Update app.py

app.py

@@ -25,12 +25,6 @@ Included (data-driven, no institution names):
 
 Configure GLMOCR_API_KEY (environment variable). Optional: glmocr + gradio +
 pymupdf + pillow installed.
-
-When GLMOCR_PREFER_PDF_TEXT_BODY is 1 (default), searchable PDFs skip vision OCR
-for the body and return each page's embedded text so output matches the PDF text
-layer. Set GLMOCR_PREFER_PDF_TEXT_BODY=0 to force the image OCR path. Optional
-GLMOCR_MIN_PDF_BODY_CHARS (default 120) is the minimum characters per page required
-to use the text-layer path for the whole document.
 """
 
 # Patch asyncio first (before Gradio imports it) to reduce Python 3.13 loop noise
@@ -55,7 +49,7 @@ import os
 import re
 import tempfile
 from collections import Counter
-from typing import List, Optional, Tuple
+from typing import List, Tuple
 
 import yaml
 
@@ -194,41 +188,6 @@ def extract_zone_text_pdf(pdf_path, page_num, y_start_frac, y_end_frac):
         return ""
 
 
-def _prefer_pdf_text_body() -> bool:
-    v = os.environ.get("GLMOCR_PREFER_PDF_TEXT_BODY", "1").strip().lower()
-    return v in ("1", "true", "yes", "")
-
-
-def extract_pdf_body_text_all_pages_if_suitable(pdf_path: str) -> Optional[List[str]]:
-    try:
-        import pymupdf as fitz
-    except ImportError:
-        return None
-    try:
-        min_c = int(os.environ.get("GLMOCR_MIN_PDF_BODY_CHARS", "120"))
-    except ValueError:
-        min_c = 120
-    try:
-        doc = fitz.open(pdf_path)
-    except Exception:
-        return None
-    try:
-        if len(doc) < 1:
-            return None
-        out: List[str] = []
-        for i in range(len(doc)):
-            t = (doc[i].get_text("text") or "").strip()
-            if len(t) < min_c:
-                return None
-            out.append(t)
-        return out
-    finally:
-        try:
-            doc.close()
-        except Exception:
-            pass
-
-
 def extract_pdf_text_in_band(pdf_path, page_num, y_start_frac, y_end_frac):
     try:
         import pymupdf as fitz
@@ -656,12 +615,6 @@ def run_ocr(uploaded_file):
     try:
         path = uploaded_file.name if hasattr(uploaded_file, "name") else str(uploaded_file)
         is_pdf = path.lower().endswith(".pdf")
-
-        if is_pdf and _prefer_pdf_text_body():
-            pdf_pages = extract_pdf_body_text_all_pages_if_suitable(path)
-            if pdf_pages is not None:
-                return "\n\n---page-separator---\n\n".join(pdf_pages)
-
         parser = get_parser()
 
         page_heights: List[int] = []
@@ -759,8 +712,8 @@ def _create_gradio_demo():
     with gr.Blocks(title="GLM-OCR (simple)") as demo:
         gr.Markdown(
             "# GLM-OCR (simple)\n"
-            "Searchable PDFs use embedded page text by default (matches the PDF text layer). "
-            "Otherwise the vision model reads rasterized pages. Images always use vision OCR."
+            "Upload a PDF or image. Header and footer bands are included; "
+            "body OCR is passed through with only light markdown cleanup."
         )
         file_in = gr.File(
             label="Upload PDF or image",
@@ -773,4 +726,4 @@ def _create_gradio_demo():
 
 
 if __name__ == "__main__":
-    _create_gradio_demo().launch(share=True)
+    _create_gradio_demo().launch()