fix:1.修复自定义系统模板提示词的多出问题

backend/app/api/chapters.py

@@ -2709,7 +2709,9 @@ async def regenerate_chapter_stream(
                     analysis=analysis,
                     regenerate_request=regenerate_request,
                     project_context=project_context,
-                    style_content=style_content
+                    style_content=style_content,
+                    user_id=user_id,
+                    db=db_session
                 ):
                     # 处理不同类型的事件
                     if event['type'] == 'chunk':

backend/app/services/chapter_regenerator.py

@@ -177,11 +177,9 @@ class ChapterRegenerator:
         db: AsyncSession = None
     ) -> str:
         """构建完整的重新生成提示词"""
-        # 获取自定义提示词模板
+        # 使用PromptService的get_chapter_regeneration_prompt方法
-        template = await PromptService.get_template("CHAPTER_REGENERATION_SYSTEM", user_id, db)
+        # 该方法会处理自定义模板加载和完整提示词构建
-        # 格式化提示词
+        return await PromptService.get_chapter_regeneration_prompt(
-        return PromptService.format_prompt(
-            template,
             chapter_number=chapter.chapter_number,
             title=chapter.title,
             word_count=chapter.word_count,
@@ -189,7 +187,9 @@ class ChapterRegenerator:
             modification_instructions=modification_instructions,
             project_context=project_context,
             style_content=style_content,
-            target_word_count=regenerate_request.target_word_count
+            target_word_count=regenerate_request.target_word_count,
+            user_id=user_id,
+            db=db
         )
     
     def calculate_content_diff(

backend/app/services/plot_analyzer.py

@@ -53,7 +53,12 @@ class PlotAnalyzer:
             analysis_content = content[:8000] if len(content) > 8000 else content
             
             # 获取自定义提示词模板
+            if user_id and db:
                 template = await PromptService.get_template("PLOT_ANALYSIS", user_id, db)
+            else:
+                # 降级到系统默认模板
+                template = PromptService.PLOT_ANALYSIS
+            
             # 格式化提示词
             prompt = PromptService.format_prompt(
                 template,

backend/app/services/prompt_service.py

@@ -1901,11 +1901,35 @@ class PromptService:
         )
 
     @classmethod
-    def get_chapter_regeneration_prompt(cls, chapter_number: int, title: str, word_count: int, content: str,
+    async def get_chapter_regeneration_prompt(cls, chapter_number: int, title: str, word_count: int, content: str,
                                         modification_instructions: str, project_context: Dict[str, Any],
-                                        style_content: str, target_word_count: int) -> str:
+                                        style_content: str, target_word_count: int,
-        """获取章节重写提示词"""
+                                        user_id: str = None, db = None) -> str:
-        prompt_parts = [cls.CHAPTER_REGENERATION_SYSTEM]
+        """
+        获取章节重写提示词（支持用户自定义）
+        
+        Args:
+            chapter_number: 章节序号
+            title: 章节标题
+            word_count: 原始字数
+            content: 原始内容
+            modification_instructions: 修改指令
+            project_context: 项目上下文
+            style_content: 写作风格
+            target_word_count: 目标字数
+            user_id: 用户ID（可选，用于获取自定义模板）
+            db: 数据库会话（可选，用于查询自定义模板）
+            
+        Returns:
+            完整的章节重写提示词
+        """
+        # 获取系统提示词模板（支持用户自定义）
+        if user_id and db:
+            system_template = await cls.get_template("CHAPTER_REGENERATION_SYSTEM", user_id, db)
+        else:
+            system_template = cls.CHAPTER_REGENERATION_SYSTEM
+        
+        prompt_parts = [system_template]
         
         # 原始章节信息
         prompt_parts.append(f"""## 📖 原始章节信息