# pyright: reportMissingImports=false

from __future__ import annotations

from pathlib import Path
import re

import fitz
import numpy as np
from pptx import Presentation
from pptx.enum.shapes import MSO_SHAPE_TYPE
from rapidocr_onnxruntime import RapidOCR


ROOT = Path(__file__).resolve().parent
SOURCE_DIR = ROOT.parent

PDF_PATH = SOURCE_DIR / "User Journeys.pdf"
PPTX_PATH = SOURCE_DIR / "零售商系统方案研讨会PPT.retro.pptx"

PDF_OUTPUT = ROOT / "User Journeys.md"
PPTX_OUTPUT = ROOT / "零售商系统方案研讨会PPT.retro.md"

OCR = RapidOCR()


def normalize_text(text: str) -> str:
    text = text.replace("\r\n", "\n").replace("\r", "\n")
    lines = [re.sub(r"\s+", " ", line).strip() for line in text.split("\n")]
    return "\n".join(line for line in lines if line)


def extract_page_ocr_text(page: fitz.Page) -> str:
    pix = page.get_pixmap(matrix=fitz.Matrix(4, 4), alpha=False)
    image = np.frombuffer(pix.samples, dtype=np.uint8).reshape(pix.height, pix.width, pix.n)
    result, _ = OCR(image)
    if not result:
        return ""
    return normalize_text("\n".join(str(item[1]) for item in result))


def extract_pdf_to_md(pdf_path: Path, output_path: Path) -> None:
    doc = fitz.open(pdf_path)
    parts: list[str] = [f"# {pdf_path.stem}", ""]

    try:
        for index in range(doc.page_count):
            page = doc.load_page(index)
            text = normalize_text(str(page.get_text("text") or ""))
            if not text:
                text = extract_page_ocr_text(page)
            parts.append(f"## Page {index + 1}")
            parts.append("")
            parts.append(text or "[No extractable text]")
            parts.append("")
    finally:
        doc.close()

    output_path.write_text("\n".join(parts).strip() + "\n", encoding="utf-8")


def iter_shape_text(shape) -> list[str]:
    chunks: list[str] = []

    if hasattr(shape, "has_text_frame") and shape.has_text_frame:
        text = normalize_text(shape.text_frame.text)
        if text:
            chunks.append(text)

    if hasattr(shape, "has_table") and shape.has_table:
        for row in shape.table.rows:
            cells = [normalize_text(cell.text) for cell in row.cells]
            cells = [cell for cell in cells if cell]
            if cells:
                chunks.append(" | ".join(cells))

    if shape.shape_type == MSO_SHAPE_TYPE.GROUP:
        for subshape in shape.shapes:
            chunks.extend(iter_shape_text(subshape))

    return chunks


def extract_pptx_to_md(pptx_path: Path, output_path: Path) -> None:
    prs = Presentation(str(pptx_path))
    parts: list[str] = [f"# {pptx_path.stem}", ""]

    for index, slide in enumerate(prs.slides, start=1):
        title = ""
        parts.append(f"## Slide {index}")
        parts.append("")

        if slide.shapes.title and slide.shapes.title.text:
            title = normalize_text(slide.shapes.title.text)
            if title:
                parts.append(f"### {title}")
                parts.append("")

        seen: set[str] = set()
        collected = []

        for shape in slide.shapes:
            for chunk in iter_shape_text(shape):
                if title and chunk == title:
                    continue
                if chunk and chunk not in seen:
                    seen.add(chunk)
                    collected.append(chunk)

        if collected:
            parts.extend(f"- {chunk}" for chunk in collected)
        else:
            parts.append("[No extractable text]")

        parts.append("")

    output_path.write_text("\n".join(parts).strip() + "\n", encoding="utf-8")


def main() -> None:
    extract_pdf_to_md(PDF_PATH, PDF_OUTPUT)
    extract_pptx_to_md(PPTX_PATH, PPTX_OUTPUT)
    print("Wrote PDF markdown output")
    print("Wrote PPTX markdown output")


if __name__ == "__main__":
    main()