"""
LangSwarm V2 Voice Conversation Manager

Real-time voice conversation support for V2 agents with speech-to-text,
text-to-speech, and voice activity detection capabilities.
"""

import asyncio
import logging
from typing import Dict, Optional, AsyncIterator, Any, List
from datetime import datetime
import uuid

from .interfaces import (
    IVoiceConversation, VoiceSegment, RealtimeConfiguration,
    VoiceState, VoiceError
)


class VoiceConversationManager(IVoiceConversation):
    """
    Voice conversation manager for real-time agent communication.
    
    Provides voice-based interaction with agents including speech recognition,
    text-to-speech synthesis, and voice activity detection.
    """
    
    def __init__(self, agent_id: str, config: RealtimeConfiguration):
        """
        Initialize voice conversation manager.
        
        Args:
            agent_id: Agent identifier for voice conversation
            config: Real-time configuration
        """
        self.agent_id = agent_id
        self.config = config
        self._logger = logging.getLogger(f"{__name__}.{agent_id}")
        
        # Voice state
        self._state = VoiceState.IDLE
        self._session_id: Optional[str] = None
        self._conversation_id: Optional[str] = None
        
        # Audio processing
        self._audio_buffer = []
        self._audio_queue = asyncio.Queue()
        self._voice_segments = asyncio.Queue()
        
        # Background tasks
        self._audio_processing_task: Optional[asyncio.Task] = None
        self._voice_detection_task: Optional[asyncio.Task] = None
        self._synthesis_task: Optional[asyncio.Task] = None
        
        # Voice processing components (placeholders for real implementations)
        self._speech_recognizer = None
        self._speech_synthesizer = None
        self._voice_activity_detector = None
        
        # Statistics
        self._stats = {
            "conversation_start_time": None,
            "total_audio_duration": 0.0,
            "speech_segments_processed": 0,
            "synthesis_requests": 0,
            "recognition_accuracy": 0.0,
            "average_response_time": 0.0
        }
        
        self._logger.debug(f"Voice conversation manager initialized for agent: {agent_id}")
    
    @property
    def state(self) -> VoiceState:
        """Current voice conversation state"""
        return self._state
    
    @property
    def is_active(self) -> bool:
        """Check if voice conversation is active"""
        return self._state != VoiceState.IDLE
    
    @property
    def session_id(self) -> Optional[str]:
        """Get current voice session ID"""
        return self._session_id
    
    @property
    def conversation_id(self) -> Optional[str]:
        """Get current conversation ID"""
        return self._conversation_id
    
    async def start_conversation(self, agent_id: str) -> bool:
        """
        Start voice conversation with agent.
        
        Args:
            agent_id: Agent identifier to start conversation with
            
        Returns:
            True if conversation started successfully
        """
        if self.is_active:
            self._logger.warning("Voice conversation already active")
            return False
        
        try:
            self._logger.info(f"Starting voice conversation with agent: {agent_id}")
            
            # Initialize voice session
            self._session_id = str(uuid.uuid4())
            self._conversation_id = str(uuid.uuid4())
            self._state = VoiceState.LISTENING
            self._stats["conversation_start_time"] = datetime.utcnow()
            
            # Initialize voice processing components
            await self._initialize_voice_components()
            
            # Start background tasks
            await self._start_background_tasks()
            
            self._logger.info(f"Voice conversation started with agent: {agent_id}")
            return True
            
        except Exception as e:
            self._logger.error(f"Failed to start voice conversation with agent {agent_id}: {e}")
            self._state = VoiceState.ERROR
            return False
    
    async def stop_conversation(self) -> None:
        """Stop voice conversation"""
        if not self.is_active:
            return
        
        try:
            self._logger.info("Stopping voice conversation")
            
            # Stop background tasks
            await self._stop_background_tasks()
            
            # Cleanup voice components
            await self._cleanup_voice_components()
            
            # Reset state
            self._state = VoiceState.IDLE
            self._session_id = None
            self._conversation_id = None
            
            self._logger.info("Voice conversation stopped")
            
        except Exception as e:
            self._logger.error(f"Error stopping voice conversation: {e}")
            self._state = VoiceState.ERROR
    
    async def send_audio(self, audio_data: bytes) -> bool:
        """
        Send audio data to agent.
        
        Args:
            audio_data: Raw audio data to process
            
        Returns:
            True if audio sent successfully
        """
        if not self.is_active:
            self._logger.warning("Cannot send audio - conversation not active")
            return False
        
        try:
            # Create voice segment
            segment = VoiceSegment(
                audio_data=audio_data,
                duration=len(audio_data) / (self.config.voice_sample_rate * 2),  # Assuming 16-bit audio
                format=self.config.voice_format,
                sample_rate=self.config.voice_sample_rate
            )
            
            # Add to processing queue
            await self._audio_queue.put(segment)
            
            self._logger.debug(f"Queued audio segment for processing: {len(audio_data)} bytes")
            return True
            
        except Exception as e:
            self._logger.error(f"Failed to send audio data: {e}")
            return False
    
    async def receive_audio(self) -> AsyncIterator[VoiceSegment]:
        """
        Receive audio from agent.
        
        Yields:
            Voice segments from agent responses
        """
        while self.is_active:
            try:
                # Get voice segment from queue (populated by synthesis task)
                segment = await asyncio.wait_for(
                    self._voice_segments.get(),
                    timeout=1.0
                )
                
                yield segment
                
            except asyncio.TimeoutError:
                # Continue waiting for voice segments
                continue
            except Exception as e:
                self._logger.error(f"Error receiving audio: {e}")
                break
    
    async def process_speech(self, audio_data: bytes) -> Optional[str]:
        """
        Process speech to text.
        
        Args:
            audio_data: Audio data to transcribe
            
        Returns:
            Transcribed text or None if processing failed
        """
        if not self.is_active:
            self._logger.warning("Cannot process speech - conversation not active")
            return None
        
        try:
            self._state = VoiceState.PROCESSING
            
            # Create voice segment
            segment = VoiceSegment(
                audio_data=audio_data,
                duration=len(audio_data) / (self.config.voice_sample_rate * 2),
                format=self.config.voice_format,
                sample_rate=self.config.voice_sample_rate
            )
            
            # Process with speech recognizer (placeholder implementation)
            transcript = await self._transcribe_audio(segment)
            
            if transcript:
                segment.transcript = transcript
                segment.confidence = 0.85  # Placeholder confidence score
                self._stats["speech_segments_processed"] += 1
            
            self._state = VoiceState.LISTENING
            return transcript
            
        except Exception as e:
            self._logger.error(f"Failed to process speech: {e}")
            self._state = VoiceState.ERROR
            return None
    
    async def synthesize_speech(self, text: str) -> Optional[VoiceSegment]:
        """
        Synthesize text to speech.
        
        Args:
            text: Text to synthesize
            
        Returns:
            Voice segment with synthesized audio or None if failed
        """
        if not self.is_active:
            self._logger.warning("Cannot synthesize speech - conversation not active")
            return None
        
        try:
            self._state = VoiceState.SPEAKING
            
            # Synthesize audio (placeholder implementation)
            audio_data = await self._synthesize_audio(text)
            
            if audio_data:
                segment = VoiceSegment(
                    audio_data=audio_data,
                    duration=len(audio_data) / (self.config.voice_sample_rate * 2),
                    format=self.config.voice_format,
                    sample_rate=self.config.voice_sample_rate,
                    transcript=text,
                    confidence=1.0
                )
                
                self._stats["synthesis_requests"] += 1
                self._state = VoiceState.LISTENING
                return segment
            
            self._state = VoiceState.LISTENING
            return None
            
        except Exception as e:
            self._logger.error(f"Failed to synthesize speech: {e}")
            self._state = VoiceState.ERROR
            return None
    
    async def get_statistics(self) -> Dict[str, Any]:
        """
        Get voice conversation statistics.
        
        Returns:
            Dictionary of statistics
        """
        return {
            **self._stats,
            "agent_id": self.agent_id,
            "session_id": self._session_id,
            "conversation_id": self._conversation_id,
            "state": self._state.value,
            "is_active": self.is_active,
            "queue_sizes": {
                "audio_queue": self._audio_queue.qsize(),
                "voice_segments": self._voice_segments.qsize()
            },
            "config": {
                "sample_rate": self.config.voice_sample_rate,
                "format": self.config.voice_format,
                "chunk_size": self.config.voice_chunk_size
            }
        }
    
    async def _initialize_voice_components(self) -> None:
        """Initialize voice processing components"""
        try:
            # Initialize speech recognizer (placeholder)
            self._speech_recognizer = await self._create_speech_recognizer()
            
            # Initialize speech synthesizer (placeholder)
            self._speech_synthesizer = await self._create_speech_synthesizer()
            
            # Initialize voice activity detector (placeholder)
            self._voice_activity_detector = await self._create_voice_activity_detector()
            
            self._logger.debug("Voice processing components initialized")
            
        except Exception as e:
            self._logger.error(f"Failed to initialize voice components: {e}")
            raise VoiceError(f"Voice component initialization failed: {e}")
    
    async def _cleanup_voice_components(self) -> None:
        """Cleanup voice processing components"""
        try:
            if self._speech_recognizer:
                # Cleanup speech recognizer
                pass
            
            if self._speech_synthesizer:
                # Cleanup speech synthesizer
                pass
            
            if self._voice_activity_detector:
                # Cleanup voice activity detector
                pass
            
            self._logger.debug("Voice processing components cleaned up")
            
        except Exception as e:
            self._logger.error(f"Error cleaning up voice components: {e}")
    
    async def _start_background_tasks(self) -> None:
        """Start background tasks for voice processing"""
        # Start audio processing task
        self._audio_processing_task = asyncio.create_task(self._audio_processing_loop())
        
        # Start voice detection task
        self._voice_detection_task = asyncio.create_task(self._voice_detection_loop())
        
        # Start synthesis task
        self._synthesis_task = asyncio.create_task(self._synthesis_loop())
    
    async def _stop_background_tasks(self) -> None:
        """Stop background tasks"""
        tasks = [
            self._audio_processing_task,
            self._voice_detection_task,
            self._synthesis_task
        ]
        
        for task in tasks:
            if task:
                task.cancel()
                try:
                    await task
                except asyncio.CancelledError:
                    pass
        
        self._audio_processing_task = None
        self._voice_detection_task = None
        self._synthesis_task = None
    
    async def _audio_processing_loop(self) -> None:
        """Background task for processing audio segments"""
        while self.is_active:
            try:
                # Get audio segment from queue
                segment = await asyncio.wait_for(
                    self._audio_queue.get(),
                    timeout=1.0
                )
                
                # Process audio segment
                await self._process_audio_segment(segment)
                
            except asyncio.TimeoutError:
                continue
            except asyncio.CancelledError:
                break
            except Exception as e:
                self._logger.error(f"Error in audio processing loop: {e}")
    
    async def _voice_detection_loop(self) -> None:
        """Background task for voice activity detection"""
        while self.is_active:
            try:
                # Perform voice activity detection
                await asyncio.sleep(0.1)  # Placeholder delay
                
                # Voice activity detection logic would go here
                
            except asyncio.CancelledError:
                break
            except Exception as e:
                self._logger.error(f"Error in voice detection loop: {e}")
    
    async def _synthesis_loop(self) -> None:
        """Background task for speech synthesis"""
        while self.is_active:
            try:
                # Handle synthesis requests
                await asyncio.sleep(0.1)  # Placeholder delay
                
                # Speech synthesis logic would go here
                
            except asyncio.CancelledError:
                break
            except Exception as e:
                self._logger.error(f"Error in synthesis loop: {e}")
    
    async def _process_audio_segment(self, segment: VoiceSegment) -> None:
        """Process individual audio segment"""
        try:
            # Transcribe audio
            transcript = await self._transcribe_audio(segment)
            
            if transcript:
                segment.transcript = transcript
                self._logger.debug(f"Transcribed: {transcript}")
                
                # Send to agent for processing (placeholder)
                # await self._send_to_agent(transcript)
            
        except Exception as e:
            self._logger.error(f"Error processing audio segment: {e}")
    
    async def _transcribe_audio(self, segment: VoiceSegment) -> Optional[str]:
        """Transcribe audio segment to text (placeholder implementation)"""
        try:
            # Placeholder transcription logic
            # In real implementation, would use speech recognition service
            if len(segment.audio_data) > 0:
                return "Transcribed text placeholder"
            return None
            
        except Exception as e:
            self._logger.error(f"Transcription failed: {e}")
            return None
    
    async def _synthesize_audio(self, text: str) -> Optional[bytes]:
        """Synthesize text to audio (placeholder implementation)"""
        try:
            # Placeholder synthesis logic
            # In real implementation, would use text-to-speech service
            if text:
                # Return placeholder audio data
                return b"audio_data_placeholder" * 100
            return None
            
        except Exception as e:
            self._logger.error(f"Synthesis failed: {e}")
            return None
    
    async def _create_speech_recognizer(self):
        """Create speech recognizer instance (placeholder)"""
        # Placeholder for speech recognizer initialization
        return "speech_recognizer_placeholder"
    
    async def _create_speech_synthesizer(self):
        """Create speech synthesizer instance (placeholder)"""
        # Placeholder for speech synthesizer initialization
        return "speech_synthesizer_placeholder"
    
    async def _create_voice_activity_detector(self):
        """Create voice activity detector instance (placeholder)"""
        # Placeholder for voice activity detector initialization
        return "voice_activity_detector_placeholder"


class VoiceProcessor:
    """
    Voice processing utilities for audio handling and conversion.
    
    Provides audio format conversion, noise reduction, and other
    voice processing capabilities.
    """
    
    def __init__(self, config: RealtimeConfiguration):
        """
        Initialize voice processor.
        
        Args:
            config: Real-time configuration
        """
        self.config = config
        self._logger = logging.getLogger(__name__)
    
    async def convert_audio_format(self, audio_data: bytes, source_format: str, target_format: str) -> bytes:
        """Convert audio between formats"""
        # Placeholder implementation
        return audio_data
    
    async def reduce_noise(self, audio_data: bytes) -> bytes:
        """Apply noise reduction to audio"""
        # Placeholder implementation
        return audio_data
    
    async def normalize_volume(self, audio_data: bytes) -> bytes:
        """Normalize audio volume"""
        # Placeholder implementation
        return audio_data


class AudioStreamer:
    """
    Audio streaming utilities for real-time audio transmission.
    
    Handles audio streaming, buffering, and real-time transmission
    of voice data.
    """
    
    def __init__(self, config: RealtimeConfiguration):
        """
        Initialize audio streamer.
        
        Args:
            config: Real-time configuration
        """
        self.config = config
        self._logger = logging.getLogger(__name__)
        
        # Streaming state
        self._streaming = False
        self._audio_buffer = []
    
    async def start_streaming(self) -> bool:
        """Start audio streaming"""
        try:
            self._streaming = True
            self._logger.info("Audio streaming started")
            return True
        except Exception as e:
            self._logger.error(f"Failed to start audio streaming: {e}")
            return False
    
    async def stop_streaming(self) -> None:
        """Stop audio streaming"""
        self._streaming = False
        self._audio_buffer.clear()
        self._logger.info("Audio streaming stopped")
    
    async def stream_audio(self, audio_data: bytes) -> bool:
        """Stream audio data"""
        if not self._streaming:
            return False
        
        try:
            # Add to buffer and stream
            self._audio_buffer.append(audio_data)
            
            # Stream buffered audio
            await self._flush_buffer()
            
            return True
        except Exception as e:
            self._logger.error(f"Failed to stream audio: {e}")
            return False
    
    async def _flush_buffer(self) -> None:
        """Flush audio buffer"""
        # Placeholder implementation for streaming buffered audio
        if self._audio_buffer:
            self._audio_buffer.clear()


# Factory functions
def create_voice_conversation(agent_id: str, config: RealtimeConfiguration) -> VoiceConversationManager:
    """Create a new voice conversation manager"""
    return VoiceConversationManager(agent_id, config)


async def start_voice_session(agent_id: str, config: Optional[RealtimeConfiguration] = None) -> Optional[VoiceConversationManager]:
    """Start a voice session with an agent"""
    if not config:
        config = RealtimeConfiguration(voice_enabled=True)
    
    voice_manager = VoiceConversationManager(agent_id, config)
    success = await voice_manager.start_conversation(agent_id)
    
    if success:
        return voice_manager
    return None
