Introduce Project ID for context management, finalizing the stateful API pipeline from file submission to graph construction.

backend/app/services/text_processor.py

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+"""
+文本处理服务
+"""
+
+from typing import List, Optional
+from ..utils.file_parser import FileParser, split_text_into_chunks
+
+
+class TextProcessor:
+    """文本处理器"""
+    
+    @staticmethod
+    def extract_from_files(file_paths: List[str]) -> str:
+        """从多个文件提取文本"""
+        return FileParser.extract_from_multiple(file_paths)
+    
+    @staticmethod
+    def split_text(
+        text: str,
+        chunk_size: int = 500,
+        overlap: int = 50
+    ) -> List[str]:
+        """
+        分割文本
+        
+        Args:
+            text: 原始文本
+            chunk_size: 块大小
+            overlap: 重叠大小
+            
+        Returns:
+            文本块列表
+        """
+        return split_text_into_chunks(text, chunk_size, overlap)
+    
+    @staticmethod
+    def preprocess_text(text: str) -> str:
+        """
+        预处理文本
+        - 移除多余空白
+        - 标准化换行
+        
+        Args:
+            text: 原始文本
+            
+        Returns:
+            处理后的文本
+        """
+        import re
+        
+        # 标准化换行
+        text = text.replace('\r\n', '\n').replace('\r', '\n')
+        
+        # 移除连续空行（保留最多两个换行）
+        text = re.sub(r'\n{3,}', '\n\n', text)
+        
+        # 移除行首行尾空白
+        lines = [line.strip() for line in text.split('\n')]
+        text = '\n'.join(lines)
+        
+        return text.strip()
+    
+    @staticmethod
+    def get_text_stats(text: str) -> dict:
+        """获取文本统计信息"""
+        return {
+            "total_chars": len(text),
+            "total_lines": text.count('\n') + 1,
+            "total_words": len(text.split()),
+        }
+