import io
from dataclasses import dataclass
from typing import Optional

import aiohttp
from google.cloud import texttospeech
from pydub import AudioSegment

from ..core.config import settings
from ..core.logging import get_logger
from .gemini_tts import gemini_tts_service

logger = get_logger(__name__)


@dataclass
class TTSCueSegment:
    """Represents a synthesized audio segment for a single AD cue."""
    cue_index: int
    start_time: float  # Original VTT start time
    end_time: float    # Original VTT end time
    duration: float    # Actual TTS audio duration in seconds
    text: str          # The AD text that was synthesized
    audio_bytes: bytes # The raw MP3 audio bytes


class TTSService:
    def __init__(self):
        # Check Gemini TTS availability (uses same API key as other Gemini services)
        self.gemini_available = bool(settings.gemini_api_key)

        # Initialize Google Cloud TTS (uses GOOGLE_APPLICATION_CREDENTIALS env var)
        try:
            self.google_client = texttospeech.TextToSpeechClient()
            logger.info("Google Cloud TTS client initialized successfully")
        except Exception as e:
            logger.warning(f"Google Cloud TTS credentials not configured: {e}")
            self.google_client = None

        # Check ElevenLabs availability
        self.elevenlabs_available = bool(settings.elevenlabs_api_key)

        # Log configured provider
        logger.info(f"TTS provider configured: {settings.tts_provider}")

    async def synthesize_audio_description(
        self,
        ad_vtt_content: str,
        language_code: str = "en-US",
        voice_name: Optional[str] = None,
        provider: Optional[str] = None,
        model: str = "flash",
        speed: float = 1.0,
        style_prompt: str = "",
        stability: float = 0.5,
        similarity_boost: float = 0.5,
    ) -> bytes:
        """
        Generate MP3 audio from audio description VTT content.
        Synthesizes each cue separately and stitches them together with timing.

        Provider priority: specified provider > settings.tts_provider > fallback chain
        Fallback chain: Gemini -> Google Cloud TTS -> ElevenLabs

        Args:
            ad_vtt_content: VTT content with audio description cues
            language_code: Language code (e.g., "en-US")
            voice_name: Voice name/ID for the provider
            provider: TTS provider ("gemini", "google", "elevenlabs")
            model: Gemini model variant - "flash" or "pro" (Gemini only)
            speed: Speech rate multiplier 0.5-2.0 (Gemini only)
            style_prompt: Style instructions (Gemini only)
        """
        # Determine which provider to use
        active_provider = provider or settings.tts_provider

        # Extract simple language code for Gemini (e.g., "en-US" -> "en")
        simple_lang = language_code.split("-")[0] if "-" in language_code else language_code

        # Try the configured provider first, then fallback
        if active_provider == "gemini" and self.gemini_available:
            try:
                logger.info(
                    f"Using Gemini TTS for language: {simple_lang}, voice: {voice_name}, "
                    f"model: {model}, speed: {speed}x"
                )
                return await gemini_tts_service.synthesize_audio_description(
                    ad_vtt_content,
                    simple_lang,
                    voice_name,
                    model=model,
                    speed=speed,
                    style_prompt=style_prompt
                )
            except Exception as e:
                logger.warning(f"Gemini TTS failed, falling back: {e}")
                # Fall through to Google/ElevenLabs

        if active_provider == "google" or (active_provider == "gemini" and self.google_client):
            try:
                if self.google_client:
                    logger.info(f"Using Google Cloud TTS for language: {language_code}")
                    return await self._synthesize_with_google(ad_vtt_content, language_code, voice_name)
            except Exception as e:
                logger.warning(f"Google Cloud TTS failed: {e}")

        if self.elevenlabs_available:
            logger.info(f"Using ElevenLabs TTS for language: {language_code}")
            return await self._synthesize_with_elevenlabs(
                ad_vtt_content, language_code, voice_name,
                stability=stability, similarity_boost=similarity_boost,
            )

        raise ValueError("No TTS service available")

    async def synthesize_audio_description_with_segments(
        self,
        ad_vtt_content: str,
        language_code: str = "en-US",
        voice_name: Optional[str] = None,
        provider: Optional[str] = None,
        model: str = "flash",
        speed: float = 1.0,
        style_prompt: str = "",
        stability: float = 0.5,
        similarity_boost: float = 0.5,
    ) -> tuple[bytes, list[TTSCueSegment]]:
        """
        Generate MP3 audio from audio description VTT content AND return individual segments.
        Used for accessible video generation where we need per-cue audio files.

        Returns:
            Tuple of (combined_mp3_bytes, list_of_cue_segments)
        """
        # Determine which provider to use
        active_provider = provider or settings.tts_provider

        # Extract simple language code for Gemini (e.g., "en-US" -> "en")
        simple_lang = language_code.split("-")[0] if "-" in language_code else language_code

        # Parse VTT cues first
        cues = self._parse_ad_cues(ad_vtt_content)
        if not cues:
            raise ValueError("No audio description cues found")

        # Synthesize each cue individually
        segments: list[TTSCueSegment] = []
        audio_segments_for_combine = []
        current_audio_position = 0.0

        for i, cue in enumerate(cues):
            target_start_time = cue["start_time"]

            # Add silence to reach the exact VTT start time
            if target_start_time > current_audio_position:
                silence_duration = target_start_time - current_audio_position
                silence = AudioSegment.silent(duration=int(silence_duration * 1000))
                audio_segments_for_combine.append(silence)
                current_audio_position = target_start_time

            text = cue["text"].strip()
            if text:
                # Ensure proper punctuation for natural TTS flow
                if not text.endswith(('.', '!', '?')):
                    text += "."

                # Synthesize with the appropriate provider
                try:
                    if active_provider == "gemini" and self.gemini_available:
                        audio_data = await gemini_tts_service.synthesize_text(
                            text, voice_name or gemini_tts_service.default_voice,
                            simple_lang, model=model, speed=speed, style_prompt=style_prompt
                        )
                    elif self.google_client:
                        audio_data = await self._synthesize_text_google(text, language_code, voice_name)
                    elif self.elevenlabs_available:
                        voice_id = self._get_elevenlabs_voice(language_code, voice_name)
                        audio_data = await self._synthesize_text_elevenlabs(
                            text, voice_id,
                            stability=stability, similarity_boost=similarity_boost,
                        )
                    else:
                        raise ValueError("No TTS service available")

                    # Get actual duration from audio
                    audio_segment = AudioSegment.from_file(io.BytesIO(audio_data), format="mp3")
                    actual_duration = len(audio_segment) / 1000.0

                    # Store segment info
                    segments.append(TTSCueSegment(
                        cue_index=i,
                        start_time=cue["start_time"],
                        end_time=cue["end_time"],
                        duration=actual_duration,
                        text=cue["text"],
                        audio_bytes=audio_data
                    ))

                    # Add to combined audio
                    audio_segments_for_combine.append(audio_segment)
                    current_audio_position += actual_duration

                except Exception as e:
                    logger.warning(f"Failed to synthesize cue {i}: {e}")
                    # Add silence for failed cue
                    cue_duration = cue["end_time"] - cue["start_time"]
                    silence = AudioSegment.silent(duration=int(cue_duration * 1000))
                    audio_segments_for_combine.append(silence)
                    current_audio_position += cue_duration

        # Combine all segments
        if audio_segments_for_combine:
            final_audio = sum(audio_segments_for_combine, AudioSegment.empty())
        else:
            final_audio = AudioSegment.silent(duration=1000)

        # Export combined to MP3
        output_buffer = io.BytesIO()
        final_audio.export(output_buffer, format="mp3", bitrate="128k")

        logger.info(f"Synthesized {len(segments)} AD cue segments")
        return output_buffer.getvalue(), segments

    async def _synthesize_with_google(
        self,
        ad_vtt_content: str,
        language_code: str = "en-US",
        voice_name: Optional[str] = None
    ) -> bytes:
        """Generate MP3 using Google TTS with 2-second pauses between passages"""

        # Parse VTT cues
        cues = self._parse_ad_cues(ad_vtt_content)

        if not cues:
            raise ValueError("No audio description cues found")

        # Synthesize each cue separately with precise timing anchoring
        audio_segments = []
        current_audio_position = 0.0  # Track actual audio timeline position

        for i, cue in enumerate(cues):
            # Calculate where this cue should start (anchored to VTT timing)
            target_start_time = cue["start_time"]

            # Add silence to reach the exact VTT start time
            if target_start_time > current_audio_position:
                silence_duration = target_start_time - current_audio_position
                silence = AudioSegment.silent(duration=int(silence_duration * 1000))
                audio_segments.append(silence)
                current_audio_position = target_start_time

            # Synthesize this cue's text
            text = cue["text"].strip()
            if text:
                # Ensure proper punctuation for natural TTS flow
                if not text.endswith(('.', '!', '?')):
                    text += "."

                # Synthesize this individual cue
                audio_data = await self._synthesize_text_google(
                    text, language_code, voice_name
                )

                # Convert to AudioSegment and get actual duration
                audio_segment = AudioSegment.from_file(io.BytesIO(audio_data), format="mp3")
                audio_segments.append(audio_segment)

                # Update current position based on actual audio duration (not VTT end time)
                actual_audio_duration = len(audio_segment) / 1000.0  # Convert ms to seconds
                current_audio_position += actual_audio_duration

        # Combine all segments
        if audio_segments:
            final_audio = sum(audio_segments, AudioSegment.empty())
        else:
            # Fallback to empty audio if no segments
            final_audio = AudioSegment.silent(duration=1000)

        # Export to MP3
        output_buffer = io.BytesIO()
        final_audio.export(output_buffer, format="mp3", bitrate="128k")

        return output_buffer.getvalue()

    async def _synthesize_with_elevenlabs(
        self,
        ad_vtt_content: str,
        language_code: str = "en-US",
        voice_name: Optional[str] = None,
        stability: float = 0.5,
        similarity_boost: float = 0.5,
    ) -> bytes:
        """Generate MP3 using ElevenLabs TTS"""
        # Parse VTT cues
        cues = self._parse_ad_cues(ad_vtt_content)

        if not cues:
            raise ValueError("No audio description cues found")

        # Get voice ID for language
        voice_id = self._get_elevenlabs_voice(language_code, voice_name)

        # Synthesize each cue with precise timing anchoring
        audio_segments = []
        current_audio_position = 0.0  # Track actual audio timeline position

        for i, cue in enumerate(cues):
            # Calculate where this cue should start (anchored to VTT timing)
            target_start_time = cue["start_time"]

            # Add silence to reach the exact VTT start time
            if target_start_time > current_audio_position:
                silence_duration = target_start_time - current_audio_position
                silence = AudioSegment.silent(duration=int(silence_duration * 1000))
                audio_segments.append(silence)
                current_audio_position = target_start_time

            # Synthesize this cue with ElevenLabs
            text = cue["text"].strip()
            if text:
                audio_data = await self._synthesize_text_elevenlabs(
                    text, voice_id,
                    stability=stability, similarity_boost=similarity_boost,
                )

                # Convert to AudioSegment and get actual duration
                audio_segment = AudioSegment.from_file(io.BytesIO(audio_data), format="mp3")
                audio_segments.append(audio_segment)

                # Update current position based on actual audio duration (not VTT end time)
                actual_audio_duration = len(audio_segment) / 1000.0  # Convert ms to seconds
                current_audio_position += actual_audio_duration

        # Combine all segments
        final_audio = sum(audio_segments, AudioSegment.empty())

        # Export to MP3
        output_buffer = io.BytesIO()
        final_audio.export(output_buffer, format="mp3", bitrate="128k")

        return output_buffer.getvalue()

    async def _synthesize_text_google(
        self,
        text: str,
        language_code: str,
        voice_name: Optional[str] = None
    ) -> bytes:
        """Synthesize a single text string to audio using Google TTS"""
        # Configure voice
        if not voice_name:
            voice_name = settings.google_tts_voices.get(language_code, "en-US-Neural2-D")

        voice = texttospeech.VoiceSelectionParams(
            language_code=language_code,
            name=voice_name
        )

        # Configure audio
        audio_config = texttospeech.AudioConfig(
            audio_encoding=texttospeech.AudioEncoding.MP3,
            speaking_rate=1.2,  # Faster cadence for better flow
            pitch=0.0
        )

        # Synthesize
        synthesis_input = texttospeech.SynthesisInput(text=text)

        response = self.google_client.synthesize_speech(
            input=synthesis_input,
            voice=voice,
            audio_config=audio_config
        )

        return response.audio_content

    async def _synthesize_text_elevenlabs(
        self,
        text: str,
        voice_id: str,
        stability: float = 0.5,
        similarity_boost: float = 0.5,
    ) -> bytes:
        """Synthesize text using ElevenLabs API"""
        url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"

        headers = {
            "Accept": "audio/mpeg",
            "Content-Type": "application/json",
            "xi-api-key": settings.elevenlabs_api_key
        }

        data = {
            "text": text,
            "model_id": "eleven_multilingual_v2",
            "voice_settings": {
                "stability": stability,
                "similarity_boost": similarity_boost,
                "style": 0.0,
                "use_speaker_boost": True
            }
        }

        async with aiohttp.ClientSession() as session:
            async with session.post(url, json=data, headers=headers) as response:
                if response.status == 200:
                    return await response.read()
                else:
                    error_text = await response.text()
                    raise ValueError(f"ElevenLabs TTS failed: {response.status} - {error_text}")

    def _get_elevenlabs_voice(self, language_code: str, voice_name: Optional[str] = None) -> str:
        """Get ElevenLabs voice ID for language"""
        if voice_name:
            return voice_name

        return settings.elevenlabs_voices.get(language_code, "21m00Tcm4TlvDq8ikWAM")

    def _parse_ad_cues(self, vtt_content: str) -> list[dict]:
        """Parse audio description VTT and extract timing + text"""
        lines = vtt_content.strip().split('\n')
        cues = []

        i = 0
        while i < len(lines):
            line = lines[i].strip()

            # Skip header and empty lines
            if line == "WEBVTT" or line == "" or line.startswith("NOTE"):
                i += 1
                continue

            # Check for timing line
            if " --> " in line:
                timing_parts = line.split(" --> ")
                start_time = self._parse_timestamp(timing_parts[0].strip())
                end_time = self._parse_timestamp(timing_parts[1].strip())

                # Get text from next line(s)
                i += 1
                text_lines = []
                while i < len(lines) and lines[i].strip() != "":
                    text_lines.append(lines[i].strip())
                    i += 1

                if text_lines:
                    cues.append({
                        "start_time": start_time,
                        "end_time": end_time,
                        "text": " ".join(text_lines)
                    })
            else:
                i += 1

        return cues

    def _parse_timestamp(self, timestamp: str) -> float:
        """Convert VTT timestamp to seconds"""
        # Format: HH:MM:SS.mmm or MM:SS.mmm
        parts = timestamp.split(":")

        if len(parts) == 3:  # HH:MM:SS.mmm
            hours, minutes, seconds = parts
        elif len(parts) == 2:  # MM:SS.mmm
            hours, minutes, seconds = "0", parts[0], parts[1]
        else:
            raise ValueError(f"Invalid timestamp format: {timestamp}")

        # Parse seconds and milliseconds
        sec_parts = seconds.split(".")
        seconds = int(sec_parts[0])
        milliseconds = int(sec_parts[1]) if len(sec_parts) > 1 else 0

        total_seconds = (
            int(hours) * 3600 +
            int(minutes) * 60 +
            seconds +
            milliseconds / 1000.0
        )

        return total_seconds


# Global service instance
tts_service = TTSService()