import json
import re
import torch
import torchaudio
import edge_tts
from pathlib import Path
from rich.console import Console
from rich.progress import (
    Progress,
    SpinnerColumn,
    TextColumn,
    BarColumn,
    TaskProgressColumn,
)
from dubbing.steps.base import PipelineStep
from dubbing.models import TranslatedSegment, Language
from dubbing.config import TTSConfig

console = Console()


class TTSStep(PipelineStep):
    name = "TTS"

    def __init__(self, paths, language: Language = Language.RU):
        super().__init__(paths)
        self.language = language
        self._silero_model = None

    def is_cached(self) -> bool:
        if not self.paths.tts_dir.exists():
            return False
        return any(self.paths.tts_dir.glob("*.wav"))

    def clean(self) -> None:
        if self.paths.tts_dir.exists():
            for f in self.paths.tts_dir.glob("*.wav"):
                f.unlink()

    def _load_translated(self) -> list[TranslatedSegment]:
        with open(self.paths.translated_json, "r", encoding="utf-8") as f:
            data = json.load(f)
        return [TranslatedSegment(**s) for s in data]

    def _clean_text_russian(self, text: str) -> str | None:
        """Clean text for Russian TTS (Silero)."""
        text = re.sub(r"[^\w\s.,!?;:\-—–\'\"«»а-яА-ЯёЁ]", "", text)
        text = re.sub(r"\s+", " ", text).strip()
        if not text or not re.search(r"[а-яА-ЯёЁ]", text):
            return None
        return text

    def _clean_text_english(self, text: str) -> str | None:
        """Clean text for English TTS (Piper)."""
        text = re.sub(r"[^\w\s.,!?;:\-—–\'\"a-zA-Z0-9]", "", text)
        text = re.sub(r"\s+", " ", text).strip()
        if not text or not re.search(r"[a-zA-Z]", text):
            return None
        return text

    def _clean_text(self, text: str) -> str | None:
        """Clean text based on language."""
        if self.language == Language.EN:
            return self._clean_text_english(text)
        # RU and EN_RU both output Russian
        return self._clean_text_russian(text)

    def _load_silero_model(self):
        """Load Silero TTS model for Russian."""
        if self._silero_model is None:
            console.print("[dim]Loading Silero TTS model...[/]")
            device = torch.device("cpu")
            self._silero_model, _ = torch.hub.load(
                repo_or_dir="snakers4/silero-models",
                model="silero_tts",
                language="ru",
                speaker="v4_ru",
            )
            self._silero_model.to(device)
        return self._silero_model

    def _synthesize_russian(self, text: str, output_path: Path) -> bool:
        """Synthesize Russian speech using Silero."""
        model = self._load_silero_model()
        try:
            audio = model.apply_tts(
                text=text,
                speaker=TTSConfig.RU_VOICE,
                sample_rate=TTSConfig.RU_SAMPLE_RATE,
            )
            torchaudio.save(
                str(output_path), audio.unsqueeze(0), TTSConfig.RU_SAMPLE_RATE
            )
            return True
        except ValueError:
            return False

    async def _synthesize_english(self, text: str, output_path: Path) -> bool:
        """Synthesize English speech using Edge TTS."""
        try:
            mp3_path = output_path.with_suffix(".mp3")
            communicate = edge_tts.Communicate(text, TTSConfig.EN_VOICE)
            await communicate.save(str(mp3_path))

            # Convert MP3 to WAV using pydub
            from pydub import AudioSegment

            audio = AudioSegment.from_mp3(str(mp3_path))
            audio.export(str(output_path), format="wav")
            mp3_path.unlink()
            return True
        except Exception as e:
            console.print(f"[red]Edge TTS error: {e}[/]")
            return False

    async def _synthesize(self, text: str, output_path: Path) -> bool:
        """Synthesize speech based on language."""
        if self.language == Language.EN:
            return await self._synthesize_english(text, output_path)
        # RU and EN_RU both use Russian TTS
        return self._synthesize_russian(text, output_path)

    async def run(self) -> None:
        engine = (
            TTSConfig.EN_ENGINE if self.language == Language.EN else TTSConfig.RU_ENGINE
        )  # EN_RU uses RU engine
        console.print(f"[cyan]Generating TTS audio ({engine})...[/]")

        self.paths.tts_dir.mkdir(parents=True, exist_ok=True)

        segments = self._load_translated()

        skipped = []
        with Progress(
            SpinnerColumn(),
            TextColumn("[progress.description]{task.description}"),
            BarColumn(),
            TaskProgressColumn(),
            console=console,
        ) as progress:
            task = progress.add_task("Generating speech...", total=len(segments))

            for i, seg in enumerate(segments):
                clean_text = self._clean_text(seg.translated)
                if not clean_text:
                    skipped.append((i, seg.translated, "no_text"))
                    progress.advance(task)
                    continue

                path = self.paths.tts_dir / f"seg_{i:04d}.wav"
                success = await self._synthesize(clean_text, path)
                if not success:
                    skipped.append((i, seg.translated, "tts_error"))

                progress.advance(task)

        generated = len(segments) - len(skipped)
        console.print(f"[green]✓ Generated {generated} audio files[/]")
        if skipped:
            console.print(f"[yellow]Skipped {len(skipped)} segments:[/]")
            for idx, text, reason in skipped:
                console.print(f"  [dim]{idx}:[/] {text[:60]}... [red]({reason})[/]")