Update app.py

app.py

@@ -1,4 +1,22 @@
 
+# 🚫 스마트 따옴표 제거기 - 런타임에서 1회 실행됨
+def clean_smart_quotes_inplace():
+    import os
+    path = os.path.abspath(__file__)
+    with open(path, "r", encoding="utf-8") as f:
+        content = f.read()
+
+    for wrong, right in {"‘": "'", "’": "'", "“": '"', "”": '"'}.items():
+        content = content.replace(wrong, right)
+
+    with open(path, "w", encoding="utf-8") as f:
+        f.write(content)
+
+# 🔥 단 한 번 실행 (다시 실행되면 의미 없음)
+clean_smart_quotes_inplace()
+
+
+
 # 📦 PART 1: 이름 추출기 + 태그 치환기
 
 from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
@@ -39,17 +57,21 @@ def apply_name_tags(text: str, names: list, start_index: int = 100) -> tuple[str
     tagged_text = text
     counter = start_index
 
-# ✅ 긴 이름 우선 정렬
-names = sorted(set(names), key=len, reverse=True)
-
-for name in names:
-    tag = f"{TAG_PREFIX}{counter:03d}"
-    pattern = re.compile(rf'([\s\(\["\']*){re.escape(name)}([가-힣\s.,;:!?()\[\]"\'"]*)', re.IGNORECASE)
-    tagged_text, n = pattern.subn(tag, tagged_text)
-    if n > 0:
-        mapping[tag] = name
-        counter += 1
-return tagged_text, mapping
+    # ✅ 긴 이름 우선 정렬
+    names = sorted(set(names), key=len, reverse=True)
+
+    for name in names:
+        tag = f"{TAG_PREFIX}{counter:03d}"
+        pattern = re.compile(
+            rf'([\s\(\["\']*){re.escape(name)}([가-힣\s.,;:!?()\[\]"\'"]*)',
+            re.IGNORECASE
+        )
+        tagged_text, n = pattern.subn(tag, tagged_text)
+        if n > 0:
+            mapping[tag] = name
+            counter += 1
+    return tagged_text, mapping
+