import argparse
import shutil
from pathlib import Path

from opencc import OpenCC

from translator import (
    DEFAULT_MODEL_CACHE,
    SUPPORTED_AI_LANGS,
    TranslatorConfig,
    build_translator,
)

SOURCE_DIR = Path("./Subtitle_Trans_CN")
BASE_OPENCC_TARGETS = [
    ("通用繁體", Path("./Subtitle_ZH_Hant"), OpenCC("s2t")),
]
TW_HK_TARGETS = [
    ("台灣繁體", Path("./Subtitle_ZH_Hant_TW"), OpenCC("s2tw")),
    ("香港繁體", Path("./Subtitle_ZH_Hant_HK"), OpenCC("s2hk")),
]
AI_LANG_DIRS = {
    "en": Path("./Subtitle_EN"),
    "jp": Path("./Subtitle_JP"),
    "korean": Path("./Subtitle_KOREAN"),
}
AI_LANGS = ["en", "jp", "korean"]


def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser(description="批量翻译 SRT 字幕为多种语言。")
    parser.add_argument("--backend", choices=["local", "openai"], default="local")
    parser.add_argument("--openai-model", default="gpt-4o-mini")
    parser.add_argument("--openai-api-key", default=None)
    parser.add_argument(
        "--model-cache-dir",
        default=str(DEFAULT_MODEL_CACHE),
        help="NLLB 本地模型存储目录。",
    )
    parser.add_argument("--batch-size", type=int, default=4)
    parser.add_argument("--max-length", type=int, default=512)
    parser.add_argument(
        "--include-tw-hk",
        action="store_true",
        help="额外生成台繁与港繁字幕。",
    )
    parser.add_argument(
        "--show-lang",
        action="store_true",
        help="打印正在翻译的语言。",
    )
    return parser.parse_args()


def ensure_source_dir(source_dir: Path) -> list[Path]:
    if not source_dir.is_dir():
        print(f"❌ 目录 {source_dir} 不存在，请检查路径。")
        raise SystemExit(1)

    files = sorted(source_dir.glob("*.srt"))
    if not files:
        print(f"❌ 目录 {source_dir} 中没有找到任何 .srt 文件。")
        raise SystemExit(1)
    return files


def prepare_target_dir(path: Path) -> None:
    if path.exists():
        for child in path.iterdir():
            if child.is_file() or child.is_symlink():
                child.unlink()
            else:
                shutil.rmtree(child)
    else:
        path.mkdir(parents=True, exist_ok=True)


def is_dialog_line(line: str) -> bool:
    stripped = line.strip()
    if not stripped:
        return False
    if stripped.isdigit():
        return False
    if "-->" in stripped:
        return False
    return True


def split_line(line: str) -> tuple[str, str]:
    if line.endswith("\r\n"):
        return line[:-2], "\r\n"
    if line.endswith("\n"):
        return line[:-1], "\n"
    if line.endswith("\r"):
        return line[:-1], "\r"
    return line, ""


def translate_dialogs(content: str, translator, target_lang: str) -> str:
    lines = content.splitlines(keepends=True)
    indices: list[int] = []
    texts: list[str] = []
    endings: list[str] = []

    for idx, line in enumerate(lines):
        if is_dialog_line(line):
            text, ending = split_line(line)
            indices.append(idx)
            texts.append(text)
            endings.append(ending)

    if not texts:
        return content

    translated = translator.translate(texts, target_lang=target_lang)
    for pos, new_text in enumerate(translated):
        idx = indices[pos]
        lines[idx] = new_text + endings[pos]
    return "".join(lines)


def main() -> None:
    args = parse_args()
    files = ensure_source_dir(SOURCE_DIR)

    opencc_targets = list(BASE_OPENCC_TARGETS)
    if args.include_tw_hk:
        opencc_targets.extend(TW_HK_TARGETS)

    for _, target_dir, _ in opencc_targets:
        prepare_target_dir(target_dir)

    ai_targets = AI_LANG_DIRS
    for lang, path in ai_targets.items():
        if lang not in SUPPORTED_AI_LANGS:
            raise SystemExit(f"❌ 不支持的 AI 语言: {lang}")
        prepare_target_dir(path)

    translator = build_translator(
        TranslatorConfig(
            backend=args.backend,
            openai_model=args.openai_model,
            openai_api_key=args.openai_api_key,
            model_cache_dir=Path(args.model_cache_dir),
            batch_size=args.batch_size,
            max_length=args.max_length,
        )
    )

    total = len(files)
    print(f"🔄 开始转换 {total} 个 .srt 文件...")

    for idx, file_path in enumerate(files, 1):
        percent = idx * 100 // total
        print(f"🔄 转换中: {idx}/{total} ({percent}%) - {file_path}")
        try:
            content = file_path.read_text(encoding="utf-8")
        except UnicodeDecodeError as exc:
            print(f"❌ 转换失败: {file_path} (无法以 UTF-8 读取: {exc})")
            continue

        # 繁体系
        for label, target_dir, converter in opencc_targets:
            if args.show_lang:
                print(f"   ↳ 正在生成 {label}")
            out_path = target_dir / file_path.name
            converted = converter.convert(content)
            out_path.write_text(converted, encoding="utf-8")

        # 英日韩
        for lang, target_dir in ai_targets.items():
            if args.show_lang:
                lang_label = SUPPORTED_AI_LANGS[lang]["label"]
                print(f"   ↳ 正在翻译 {lang_label}")
            translated_content = translate_dialogs(content, translator, lang)
            out_path = target_dir / file_path.name
            out_path.write_text(translated_content, encoding="utf-8")

        print(f"✅ 转换成功: {file_path}")


if __name__ == "__main__":
    main()