"""
OCR Celery Tasks — PaddleOCR 3.x + Ollama Vision
"""
import os
import base64

import httpx
from celery import Celery
import openpyxl
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side

REDIS_URL      = os.getenv("REDIS_URL", "redis://redis:6379/0")
OUTPUT_DIR     = os.getenv("OUTPUT_DIR", "/data/outputs")
OCR_LANG       = os.getenv("OCR_LANG", "korean")
OLLAMA_URL     = os.getenv("OLLAMA_URL", "http://192.168.0.126:11434")
OLLAMA_TIMEOUT = int(os.getenv("OLLAMA_TIMEOUT", "600"))

celery_app = Celery("ocr_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,
)

_ocr_engine    = None
_struct_engine = None

def get_ocr():
    global _ocr_engine
    if _ocr_engine is None:
        from paddleocr import PaddleOCR
        print(f"[PaddleOCR] 로딩 (lang={OCR_LANG})")
        _ocr_engine = PaddleOCR(use_angle_cls=True, lang=OCR_LANG)
        print("[PaddleOCR] 완료")
    return _ocr_engine

def get_structure():
    global _struct_engine
    if _struct_engine is None:
        from paddleocr import PPStructure
        print("[PPStructure] 로딩")
        _struct_engine = PPStructure(table=True, ocr=True, lang=OCR_LANG)
        print("[PPStructure] 완료")
    return _struct_engine


@celery_app.task(bind=True, name="tasks.ocr_task", queue="ocr")
def ocr_task(self, file_id, image_path, mode="text",
             backend="paddle", ollama_model="granite3.2-vision", custom_prompt=""):
    self.update_state(state="PROGRESS", meta={"progress": 8, "message": "엔진 준비 중..."})
    try:
        if backend == "ollama":
            result = _run_ollama(self, file_id, image_path, mode, ollama_model, custom_prompt)
        else:
            result = _run_paddle(self, file_id, image_path, mode)
        try: os.remove(image_path)
        except: pass
        return result
    except Exception as e:
        try: os.remove(image_path)
        except: pass
        raise Exception(f"OCR 실패: {str(e)}")


_OLLAMA_PROMPTS = {
    "text":      "이 이미지에서 모든 텍스트를 정확하게 추출해줘. 원본의 줄 구분과 단락 구조를 유지해줘.",
    "structure": "이 이미지를 분석해서 표는 마크다운 표 형식으로, 나머지 텍스트는 원본 구조를 유지하며 추출해줘.",
}

def _run_ollama(task, file_id, image_path, mode, ollama_model, custom_prompt):
    task.update_state(state="PROGRESS",
                      meta={"progress": 15, "message": f"Ollama ({ollama_model}) 연결 중..."})
    with open(image_path, "rb") as f:
        img_b64 = base64.b64encode(f.read()).decode()
    prompt = custom_prompt.strip() or _OLLAMA_PROMPTS.get(mode, _OLLAMA_PROMPTS["text"])
    task.update_state(state="PROGRESS", meta={"progress": 30, "message": "모델 추론 중..."})
    try:
        resp = httpx.post(f"{OLLAMA_URL}/api/chat", json={
            "model": ollama_model,
            "messages": [{"role": "user", "content": prompt, "images": [img_b64]}],
            "stream": False, "options": {"temperature": 0.1},
        }, timeout=float(OLLAMA_TIMEOUT))
        resp.raise_for_status()
    except httpx.ConnectError:
        raise Exception(f"Ollama 서버 연결 실패 ({OLLAMA_URL})")
    except httpx.TimeoutException:
        raise Exception(f"Ollama 응답 시간 초과 ({OLLAMA_TIMEOUT}초). OLLAMA_TIMEOUT 값을 늘려주세요.")

    task.update_state(state="PROGRESS", meta={"progress": 85, "message": "결과 저장 중..."})
    full_text = resp.json().get("message", {}).get("content", "").strip()
    if not full_text:
        raise Exception("Ollama 빈 응답. 모델이 설치되어 있는지 확인하세요.")

    tables = _parse_md_tables(full_text) if mode == "structure" else []
    os.makedirs(OUTPUT_DIR, exist_ok=True)
    txt_file = f"{file_id}_ocr.txt"
    with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
        f.write(f"# OCR 결과 (Ollama / {ollama_model})\n\n{full_text}")
    xlsx_file = None
    if tables:
        xlsx_file = f"{file_id}_tables.xlsx"
        _save_excel(tables, os.path.join(OUTPUT_DIR, xlsx_file))
    tables_html = [_md_table_to_html(t) for t in tables]
    lines = [{"text": l, "confidence": 1.0, "bbox": []}
             for l in full_text.splitlines() if l.strip()]
    return {
        "mode": mode, "backend": "ollama", "ollama_model": ollama_model,
        "full_text": full_text, "lines": lines, "line_count": len(lines),
        "txt_file": txt_file,
        "tables": [{"html": h, "rows": len(t), "cols": max(len(r) for r in t) if t else 0}
                   for h, t in zip(tables_html, tables)],
        "xlsx_file": xlsx_file,
    }


def _run_paddle(task, file_id, image_path, mode):
    import cv2
    img = cv2.imread(image_path)
    if img is None:
        raise ValueError("이미지를 읽을 수 없습니다")
    os.makedirs(OUTPUT_DIR, exist_ok=True)
    return _paddle_structure(task, file_id, img) if mode == "structure" \
           else _paddle_text(task, file_id, img)

def _paddle_text(task, file_id, img):
    task.update_state(state="PROGRESS", meta={"progress": 30, "message": "텍스트 인식 중..."})
    result = get_ocr().ocr(img)
    task.update_state(state="PROGRESS", meta={"progress": 80, "message": "결과 정리 중..."})
    lines = []
    if result and len(result) > 0:
        r = result[0]
        if isinstance(r, dict):
            texts  = r.get("rec_texts", [])
            scores = r.get("rec_scores", [])
            for text, conf in zip(texts, scores):
                if text.strip():
                    lines.append({"text": text, "confidence": round(float(conf), 3), "bbox": []})
        elif isinstance(r, list):
            for item in r:
                if item and len(item) == 2:
                    _, (text, conf) = item
                    if text.strip():
                        lines.append({"text": text, "confidence": round(float(conf), 3), "bbox": []})
    full_text = "\n".join(l["text"] for l in lines)
    txt_file  = f"{file_id}_ocr.txt"
    with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
        f.write(full_text)
    return {"mode": "text", "backend": "paddle", "ollama_model": "",
            "full_text": full_text, "lines": lines,
            "line_count": len(lines), "txt_file": txt_file,
            "tables": [], "xlsx_file": None}

def _paddle_structure(task, file_id, img):
    task.update_state(state="PROGRESS", meta={"progress": 20, "message": "레이아웃 분석 중..."})
    result = get_structure()(img)
    task.update_state(state="PROGRESS", meta={"progress": 60, "message": "표 구조 추출 중..."})
    text_blocks, tables_html, tables_data = [], [], []
    for region in result:
        rtype = region.get("type", "").lower()
        if rtype == "table":
            html = region.get("res", {}).get("html", "")
            if html:
                tables_html.append(html)
                tables_data.append(_html_table_to_list(html))
        elif rtype in ("text", "title", "figure_caption"):
            for line in (region.get("res", []) or []):
                if isinstance(line, (list, tuple)) and len(line) == 2:
                    _, (text, _conf) = line
                    text_blocks.append(text)
    full_text = "\n".join(text_blocks)
    task.update_state(state="PROGRESS", meta={"progress": 80, "message": "Excel 생성 중..."})
    xlsx_file = None
    if tables_data:
        xlsx_file = f"{file_id}_tables.xlsx"
        _save_excel(tables_data, os.path.join(OUTPUT_DIR, xlsx_file))
    txt_file = f"{file_id}_ocr.txt"
    with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
        f.write("# 텍스트\n\n" + full_text)
    lines = [{"text": t, "confidence": 1.0, "bbox": []} for t in text_blocks]
    tables_meta = [{"html": h, "rows": len(d), "cols": max(len(r) for r in d) if d else 0}
                   for h, d in zip(tables_html, tables_data)]
    return {"mode": "structure", "backend": "paddle", "ollama_model": "",
            "full_text": full_text, "lines": lines,
            "line_count": len(lines), "txt_file": txt_file,
            "tables": tables_meta, "xlsx_file": xlsx_file}


def _parse_md_tables(text):
    tables, current = [], []
    for line in text.splitlines():
        s = line.strip()
        if s.startswith("|") and s.endswith("|"):
            if all(c in "| -:" for c in s): continue
            current.append([c.strip() for c in s.strip("|").split("|")])
        else:
            if len(current) >= 2: tables.append(current)
            current = []
    if len(current) >= 2: tables.append(current)
    return tables

def _md_table_to_html(table):
    if not table: return ""
    rows = ""
    for i, row in enumerate(table):
        tag = "th" if i == 0 else "td"
        rows += "<tr>" + "".join(f"<{tag}>{c}</{tag}>" for c in row) + "</tr>"
    return f"<table>{rows}</table>"

def _html_table_to_list(html):
    from html.parser import HTMLParser
    class P(HTMLParser):
        def __init__(self):
            super().__init__()
            self.rows, self._row, self._cell, self._in = [], [], [], False
        def handle_starttag(self, tag, attrs):
            if tag == "tr": self._row = []
            elif tag in ("td","th"): self._cell = []; self._in = True
        def handle_endtag(self, tag):
            if tag in ("td","th"): self._row.append("".join(self._cell).strip()); self._in = False
            elif tag == "tr":
                if self._row: self.rows.append(self._row)
        def handle_data(self, data):
            if self._in: self._cell.append(data)
    p = P(); p.feed(html); return p.rows

def _save_excel(tables, path):
    wb = openpyxl.Workbook(); wb.remove(wb.active)
    for i, table in enumerate(tables, 1):
        ws = wb.create_sheet(f"표 {i}")
        thin = Side(style="thin", color="2A2A33")
        bdr  = Border(left=thin, right=thin, top=thin, bottom=thin)
        for r_idx, row in enumerate(table, 1):
            for c_idx, val in enumerate(row, 1):
                cell = ws.cell(row=r_idx, column=c_idx, value=val)
                cell.border = bdr
                cell.alignment = Alignment(horizontal="center", vertical="center", wrap_text=True)
                if r_idx == 1:
                    cell.fill = PatternFill("solid", fgColor="1A1A2E")
                    cell.font = Font(color="00E5A0", bold=True, size=10)
                else:
                    cell.font = Font(size=10)
        for col in ws.columns:
            w = max((len(str(c.value or "")) for c in col), default=8)
            ws.column_dimensions[col[0].column_letter].width = min(w + 4, 40)
    if not wb.sheetnames: wb.create_sheet("Sheet1")
    wb.save(path)