"""Document parsing — PyMuPDF for digital PDFs; MiniCPM-V OCR on Modal; LiteParse for layout only."""

from __future__ import annotations

import base64
import io
import logging
import os
import re
import tempfile
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import fitz
from liteparse import LiteParse, ParseResult, ParsedPage

from utils.pdf_parser import (
    extract_pdf_spatial_pages,
    render_page_image,
    render_page_png_base64,
)

if TYPE_CHECKING:
    from models.ocr import MiniCPMVOCR

logger = logging.getLogger(__name__)

_HTML_TAG = re.compile(r"<[^>]+>")
_IMAGE_SUFFIXES = {".png", ".jpg", ".jpeg", ".tiff", ".tif", ".bmp", ".webp", ".gif"}


@lru_cache(maxsize=1)
def _get_layout_parser() -> LiteParse:
    """LiteParse for layout/format detection only — OCR disabled (text from MiniCPM-V)."""
    return LiteParse(
        ocr_enabled=False,
        dpi=300,
        quiet=True,
    )


def _suffix_from_filename(filename: Optional[str]) -> str:
    if filename and "." in filename:
        ext = os.path.splitext(filename)[1].lower()
        if ext:
            return ext
    return ".pdf"


def _is_image_suffix(suffix: str) -> bool:
    return suffix.lower() in _IMAGE_SUFFIXES


def _clean_spatial_text(text: str) -> str:
    if not text:
        return ""
    cleaned = text.replace("\r\n", "\n").replace("\r", "\n")
    if "<" in cleaned and ">" in cleaned:
        cleaned = re.sub(r"<br\s*/?>", "\n", cleaned, flags=re.IGNORECASE)
        cleaned = re.sub(r"</tr>", "\n", cleaned, flags=re.IGNORECASE)
        cleaned = re.sub(r"</t[dh]>", " ", cleaned, flags=re.IGNORECASE)
        cleaned = _HTML_TAG.sub("", cleaned)
    cleaned = re.sub(r"\n{3,}", "\n\n", cleaned)
    return cleaned.rstrip()


def _image_to_png_bytes(image_bytes: bytes) -> bytes:
    from PIL import Image

    image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
    buf = io.BytesIO()
    image.save(buf, format="PNG")
    return buf.getvalue()


def _page_image_to_png_bytes(file_bytes: bytes, page_num: int) -> bytes:
    image = render_page_image(file_bytes, page_num)
    buf = io.BytesIO()
    image.save(buf, format="PNG")
    return buf.getvalue()


def _modal_ocr_page(file_bytes: bytes, page_num: int, ocr: MiniCPMVOCR) -> str:
    png_bytes = _page_image_to_png_bytes(file_bytes, page_num)
    return ocr.extract_text(png_bytes)


def _build_parse_result(pages: List[Tuple[int, str]]) -> ParseResult:
    parsed_pages = [
        ParsedPage(page_num=n, width=0.0, height=0.0, text=t, text_items=[])
        for n, t in pages
        if t.strip()
    ]
    full_text = "\n\n".join(p.text for p in parsed_pages)
    return ParseResult(pages=parsed_pages, text=full_text)


def _liteparse_layout_pages(file_bytes: bytes) -> List[Tuple[int, str]]:
    """Optional layout pass — keeps table/section structure without running Tesseract OCR."""
    try:
        result = _get_layout_parser().parse(file_bytes)
        return [(page.page_num, page.text) for page in result.pages if page.text.strip()]
    except Exception as exc:
        logger.debug("LiteParse layout pass skipped: %s", exc)
        return []


def _parse_pdf_hybrid(file_bytes: bytes, ocr: MiniCPMVOCR) -> ParseResult:
    page_infos = extract_pdf_spatial_pages(file_bytes)
    pages_out: List[Tuple[int, str]] = []

    for page_num, text, is_sparse in page_infos:
        if is_sparse:
            try:
                logger.info("MiniCPM-V OCR on PDF page %d", page_num)
                text = _modal_ocr_page(file_bytes, page_num, ocr)
            except Exception as exc:
                logger.warning("Modal OCR failed on page %d: %s", page_num, exc)
        pages_out.append((page_num, _clean_spatial_text(text)))

    return _build_parse_result(pages_out)


def parse_document(
    file_bytes: bytes,
    filename: Optional[str],
    ocr: MiniCPMVOCR,
) -> ParseResult:
    suffix = _suffix_from_filename(filename)

    if suffix == ".pdf":
        return _parse_pdf_hybrid(file_bytes, ocr)

    if _is_image_suffix(suffix):
        logger.info("MiniCPM-V OCR on image %s", filename or "upload")
        text = ocr.extract_text(_image_to_png_bytes(file_bytes))
        cleaned = _clean_spatial_text(text)
        return ParseResult(
            pages=[
                ParsedPage(
                    page_num=1,
                    width=0.0,
                    height=0.0,
                    text=cleaned,
                    text_items=[],
                )
            ],
            text=cleaned,
        )

    with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
        tmp.write(file_bytes)
        tmp_path = tmp.name
    try:
        layout_pages = _liteparse_layout_pages(file_bytes)
        if layout_pages:
            return _build_parse_result(
                [(num, _clean_spatial_text(text)) for num, text in layout_pages]
            )
        result = _get_layout_parser().parse(tmp_path)
        return ParseResult(
            pages=result.pages,
            text=_clean_spatial_text(result.text),
        )
    finally:
        os.unlink(tmp_path)


def file_to_ocr_image_bytes(
    file_bytes: bytes,
    filename: Optional[str] = None,
    page_num: int = 1,
) -> bytes:
    suffix = _suffix_from_filename(filename)
    if _is_image_suffix(suffix):
        return _image_to_png_bytes(file_bytes)
    return _page_image_to_png_bytes(file_bytes, page_num)


def _modal_structured_page(file_bytes: bytes, page_num: int, ocr: MiniCPMVOCR) -> str:
    png_bytes = _page_image_to_png_bytes(file_bytes, page_num)
    return ocr.extract_structured(png_bytes)


def extract_document_structured_ocr(
    file_bytes: bytes,
    filename: Optional[str],
    ocr: MiniCPMVOCR,
) -> dict:
    """Structured OCR via MiniCPM-V — sections, key-value fields, and table rows."""
    from utils.ocr_structure import merge_structured_pages, parse_structured_page

    suffix = _suffix_from_filename(filename)
    pages = []

    if _is_image_suffix(suffix):
        logger.info("MiniCPM-V structured OCR on image %s", filename or "upload")
        raw = ocr.extract_structured(_image_to_png_bytes(file_bytes))
        pages.append(parse_structured_page(raw, page_number=1))
    else:
        doc = fitz.open(stream=file_bytes, filetype="pdf")
        try:
            page_count = doc.page_count
        finally:
            doc.close()

        for page_num in range(1, page_count + 1):
            logger.info("MiniCPM-V structured OCR page %d/%d", page_num, page_count)
            raw = _modal_structured_page(file_bytes, page_num, ocr)
            pages.append(parse_structured_page(raw, page_number=page_num))

    return merge_structured_pages(pages, filename)


def extract_document_ocr(
    file_bytes: bytes,
    filename: Optional[str],
    ocr: MiniCPMVOCR,
) -> str:
    """Full-document OCR via MiniCPM-V (Document OCR UI)."""
    suffix = _suffix_from_filename(filename)

    if _is_image_suffix(suffix):
        return _clean_spatial_text(ocr.extract_text(_image_to_png_bytes(file_bytes)))

    doc = fitz.open(stream=file_bytes, filetype="pdf")
    try:
        page_count = doc.page_count
    finally:
        doc.close()

    parts: List[str] = []
    for page_num in range(1, page_count + 1):
        logger.info("MiniCPM-V OCR page %d/%d", page_num, page_count)
        parts.append(_modal_ocr_page(file_bytes, page_num, ocr))

    return _clean_spatial_text("\n\n".join(part for part in parts if part.strip()))


def extract_text(
    file_bytes: bytes,
    filename: Optional[str],
    ocr: MiniCPMVOCR,
) -> str:
    return extract_document_ocr(file_bytes, filename, ocr)


def preview_page_base64(
    file_bytes: bytes,
    page_num: int = 1,
    filename: Optional[str] = None,
) -> Optional[str]:
    suffix = _suffix_from_filename(filename)

    if _is_image_suffix(suffix):
        return base64.b64encode(file_bytes).decode("ascii")

    try:
        return render_page_png_base64(file_bytes, page_num=page_num)
    except Exception as exc:
        logger.warning("PDF preview render failed: %s", exc)
        return None