"""
STT Celery Tasks
- faster-whisper 변환
- Ollama / OpenRouter 후처리 (교정 또는 번역)
- SRT / VTT / TXT 자막 파일 생성
"""
import os, json
import httpx
from celery import Celery
from ocr_tasks import ocr_task  # noqa: F401

REDIS_URL      = os.getenv("REDIS_URL", "redis://redis:6379/0")
MODEL_SIZE     = os.getenv("WHISPER_MODEL", "medium")
DEVICE         = os.getenv("WHISPER_DEVICE", "cpu")
COMPUTE_TYPE   = os.getenv("WHISPER_COMPUTE_TYPE", "int8")
LANGUAGE       = os.getenv("WHISPER_LANGUAGE", "ko") or None
BEAM_SIZE      = int(os.getenv("WHISPER_BEAM_SIZE", "5"))
INITIAL_PROMPT = os.getenv("WHISPER_INITIAL_PROMPT", "") or None
OUTPUT_DIR     = os.getenv("OUTPUT_DIR", "/data/outputs")
OLLAMA_URL     = os.getenv("OLLAMA_URL", "http://192.168.0.126:11434")
OLLAMA_TIMEOUT = int(os.getenv("OLLAMA_TIMEOUT", "600"))

_cpu_threads_env = int(os.getenv("CPU_THREADS", "0"))
CPU_THREADS = _cpu_threads_env if _cpu_threads_env > 0 else None

celery_app = Celery("whisper_tasks", broker=REDIS_URL, backend=REDIS_URL)
celery_app.conf.update(
    task_serializer="json", result_serializer="json",
    accept_content=["json"], task_track_started=True, result_expires=3600,
)

_model = None

def get_model():
    global _model
    if _model is None:
        from faster_whisper import WhisperModel
        kwargs = dict(device=DEVICE, compute_type=COMPUTE_TYPE)
        if CPU_THREADS is not None: kwargs["cpu_threads"] = CPU_THREADS
        print(f"[Whisper] 로딩: {MODEL_SIZE}/{DEVICE}/{COMPUTE_TYPE}/threads={CPU_THREADS or 'auto'}")
        _model = WhisperModel(MODEL_SIZE, **kwargs)
        print("[Whisper] 로드 완료")
    return _model


# ══════════════════════════════════════════════════════════════
#  언어 코드 매핑
# ══════════════════════════════════════════════════════════════
LANG_NAMES = {
    "ko":"한국어","en":"English","ja":"日本語","zh":"中文","fr":"Français",
    "de":"Deutsch","es":"Español","it":"Italiano","pt":"Português","ru":"Русский",
    "ar":"العربية","vi":"Tiếng Việt","th":"ไทย","id":"Bahasa Indonesia",
    "nl":"Nederlands","pl":"Polski","tr":"Türkçe","sv":"Svenska","uk":"Українська",
}

def _lang_name(code: str) -> str:
    return LANG_NAMES.get(code, code)


# ══════════════════════════════════════════════════════════════
#  자막 포맷 생성
# ══════════════════════════════════════════════════════════════
def _fmt_srt_time(s: float) -> str:
    """초 → SRT 시간 포맷 00:00:00,000"""
    ms = int(round(s * 1000))
    h, rem = divmod(ms, 3600000)
    m, rem = divmod(rem, 60000)
    sec, ms = divmod(rem, 1000)
    return f"{h:02d}:{m:02d}:{sec:02d},{ms:03d}"

def _fmt_vtt_time(s: float) -> str:
    """초 → VTT 시간 포맷 00:00:00.000"""
    return _fmt_srt_time(s).replace(",", ".")

def _make_srt(segments: list) -> str:
    lines = []
    for i, seg in enumerate(segments, 1):
        lines.append(str(i))
        lines.append(f"{_fmt_srt_time(seg['start'])} --> {_fmt_srt_time(seg['end'])}")
        lines.append(seg["text"].strip())
        lines.append("")
    return "\n".join(lines)

def _make_vtt(segments: list) -> str:
    lines = ["WEBVTT", ""]
    for i, seg in enumerate(segments, 1):
        lines.append(f"{i}")
        lines.append(f"{_fmt_vtt_time(seg['start'])} --> {_fmt_vtt_time(seg['end'])}")
        lines.append(seg["text"].strip())
        lines.append("")
    return "\n".join(lines)


# ══════════════════════════════════════════════════════════════
#  번역 (Ollama / OpenRouter)
# ══════════════════════════════════════════════════════════════
def _translate_segments(segments: list, target_lang: str,
                         use_openrouter: bool, model: str,
                         openrouter_url: str, openrouter_key: str,
                         task_self=None) -> list:
    """세그먼트 텍스트를 target_lang으로 번역해서 새 세그먼트 리스트 반환"""
    if not model or not target_lang:
        return segments

    lang_name = _lang_name(target_lang)
    translated = []

    # 세그먼트를 청크로 묶어서 번역 (API 호출 최소화)
    # 최대 20개씩 묶음
    CHUNK = 20
    chunks = [segments[i:i+CHUNK] for i in range(0, len(segments), CHUNK)]

    for ci, chunk in enumerate(chunks):
        if task_self:
            pct = 85 + int((ci / len(chunks)) * 10)
            task_self.update_state(state="PROGRESS",
                meta={"progress": pct,
                      "message": f"번역 중... ({ci*CHUNK+1}/{len(segments)})"})

        # JSON 배열로 텍스트만 전달
        texts = [seg["text"].strip() for seg in chunk]
        prompt = (
            f"다음 문장들을 {lang_name}로 번역해줘.\n"
            f"JSON 배열 형식으로만 답해줘. 설명 없이 번역된 문장 배열만 출력해.\n"
            f"입력 배열과 동일한 개수, 동일한 순서로 출력해.\n\n"
            f"입력: {json.dumps(texts, ensure_ascii=False)}"
        )

        try:
            if use_openrouter and openrouter_key:
                resp = httpx.post(
                    f"{openrouter_url.rstrip('/')}/chat/completions",
                    headers={"Authorization": f"Bearer {openrouter_key}",
                             "HTTP-Referer": "https://voicescript.local",
                             "Content-Type": "application/json"},
                    json={"model": model,
                          "messages": [{"role":"user","content":prompt}],
                          "temperature": 0.2},
                    timeout=float(OLLAMA_TIMEOUT),
                )
                resp.raise_for_status()
                raw = resp.json()["choices"][0]["message"]["content"].strip()
            else:
                resp = httpx.post(f"{OLLAMA_URL}/api/chat",
                    json={"model": model,
                          "messages": [{"role":"user","content":prompt}],
                          "stream": False, "options": {"temperature": 0.2}},
                    timeout=float(OLLAMA_TIMEOUT))
                resp.raise_for_status()
                raw = resp.json().get("message",{}).get("content","").strip()

            # JSON 파싱
            # 코드블록 제거
            if "```" in raw:
                raw = raw.split("```")[1].lstrip("json").strip()
            trans_texts = json.loads(raw)
            if not isinstance(trans_texts, list):
                trans_texts = texts  # 파싱 실패 시 원본 유지

        except Exception as e:
            print(f"[번역 실패 chunk {ci}] {e}")
            trans_texts = texts  # 실패 시 원본 유지

        # 번역된 텍스트를 세그먼트에 결합
        for seg, t_text in zip(chunk, trans_texts):
            translated.append({**seg, "text": t_text})
        # 남은 세그먼트 (번역 누락)
        if len(trans_texts) < len(chunk):
            for seg in chunk[len(trans_texts):]:
                translated.append(seg)

    return translated


# ══════════════════════════════════════════════════════════════
#  Ollama 텍스트 후처리 (교정)
# ══════════════════════════════════════════════════════════════
def _ollama_postprocess(text: str, model: str) -> str:
    if not model or not text.strip(): return text
    prompt = (
        "다음은 음성 인식으로 추출된 텍스트입니다. "
        "내용은 절대 변경하지 말고, 문장 부호를 추가하고 자연스럽게 다듬어줘. "
        "결과 텍스트만 출력하고 설명은 하지 마.\n\n" + text
    )
    try:
        resp = httpx.post(f"{OLLAMA_URL}/api/chat",
            json={"model":model,"messages":[{"role":"user","content":prompt}],
                  "stream":False,"options":{"temperature":0.1}},
            timeout=float(OLLAMA_TIMEOUT))
        resp.raise_for_status()
        result = resp.json().get("message",{}).get("content","").strip()
        return result if result else text
    except Exception as e:
        print(f"[Ollama 후처리 실패] {e}"); return text

def _openrouter_postprocess(text: str, model: str, base_url: str, api_key: str) -> str:
    if not model or not api_key or not text.strip(): return text
    prompt = (
        "다음은 음성 인식으로 추출된 텍스트입니다. "
        "내용은 절대 변경하지 말고, 문장 부호를 추가하고 자연스럽게 다듬어줘. "
        "결과 텍스트만 출력하고 설명은 하지 마.\n\n" + text
    )
    try:
        resp = httpx.post(f"{base_url.rstrip('/')}/chat/completions",
            headers={"Authorization":f"Bearer {api_key}","HTTP-Referer":"https://voicescript.local","Content-Type":"application/json"},
            json={"model":model,"messages":[{"role":"user","content":prompt}],"temperature":0.1},
            timeout=float(OLLAMA_TIMEOUT))
        resp.raise_for_status()
        result = resp.json()["choices"][0]["message"]["content"].strip()
        return result if result else text
    except Exception as e:
        print(f"[OpenRouter 후처리 실패] {e}"); return text


# ══════════════════════════════════════════════════════════════
#  메인 STT Task
# ══════════════════════════════════════════════════════════════
@celery_app.task(bind=True, name="tasks.transcribe_task", queue="stt")
def transcribe_task(
    self,
    file_id:           str,
    audio_path:        str,
    # 후처리
    use_ollama:        bool = False,
    ollama_model:      str  = "",
    use_openrouter:    bool = False,
    openrouter_model:  str  = "",
    openrouter_url:    str  = "",
    openrouter_key:    str  = "",
    # 자막
    subtitle_mode:     bool = False,   # True → 자막 파일 생성
    subtitle_format:   str  = "srt",   # srt | vtt | both
    translate_to:      str  = "",      # 번역 대상 언어 코드 (없으면 원어 자막)
    translate_model:   str  = "",      # 번역에 쓸 모델
    translate_via:     str  = "ollama",# ollama | openrouter
    # 원본 언어 강제 지정 (없으면 auto)
    force_language:    str  = "",
):
    self.update_state(state="PROGRESS", meta={"progress":5,"message":"모델 준비 중..."})
    try:
        model = get_model()
        self.update_state(state="PROGRESS", meta={"progress":15,"message":"오디오 분석 중..."})

        lang = force_language.strip() or LANGUAGE
        segments_gen, info = model.transcribe(
            audio_path,
            language=lang,
            beam_size=BEAM_SIZE,
            initial_prompt=INITIAL_PROMPT,
            vad_filter=True,
            vad_parameters=dict(min_silence_duration_ms=500),
            word_timestamps=False,
        )

        self.update_state(state="PROGRESS", meta={"progress":30,"message":"텍스트 변환 중..."})
        segments, parts = [], []
        duration = info.duration

        for seg in segments_gen:
            segments.append({"start":round(seg.start,3),"end":round(seg.end,3),"text":seg.text.strip()})
            parts.append(seg.text.strip())
            if duration > 0:
                pct = 30 + int((seg.end/duration)*45)
                self.update_state(state="PROGRESS",
                    meta={"progress":min(pct,75),
                          "message":f"변환 중... {seg.end:.0f}s / {duration:.0f}s"})

        raw_text  = "\n".join(parts)
        full_text = raw_text
        detected_lang = info.language

        # ── 텍스트 후처리 (교정) ──────────────────────────────
        if use_ollama and ollama_model and not subtitle_mode:
            self.update_state(state="PROGRESS",
                meta={"progress":80,"message":f"Ollama({ollama_model}) 교정 중..."})
            full_text = _ollama_postprocess(raw_text, ollama_model)

        elif use_openrouter and openrouter_model and openrouter_key and not subtitle_mode:
            self.update_state(state="PROGRESS",
                meta={"progress":80,"message":f"OpenRouter({openrouter_model}) 교정 중..."})
            full_text = _openrouter_postprocess(raw_text, openrouter_model, openrouter_url, openrouter_key)

        # ── 자막 모드: 번역 ──────────────────────────────────
        translated_segments = segments
        is_translated = False

        if subtitle_mode and translate_to and translate_to != detected_lang:
            t_model = translate_model or (ollama_model if translate_via=="ollama" else openrouter_model)
            t_via_or = (translate_via == "openrouter" and bool(openrouter_key))
            self.update_state(state="PROGRESS",
                meta={"progress":82,
                      "message":f"{_lang_name(translate_to)}로 번역 중..."})
            translated_segments = _translate_segments(
                segments, translate_to,
                use_openrouter=t_via_or,
                model=t_model,
                openrouter_url=openrouter_url,
                openrouter_key=openrouter_key,
                task_self=self,
            )
            is_translated = True
            # 번역된 전체 텍스트
            full_text = "\n".join(s["text"] for s in translated_segments)

        self.update_state(state="PROGRESS", meta={"progress":93,"message":"파일 저장 중..."})
        os.makedirs(OUTPUT_DIR, exist_ok=True)

        result_files = {}

        # ── TXT 저장 ─────────────────────────────────────────
        txt_filename = f"{file_id}.txt"
        with open(os.path.join(OUTPUT_DIR, txt_filename), "w", encoding="utf-8") as f:
            f.write(f"# 변환 결과\n")
            f.write(f"# 언어: {detected_lang}  |  재생 시간: {duration:.1f}초\n")
            if is_translated:
                f.write(f"# 번역: {_lang_name(translate_to)}\n")
            f.write(f"\n## 전체 텍스트\n\n{full_text}\n\n")
            f.write(f"## 타임스탬프별 세그먼트\n\n")
            for seg in (translated_segments if is_translated else segments):
                f.write(f"[{_fmt_ts(seg['start'])} → {_fmt_ts(seg['end'])}]  {seg['text']}\n")
        result_files["txt"] = txt_filename

        # ── 자막 파일 저장 ────────────────────────────────────
        if subtitle_mode:
            sub_segs = translated_segments if is_translated else segments
            lang_suffix = f".{translate_to}" if is_translated else f".{detected_lang}"

            if subtitle_format in ("srt", "both"):
                srt_fn = f"{file_id}{lang_suffix}.srt"
                with open(os.path.join(OUTPUT_DIR, srt_fn), "w", encoding="utf-8") as f:
                    f.write(_make_srt(sub_segs))
                result_files["srt"] = srt_fn

            if subtitle_format in ("vtt", "both"):
                vtt_fn = f"{file_id}{lang_suffix}.vtt"
                with open(os.path.join(OUTPUT_DIR, vtt_fn), "w", encoding="utf-8") as f:
                    f.write(_make_vtt(sub_segs))
                result_files["vtt"] = vtt_fn

            # 원본 언어 SRT도 함께 (번역 시)
            if is_translated and subtitle_format in ("srt","both"):
                orig_fn = f"{file_id}.{detected_lang}.srt"
                with open(os.path.join(OUTPUT_DIR, orig_fn), "w", encoding="utf-8") as f:
                    f.write(_make_srt(segments))
                result_files["srt_original"] = orig_fn

        try: os.remove(audio_path)
        except: pass

        return {
            # 기본 STT 결과
            "text":              full_text,
            "raw_text":          raw_text,
            "segments":          translated_segments if is_translated else segments,
            "orig_segments":     segments,
            "language":          detected_lang,
            "duration":          round(duration, 1),
            # 후처리
            "ollama_used":       use_ollama and bool(ollama_model) and not subtitle_mode,
            "ollama_model":      ollama_model if (use_ollama and not subtitle_mode) else "",
            "openrouter_used":   use_openrouter and bool(openrouter_model) and not subtitle_mode,
            "openrouter_model":  openrouter_model if (use_openrouter and not subtitle_mode) else "",
            # 자막
            "subtitle_mode":     subtitle_mode,
            "subtitle_format":   subtitle_format,
            "translated":        is_translated,
            "translate_to":      translate_to if is_translated else "",
            "translate_model":   translate_model if is_translated else "",
            # 파일
            "output_file":       result_files.get("txt",""),
            "srt_file":          result_files.get("srt",""),
            "vtt_file":          result_files.get("vtt",""),
            "srt_original_file": result_files.get("srt_original",""),
        }

    except Exception as e:
        raise Exception(f"변환 실패: {str(e)}")


def _fmt_ts(s: float) -> str:
    m, sec = divmod(int(s), 60)
    return f"{m:02d}:{sec:02d}"