Add architecture documentation and retail system workshop PPT

Architecture-Diagram/extract_requirements_to_md.py

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+# 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()