# Generate a transcriber rails generate ruby_llm_agents:transcriber meeting # app/agents/audio/meeting_transcriber.rb class MeetingTranscriber < ApplicationTranscriber model "whisper-1" language "en" end # Usage result = Audio::MeetingTranscriber.call(audio: "meeting.mp3") result.text # "Hello, welcome to the meeting..." result.audio_duration # 120.5 (seconds) result.total_cost # 0.012

class MyTranscriber < ApplicationTranscriber # Model selection model "whisper-1" # Default transcription model # Alternatives: "gpt-4o-transcribe", "gpt-4o-mini-transcribe" # Language settings language "en" # ISO 639-1 code (nil = auto-detect) # Output format output_format :text # :text, :json, :srt, :vtt # Timestamp granularity include_timestamps :segment # :none, :segment, :word # Caching cache_for 30.days # Enable caching # Optional: Provide context for better accuracy def prompt "Technical discussion about Ruby programming" end # Optional: Post-process transcription def postprocess_text(text) text .gsub(/\bum\b/i, '') # Remove filler words .gsub(/\buh\b/i, '') .squeeze(' ') end end

# From file path result = Audio::MeetingTranscriber.call(audio: "meeting.mp3") # From URL result = Audio::MeetingTranscriber.call(audio: "https://example.com/audio.mp3") # From File object result = Audio::MeetingTranscriber.call(audio: File.open("meeting.mp3")) # From binary data with format hint result = Audio::MeetingTranscriber.call(audio: audio_blob, format: :mp3)

class ReliableTranscriber < ApplicationTranscriber model "gpt-4o-transcribe" reliability do retry_on_failure max_attempts: 3 end fallback_models "whisper-1", "gpt-4o-mini-transcribe" end

result = Audio::MeetingTranscriber.call(audio: "meeting.mp3") # Text content result.text # Full transcription text result.segments # Array of segments with timestamps result.words # Array of words with timestamps (if requested) # Audio metadata result.audio_duration # Duration in seconds result.audio_format # Detected format result.language # Requested language result.detected_language # Auto-detected language # Execution metadata result.model_id # Model used result.duration_ms # Processing time result.total_cost # Cost in USD result.started_at # Execution start time result.completed_at # Execution end time result.tenant_id # Multi-tenant identifier # Status result.success? # true if no error result.error? # true if failed # Subtitle generation result.srt # SRT subtitle format result.vtt # VTT subtitle format # Analysis helpers result.words_per_minute # Speaking rate result.segment_at(30.5) # Find segment at timestamp result.text_between(10, 60) # Get text in time range

class SubtitleTranscriber < ApplicationTranscriber model "whisper-1" include_timestamps :segment end result = Audio::SubtitleTranscriber.call(audio: "video.mp4") # Save as SRT (for video players) File.write("captions.srt", result.srt) # Save as VTT (for web video) File.write("captions.vtt", result.vtt)

# Generate a speaker rails generate ruby_llm_agents:speaker narrator # app/agents/audio/narrator_speaker.rb class NarratorSpeaker < ApplicationSpeaker provider :openai model "tts-1" voice "nova" end # Usage result = Audio::NarratorSpeaker.call(text: "Hello, world!") result.audio # Binary audio data result.save_to("output.mp3")

class MyNarrator < ApplicationSpeaker # Provider selection provider :openai # :openai, :elevenlabs # Model and voice model "tts-1-hd" # "tts-1" for faster/cheaper voice "nova" # Voice name # OpenAI voices: alloy, echo, fable, nova, onyx, shimmer # Voice ID (ElevenLabs) voice_id "21m00Tcm..." # Voice ID for cloned voices # Audio settings speed 1.0 # Speech speed (0.25-4.0 for OpenAI) output_format :mp3 # :mp3, :wav, :opus, :pcm, :alaw, :ulaw # Or use ElevenLabs native format strings directly: # output_format "mp3_44100_192" # High-bitrate MP3 # output_format "opus_48000_64" # Low-latency Opus # output_format "pcm_16000" # Telephony PCM # Streaming streaming true # Enable streaming mode # Caching cache_for 7.days # Enable caching # Custom pronunciation lexicon lexicon do pronounce "API", "A P I" pronounce "SQL", "sequel" pronounce "RubyLLM", "ruby L L M" pronounce "nginx", "engine-X" end end

result = Audio::ArticleNarrator.call(text: "Hello!") # Audio data result.audio # Binary audio data result.save_to(path) # Save to file result.to_base64 # Base64 encoded result.to_data_uri # Data URI for web embedding # Metadata result.duration # Audio duration (seconds) result.format # Output format (:mp3, :wav, etc.) result.file_size # Size in bytes result.characters # Input character count # Provider info result.provider # :openai, :elevenlabs result.model_id # Model used result.voice_id # Voice identifier result.voice_name # Voice name # Execution result.duration_ms # Processing time result.total_cost # Cost in USD result.started_at # Execution start time result.completed_at # Execution end time result.tenant_id # Multi-tenant identifier result.success? # true if no error

class StreamingNarrator < ApplicationSpeaker provider :elevenlabs voice "Rachel" streaming true end # Stream to audio player Audio::StreamingNarrator.stream(text: "Long article...") do |chunk| audio_player.play(chunk.audio) end # Force streaming on any speaker Audio::ArticleNarrator.stream(text: "Hello!") do |chunk| buffer << chunk.audio end

class PremiumNarrator < ApplicationSpeaker provider :elevenlabs model "eleven_multilingual_v2" voice_id "21m00Tcm4TlvDq8ikWAM" # Voice settings specific to ElevenLabs voice_settings do stability 0.5 # 0-1: Lower = more expressive similarity_boost 0.75 # 0-1: Higher = closer to original voice style 0.5 # 0-1: Style exaggeration speaker_boost true # Enhance speaker clarity end end

class ReliableSpeaker < ApplicationSpeaker provider :elevenlabs voice "Rachel" reliability do retry_on_failure max_attempts: 3 end fallback_models "tts-1-hd", "tts-1" end

# config/initializers/ruby_llm_agents.rb RubyLLM::Agents.configure do |config| # Transcription defaults config.default_transcription_model = "whisper-1" config.track_transcriptions = true # TTS defaults config.default_tts_provider = :openai config.default_tts_model = "tts-1" config.default_tts_voice = "nova" config.track_speech = true # ElevenLabs (required for :elevenlabs provider) config.elevenlabs_api_key = ENV["ELEVENLABS_API_KEY"] config.elevenlabs_api_base = "https://api.elevenlabs.io" # optional, default # ElevenLabs dynamic pricing (fetches model data from /v1/models API) config.elevenlabs_base_cost_per_1k = 0.30 # Base cost × model multiplier (default: $0.30 Pro overage) config.elevenlabs_models_cache_ttl = 21_600 # Cache TTL in seconds (default: 6 hours) # TTS pricing overrides (per 1K characters) — takes priority over API pricing config.tts_model_pricing = { "eleven_v3" => 0.24, # custom rate "custom-model" => 0.10 } config.default_tts_cost = 0.015 # fallback for unknown models end

RubyLLM::Agents.configure do |c| c.transcription_model_pricing = { "whisper-1" => 0.006, "custom-model" => 0.05 } end

# Starter plan config.elevenlabs_base_cost_per_1k = 0.30 # Or override specific models directly config.tts_model_pricing = { "eleven_v3" => 0.24 }

# Simple symbols (convenience mapping) MyNarrator.call(text: "Hello", format: :mp3) # → mp3_44100_128 MyNarrator.call(text: "Hello", format: :wav) # → wav_44100 MyNarrator.call(text: "Hello", format: :opus) # → opus_48000_128 MyNarrator.call(text: "Hello", format: :pcm) # → pcm_24000 # Native format strings (precise control) MyNarrator.call(text: "Hello", format: "mp3_44100_192") # High-bitrate MP3 MyNarrator.call(text: "Hello", format: "pcm_16000") # Telephony PCM MyNarrator.call(text: "Hello", format: "opus_48000_64") # Low-bitrate Opus MyNarrator.call(text: "Hello", format: "wav_22050") # Low sample rate WAV

# Using resolver result = Audio::MeetingTranscriber.call(audio: "meeting.mp3") # Automatically uses Current.tenant if configured # Explicit tenant result = Audio::MeetingTranscriber.call( audio: "meeting.mp3", tenant: "acme_corp" ) # Tenant with budget limits result = Audio::ArticleNarrator.call( text: "Hello world", tenant: { id: "acme_corp", daily_limit: 50.0, enforcement: :hard } )

class MeetingTranscriber < ApplicationTranscriber model "whisper-1" language "en" include_timestamps :segment def prompt "Business meeting with technical discussions about software" end def postprocess_text(text) text .gsub(/\bum\b/i, '') .gsub(/\buh\b/i, '') .squeeze(' ') end end result = Audio::MeetingTranscriber.call(audio: "meeting.mp3") puts result.text puts "Duration: #{result.audio_duration} seconds" puts "Cost: $#{result.total_cost}"

class ArticleNarrator < ApplicationSpeaker provider :openai model "tts-1-hd" voice "nova" speed 1.1 lexicon do pronounce "API", "A P I" pronounce "JSON", "jay-son" end end result = Audio::ArticleNarrator.call(text: article_content) result.save_to("article_audio.mp3") puts "Duration: #{result.duration} seconds" puts "Cost: $#{result.total_cost}"

class VoiceAssistant def process_query(audio_file) # 1. Transcribe user's voice transcription = Audio::QueryTranscriber.call(audio: audio_file) # 2. Process with AI agent response = LLM::AssistantAgent.call(query: transcription.text) # 3. Convert response to speech speech = Audio::ResponseSpeaker.call(text: response.content) { transcription: transcription, response: response, speech: speech, total_cost: transcription.total_cost + response.total_cost + speech.total_cost } end end