload.send_update_event
message.account.increment_response_usage
return unless ChatwootApp.advanced_search_allowed?
message.reindex
end
def extension_from_content_type(content_type)
subtype = content_type.to_s.downcase.split(';').first.to_s.split('/').last.to_s
return if subtype.blank?
{
'x-m4a' => 'm4a',
'x-wav' => 'wav',
'x-mp3' => 'mp3'
}.fetch(subtype, subtype)
end
end