feat：LLM 分析文件并生成结构化建议

app/datafiles/readers.py

@@ -19,7 +19,8 @@ from python_calamine import (
     SheetVisibleEnum,
 )
 
-from app.datafiles.base import MAX_TABLE_ROWS, DataFileError, rows_exceeded
+from app.datafiles.base import MAX_TABLE_ROWS, DataFileError, brief, rows_exceeded
+from app.datafiles.columns import as_text
 from app.schemas.data_file import ParseWarning
 
 # 原始网格比数据多出的标题、表头、空行，读取时先粗略拦住明显超限的文件，精确的行数在拆表后检查
@@ -153,7 +154,7 @@ def read_jsonl(text: str) -> Records:
         result.warnings.append(
             ParseWarning(
                 code="bad_lines_skipped",
-                message=f"跳过了 {len(bad)} 行无法解析的内容：{_line_list(bad)}",
+                message=f"跳过了 {len(bad)} 行无法解析的内容：{brief([f'第 {n} 行' for n in bad])}",
             )
         )
     return result
@@ -230,11 +231,5 @@ def _flatten(record: dict, prefix: str, level: int, out: dict[str, Any]) -> None
 
 
 def _scalar(value: Any) -> Any:
-    if isinstance(value, (dict, list)):
-        return json.dumps(value, ensure_ascii=False)
-    return value
-
-
-def _line_list(numbers: list[int]) -> str:
-    shown = "、".join(f"第 {number} 行" for number in numbers[:5])
-    return shown + ("等" if len(numbers) > 5 else "")
+    # 嵌套的对象、数组存成 JSON 字符串，其余原样交给类型推断
+    return as_text(value) if isinstance(value, (dict, list)) else value