mkdir -p ~/.praison/templates/voice-to-voice-translator-lite
cd ~/.praison/templates/voice-to-voice-translator-lite

name: voice-to-voice-translator-lite
version: "1.0.0"
description: "Translate spoken audio with optional TTS output"
author: "PraisonAI"
license: "MIT"

tags:
  - audio
  - translation
  - voice
  - tts

requires:
  env:
    - OPENAI_API_KEY
  packages:
    - praisonaiagents
  optional_env:
    - ELEVENLABS_API_KEY

inputs:
  audio_path:
    type: string
    description: "Path to the source audio file"
    required: true
  target_language:
    type: string
    description: "Target language code (e.g., es, fr, de)"
    required: true
  voice_style:
    type: string
    description: "TTS voice style"
    required: false
    default: "neutral"
    enum:
      - neutral
      - friendly
      - professional
      - energetic

outputs:
  translated_audio_file:
    type: string
    description: "Path to translated audio file (null if TTS unavailable)"
  transcript_file:
    type: string
    description: "Path to translated transcript"
  ok:
    type: boolean
    description: "Success indicator"

cli:
  command: "praison recipes run voice-to-voice-translator-lite"
  examples:
    - 'praison recipes run voice-to-voice-translator-lite --input ''{"audio_path": "speech.mp3", "target_language": "es"}'''

safety:
  dry_run_default: false
  requires_consent: false
  overwrites_files: true
  network_access: true
  pii_handling: true

# recipe.py
import os
from pathlib import Path
from praisonaiagents import Agent, Task, PraisonAIAgents

def run(input_data: dict, config: dict = None) -> dict:
    """
    Translate spoken audio to another language.
    """
    audio_path = input_data.get("audio_path")
    target_language = input_data.get("target_language")
    voice_style = input_data.get("voice_style", "neutral")
    
    if not audio_path:
        return {"ok": False, "error": {"code": "MISSING_INPUT", "message": "audio_path is required"}}
    
    if not target_language:
        return {"ok": False, "error": {"code": "MISSING_INPUT", "message": "target_language is required"}}
    
    if not os.path.exists(audio_path):
        return {"ok": False, "error": {"code": "FILE_NOT_FOUND", "message": f"Audio file not found: {audio_path}"}}
    
    try:
        # Create transcription agent
        transcriber = Agent(
            name="Speech Transcriber",
            role="Speech Recognition Specialist",
            goal="Accurately transcribe spoken audio",
            instructions="""
            You are a speech recognition expert.
            - Transcribe speech accurately
            - Detect the source language
            - Handle accents and dialects
            - Note unclear sections
            """,
        )
        
        # Create translation agent
        translator = Agent(
            name="Voice Translator",
            role="Professional Translator",
            goal=f"Translate speech naturally to {target_language}",
            instructions=f"""
            You are a professional translator specializing in spoken language.
            - Translate to {target_language} naturally
            - Preserve tone and intent
            - Adapt idioms appropriately
            - Keep the conversational style
            """,
        )
        
        # Define tasks
        transcribe_task = Task(
            name="transcribe_speech",
            description=f"Transcribe the audio from: {audio_path}",
            expected_output="Transcribed text with detected language",
            agent=transcriber,
        )
        
        translate_task = Task(
            name="translate_speech",
            description=f"Translate the transcription to {target_language}",
            expected_output=f"Natural {target_language} translation",
            agent=translator,
            context=[transcribe_task],
        )
        
        # Execute
        agents = PraisonAIAgents(
            agents=[transcriber, translator],
            tasks=[transcribe_task, translate_task],
        )
        
        result = agents.start()
        
        # Save transcript
        audio_name = Path(audio_path).stem
        transcript_file = f"{audio_name}_{target_language}_transcript.txt"
        
        translated_text = result.get("translate_speech", "")
        with open(transcript_file, "w", encoding="utf-8") as f:
            f.write(translated_text)
        
        # Attempt TTS if available
        translated_audio_file = None
        warnings = []
        
        tts_available = check_tts_availability()
        if tts_available:
            try:
                translated_audio_file = generate_tts(
                    translated_text,
                    target_language,
                    voice_style,
                    f"{audio_name}_{target_language}.mp3"
                )
            except Exception as e:
                warnings.append(f"TTS generation failed: {str(e)}. Transcript saved.")
        else:
            warnings.append("TTS not configured. Set ELEVENLABS_API_KEY for audio output.")
        
        artifacts = [{"path": transcript_file, "type": "text", "size_bytes": os.path.getsize(transcript_file)}]
        if translated_audio_file and os.path.exists(translated_audio_file):
            artifacts.append({"path": translated_audio_file, "type": "audio", "size_bytes": os.path.getsize(translated_audio_file)})
        
        return {
            "ok": True,
            "translated_audio_file": translated_audio_file,
            "transcript_file": transcript_file,
            "artifacts": artifacts,
            "warnings": warnings,
        }
        
    except Exception as e:
        return {"ok": False, "error": {"code": "PROCESSING_ERROR", "message": str(e)}}


def check_tts_availability() -> bool:
    """Check if TTS service is available."""
    return bool(os.environ.get("ELEVENLABS_API_KEY"))


def generate_tts(text: str, language: str, style: str, output_path: str) -> str:
    """Generate TTS audio. Returns output path or raises exception."""
    # Placeholder for TTS implementation
    # In production, integrate with ElevenLabs, Google TTS, or similar
    
    api_key = os.environ.get("ELEVENLABS_API_KEY")
    if not api_key:
        raise RuntimeError("TTS API key not configured")
    
    # Example ElevenLabs integration (simplified)
    # import requests
    # response = requests.post(
    #     "https://api.elevenlabs.io/v1/text-to-speech/...",
    #     headers={"xi-api-key": api_key},
    #     json={"text": text, "voice_settings": {...}}
    # )
    # with open(output_path, "wb") as f:
    #     f.write(response.content)
    
    # For now, create placeholder
    with open(output_path, "wb") as f:
        f.write(b"")  # Placeholder
    
    return output_path

# test_recipe.py
import pytest
from recipe import run, check_tts_availability

def test_missing_audio_path():
    result = run({"target_language": "es"})
    assert result["ok"] is False
    assert result["error"]["code"] == "MISSING_INPUT"

def test_missing_target_language():
    result = run({"audio_path": "test.mp3"})
    assert result["ok"] is False
    assert result["error"]["code"] == "MISSING_INPUT"

def test_file_not_found():
    result = run({"audio_path": "/nonexistent.mp3", "target_language": "es"})
    assert result["ok"] is False

def test_tts_availability_check():
    # Should return False without API key
    import os
    original = os.environ.get("ELEVENLABS_API_KEY")
    if "ELEVENLABS_API_KEY" in os.environ:
        del os.environ["ELEVENLABS_API_KEY"]
    
    assert check_tts_availability() is False
    
    if original:
        os.environ["ELEVENLABS_API_KEY"] = original

@pytest.mark.integration
def test_transcript_only():
    """Test that transcript is generated even without TTS."""
    import os
    import tempfile
    
    test_audio = os.environ.get("TEST_AUDIO_PATH")
    if not test_audio:
        pytest.skip("No test audio available")
    
    result = run({
        "audio_path": test_audio,
        "target_language": "es"
    })
    
    assert result["ok"] is True
    assert result["transcript_file"] is not None