diff --git a/api/routers/__pycache__/tweet.cpython-312.pyc b/api/routers/__pycache__/tweet.cpython-312.pyc
index 8108c72..a300c85 100644
Binary files a/api/routers/__pycache__/tweet.cpython-312.pyc and b/api/routers/__pycache__/tweet.cpython-312.pyc differ
diff --git a/api/routers/tweet.py b/api/routers/tweet.py
index e4d4158..8dabb5f 100644
--- a/api/routers/tweet.py
+++ b/api/routers/tweet.py
@@ -53,73 +53,40 @@ router = APIRouter(
 )
 
 
-def _resolve_ids_to_names_with_mapping(db_service: DatabaseService, 
-                                      styleIds: Optional[List[int]] = None,
-                                      audienceIds: Optional[List[int]] = None,
-                                      scenicSpotIds: Optional[List[int]] = None,
-                                      productIds: Optional[List[int]] = None) -> tuple:
+def _resolve_ids_to_objects(db_service: DatabaseService, 
+                             styleIds: Optional[List[int]] = None,
+                             audienceIds: Optional[List[int]] = None,
+                             scenicSpotIds: Optional[List[int]] = None,
+                             productIds: Optional[List[int]] = None) -> tuple:
     """
-    将ID列表转换为名称列表，并返回ID到名称的映射关系
-    
-    Args:
-        db_service: 数据库服务
-        styleIds: 风格ID列表
-        audienceIds: 受众ID列表
-        scenicSpotIds: 景区ID列表
-        productIds: 产品ID列表
-        
-    Returns:
-        (styles, audiences, scenic_spots, products, id_name_mappings) 名称列表和映射关系元组
+    将ID列表解析为完整的对象记录列表，并返回ID到名称的映射。
     """
-    styles = []
-    audiences = []
-    scenic_spots = []
-    products = []
+    styles, audiences, scenic_spots, products = [], [], [], []
     
-    # 建立ID到名称的映射字典
     id_name_mappings = {
-        'style_mapping': {},    # {name: id}
-        'audience_mapping': {}, # {name: id}
-        'scenic_spot_mapping': {}, # {name: id}
-        'product_mapping': {}   # {name: id}
+        'style_mapping': {}, 'audience_mapping': {},
+        'scenic_spot_mapping': {}, 'product_mapping': {}
     }
-    
-    # 如果数据库服务不可用，返回空列表
+
     if not db_service or not db_service.is_available():
         logger.warning("数据库服务不可用，无法解析ID")
         return styles, audiences, scenic_spots, products, id_name_mappings
-    
-    # 解析风格ID
+
     if styleIds:
-        style_records = db_service.get_styles_by_ids(styleIds)
-        for record in style_records:
-            style_name = record['styleName']
-            styles.append(style_name)
-            id_name_mappings['style_mapping'][style_name] = record['id']
+        styles = db_service.get_styles_by_ids(styleIds)
+        id_name_mappings['style_mapping'] = {record['styleName']: record['id'] for record in styles}
     
-    # 解析受众ID
     if audienceIds:
-        audience_records = db_service.get_audiences_by_ids(audienceIds)
-        for record in audience_records:
-            audience_name = record['audienceName']
-            audiences.append(audience_name)
-            id_name_mappings['audience_mapping'][audience_name] = record['id']
+        audiences = db_service.get_audiences_by_ids(audienceIds)
+        id_name_mappings['audience_mapping'] = {record['audienceName']: record['id'] for record in audiences}
     
-    # 解析景区ID
     if scenicSpotIds:
-        spot_records = db_service.get_scenic_spots_by_ids(scenicSpotIds)
-        for record in spot_records:
-            spot_name = record['name']
-            scenic_spots.append(spot_name)
-            id_name_mappings['scenic_spot_mapping'][spot_name] = record['id']
+        scenic_spots = db_service.get_scenic_spots_by_ids(scenicSpotIds)
+        id_name_mappings['scenic_spot_mapping'] = {record['name']: record['id'] for record in scenic_spots}
     
-    # 解析产品ID
     if productIds:
-        product_records = db_service.get_products_by_ids(productIds)
-        for record in product_records:
-            product_name = record['productName']  # 修改这里，从name改为productName
-            products.append(product_name)
-            id_name_mappings['product_mapping'][product_name] = record['id']
+        products = db_service.get_products_by_ids(productIds)
+        id_name_mappings['product_mapping'] = {record['productName']: record['id'] for record in products}
     
     return styles, audiences, scenic_spots, products, id_name_mappings
 
@@ -141,7 +108,7 @@ def _resolve_ids_to_names(db_service: DatabaseService,
     Returns:
         (styles, audiences, scenic_spots, products) 名称列表元组
     """
-    styles, audiences, scenic_spots, products, _ = _resolve_ids_to_names_with_mapping(
+    styles, audiences, scenic_spots, products, _ = _resolve_ids_to_objects(
         db_service, styleIds, audienceIds, scenicSpotIds, productIds
     )
     return styles, audiences, scenic_spots, products
@@ -213,8 +180,8 @@ async def generate_topics(
     - **productIds**: 产品ID列表
     """
     try:
-        # 将ID转换为名称，并获取映射关系
-        styles, audiences, scenic_spots, products, id_name_mappings = _resolve_ids_to_names_with_mapping(
+        # 将ID解析为完整的对象记录
+        styles, audiences, scenic_spots, products, id_name_mappings = _resolve_ids_to_objects(
             db_service, 
             request.styleIds, 
             request.audienceIds, 
@@ -222,16 +189,26 @@ async def generate_topics(
             request.productIds
         )
         
+        # 从对象中提取名称列表，用于向后兼容
+        style_names = [s['styleName'] for s in styles]
+        audience_names = [a['audienceName'] for a in audiences]
+        scenic_spot_names = [s['name'] for s in scenic_spots]
+        product_names = [p['productName'] for p in products]
+
         request_id, topics = await tweet_service.generate_topics(
             dates=request.dates,
             numTopics=request.numTopics,
-            styles=styles,
-            audiences=audiences,
-            scenic_spots=scenic_spots,
-            products=products
+            styles=style_names,
+            audiences=audience_names,
+            scenic_spots=scenic_spot_names,
+            products=product_names,
+            # 传递完整的对象以供下游使用
+            style_objects=styles,
+            audience_objects=audiences,
+            scenic_spot_objects=scenic_spots,
+            product_objects=products
         )
         
-        # 为topics添加ID字段
         enriched_topics = _add_ids_to_topics(topics, id_name_mappings)
         
         return TopicResponse(
@@ -260,8 +237,8 @@ async def generate_content(
     - **autoJudge**: 是否自动进行内容审核
     """
     try:
-        # 将ID转换为名称
-        styles, audiences, scenic_spots, products = _resolve_ids_to_names(
+        # 将ID解析为完整的对象记录
+        styles, audiences, scenic_spots, products, _ = _resolve_ids_to_objects(
             db_service, 
             request.styleIds, 
             request.audienceIds, 
@@ -271,17 +248,14 @@ async def generate_content(
         
         request_id, topic_index, content = await tweet_service.generate_content(
             topic=request.topic,
-            styles=styles,
-            audiences=audiences,
-            scenic_spots=scenic_spots,
-            products=products,
+            style_objects=styles,
+            audience_objects=audiences,
+            scenic_spot_objects=scenic_spots,
+            product_objects=products,
             autoJudge=request.autoJudge
         )
         
-        # 提取judgeSuccess字段，从content中移除以避免重复
-        judge_success = None
-        if isinstance(content, dict) and 'judgeSuccess' in content:
-            judge_success = content.pop('judgeSuccess')
+        judge_success = content.pop('judgeSuccess', None) if isinstance(content, dict) else None
         
         return ContentResponse(
             requestId=request_id,
@@ -341,8 +315,8 @@ async def judge_content(
     - **productIds**: 产品ID列表
     """
     try:
-        # 将ID转换为名称
-        styles, audiences, scenic_spots, products = _resolve_ids_to_names(
+        # 将ID解析为完整的对象记录
+        styles, audiences, scenic_spots, products, _ = _resolve_ids_to_objects(
             db_service, 
             request.styleIds, 
             request.audienceIds, 
@@ -353,10 +327,10 @@ async def judge_content(
         request_id, topic_index, judged_content, judge_success = await tweet_service.judge_content(
             topic=request.topic,
             content=request.content,
-            styles=styles,
-            audiences=audiences,
-            scenic_spots=scenic_spots,
-            products=products
+            style_objects=styles,
+            audience_objects=audiences,
+            scenic_spot_objects=scenic_spots,
+            product_objects=products
         )
         
         return JudgeResponse(
diff --git a/api/services/__pycache__/database_service.cpython-312.pyc b/api/services/__pycache__/database_service.cpython-312.pyc
index 4336092..c79dd35 100644
Binary files a/api/services/__pycache__/database_service.cpython-312.pyc and b/api/services/__pycache__/database_service.cpython-312.pyc differ
diff --git a/api/services/__pycache__/prompt_builder.cpython-312.pyc b/api/services/__pycache__/prompt_builder.cpython-312.pyc
index 6b7f46b..65f0bb9 100644
Binary files a/api/services/__pycache__/prompt_builder.cpython-312.pyc and b/api/services/__pycache__/prompt_builder.cpython-312.pyc differ
diff --git a/api/services/__pycache__/prompt_service.cpython-312.pyc b/api/services/__pycache__/prompt_service.cpython-312.pyc
index a45a660..2abfdce 100644
Binary files a/api/services/__pycache__/prompt_service.cpython-312.pyc and b/api/services/__pycache__/prompt_service.cpython-312.pyc differ
diff --git a/api/services/__pycache__/tweet.cpython-312.pyc b/api/services/__pycache__/tweet.cpython-312.pyc
index 2ba49f2..664858c 100644
Binary files a/api/services/__pycache__/tweet.cpython-312.pyc and b/api/services/__pycache__/tweet.cpython-312.pyc differ
diff --git a/api/services/prompt_builder.py b/api/services/prompt_builder.py
index 72e3148..95c6fba 100644
--- a/api/services/prompt_builder.py
+++ b/api/services/prompt_builder.py
@@ -57,53 +57,35 @@ class PromptBuilderService:
         
     def build_content_prompt(self, topic: Dict[str, Any], step: str = "content") -> Tuple[str, str]:
         """
-        构建内容生成提示词
-        
-        Args:
-            topic: 选题信息
-            step: 当前步骤，用于过滤参考内容
-            
-        Returns:
-            系统提示词和用户提示词的元组
+        构建内容生成提示词 (已重构)
+        此方法现在依赖于一个预先填充好完整信息的topic对象。
         """
-        # 获取内容生成配置
         content_config = self._ensure_content_config()
-        
-        # 加载系统提示词和用户提示词模板
-        system_prompt_path = content_config.content_system_prompt
-        user_prompt_path = content_config.content_user_prompt
-        
-        # 创建提示词模板
-        template = PromptTemplate(system_prompt_path, user_prompt_path)
-        
-        # 获取风格内容
-        style_filename = topic.get("style", "")
-        style_content = self.prompt_service.get_style_content(style_filename)
-        
-        # 获取目标受众内容
-        demand_filename = topic.get("targetAudience", "")
-        demand_content = self.prompt_service.get_audience_content(demand_filename)
-        
-        # 获取景区信息
-        object_name = topic.get("object", "")
-        object_content = self.prompt_service.get_scenic_spot_info(object_name)
-        
-        # 获取产品信息
-        product_name = topic.get("product", "")
-        product_content = self.prompt_service.get_product_info(product_name)
-        
-        # 获取参考内容
+        template = PromptTemplate(content_config.content_system_prompt, content_config.content_user_prompt)
+
+        # 从预填充的topic对象中直接获取信息，不再调用prompt_service
+        style_obj = topic.get('style_object', {})
+        style_content = f"{style_obj.get('styleName', '')}\n{style_obj.get('description', '')}"
+
+        audience_obj = topic.get('audience_object', {})
+        demand_content = f"{audience_obj.get('audienceName', '')}\n{audience_obj.get('description', '')}"
+
+        spot_obj = topic.get('scenic_spot_object', {})
+        object_content = f"{spot_obj.get('name', '')}\n{spot_obj.get('description', '')}"
+
+        product_obj = topic.get('product_object', {})
+        product_content = f"{product_obj.get('productName', '')}\n{product_obj.get('detailedDescription', '')}"
+
+        # 获取通用的参考内容
         refer_content = self.prompt_service.get_refer_content(step)
         
-        # 构建系统提示词
         system_prompt = template.get_system_prompt()
         
-        # 构建用户提示词
         user_prompt = template.build_user_prompt(
-            style_content=f"{style_filename}\n{style_content}",
-            demand_content=f"{demand_filename}\n{demand_content}",
-            object_content=f"{object_name}\n{object_content}",
-            product_content=f"{product_name}\n{product_content}",
+            style_content=style_content,
+            demand_content=demand_content,
+            object_content=object_content,
+            product_content=product_content,
             refer_content=refer_content
         )
         
@@ -229,7 +211,15 @@ class PromptBuilderService:
         
         return system_prompt, user_prompt
         
-    def build_topic_prompt(self, products: Optional[List[str]] = None, scenic_spots: Optional[List[str]] = None, styles: Optional[List[str]] = None, audiences: Optional[List[str]] = None, dates: Optional[str] = None, numTopics: int = 5) -> Tuple[str, str]:
+    def build_topic_prompt(self, products: Optional[List[str]] = None,
+                             scenic_spots: Optional[List[str]] = None,
+                             styles: Optional[List[str]] = None,
+                             audiences: Optional[List[str]] = None,
+                             dates: Optional[str] = None, numTopics: int = 5,
+                             style_objects: Optional[List[Dict[str, Any]]] = None,
+                             audience_objects: Optional[List[Dict[str, Any]]] = None,
+                             scenic_spot_objects: Optional[List[Dict[str, Any]]] = None,
+                             product_objects: Optional[List[Dict[str, Any]]] = None) -> Tuple[str, str]:
         """
         构建选题生成提示词
         
@@ -253,59 +243,50 @@ class PromptBuilderService:
         if not system_prompt_path or not user_prompt_path:
             raise ValueError("选题提示词模板路径不完整")
         
-        # 创建提示词模板
         template = PromptTemplate(system_prompt_path, user_prompt_path)
         
-        # 处理日期
-        if dates:
-            if ' to ' in dates:
-                start_date, end_date = dates.split(' to ')
-                month = f"从 {start_date} 到 {end_date}"
-            elif ',' in dates:
-                month = ', '.join(dates.split(','))
-            else:
-                month = dates
-        else:
-            month = ''
-        
-        # 获取风格内容
-        style_content = ''
-        if styles:
+        month = dates or ''
+        if dates and ' to ' in dates:
+            start_date, end_date = dates.split(' to ')
+            month = f"从 {start_date} 到 {end_date}"
+        elif dates and ',' in dates:
+            month = ', '.join(dates.split(','))
+
+        # 使用传入的完整对象构建内容，避免重复查询
+        if style_objects:
+            style_content = '\n'.join([f"{obj['styleName']}: {obj.get('description', '')}" for obj in style_objects])
+        elif styles:
             style_content = '\n'.join([f"{style}: {self.prompt_service.get_style_content(style)}" for style in styles])
         else:
             all_styles = self.prompt_service.get_all_styles()
             style_content = "Style文件列表:\n" + "\n".join([f"- {style['name']}" for style in all_styles])
-        
-        # 获取受众内容
-        demand_content = ''
-        if audiences:
+
+        if audience_objects:
+            demand_content = '\n'.join([f"{obj['audienceName']}: {obj.get('description', '')}" for obj in audience_objects])
+        elif audiences:
             demand_content = '\n'.join([f"{audience}: {self.prompt_service.get_audience_content(audience)}" for audience in audiences])
         else:
             all_audiences = self.prompt_service.get_all_audiences()
             demand_content = "Demand文件列表:\n" + "\n".join([f"- {audience['name']}" for audience in all_audiences])
-        
-        # 获取参考内容
-        refer_content = self.prompt_service.get_refer_content("topic")
-        
-        # 获取景区内容
-        object_content = ''
-        if scenic_spots:
+
+        if scenic_spot_objects:
+            object_content = '\n'.join([f"{obj['name']}: {obj.get('description', '')}" for obj in scenic_spot_objects])
+        elif scenic_spots:
             object_content = '\n'.join([f"{spot}: {self.prompt_service.get_scenic_spot_info(spot)}" for spot in scenic_spots])
         else:
             all_spots = self.prompt_service.get_all_scenic_spots()
             object_content = "Object信息:\n" + "\n".join([f"- {spot['name']}" for spot in all_spots])
-        
-        # 获取产品内容
-        product_content = ''
-        if products:
+
+        if product_objects:
+            product_content = '\n'.join([f"{obj['productName']}: {obj.get('detailedDescription', '')}" for obj in product_objects])
+        elif products:
             product_content = '\n'.join([f"{product}: {self.prompt_service.get_product_info(product)}" for product in products])
         else:
-            product_content = ''  # 假设没有默认产品列表
-        
-        # 构建系统提示词
+            product_content = ''
+
+        refer_content = self.prompt_service.get_refer_content("topic")
         system_prompt = template.get_system_prompt()
         
-        # 构建创作资料
         creative_materials = (
             f"你拥有的创作资料如下：\n"
             f"风格信息:\n{style_content}\n\n"
@@ -315,7 +296,6 @@ class PromptBuilderService:
             f"产品信息:\n{product_content}"
         )
         
-        # 构建用户提示词
         user_prompt = template.build_user_prompt(
             creative_materials=creative_materials,
             numTopics=numTopics,
@@ -326,44 +306,25 @@ class PromptBuilderService:
     
     def build_judge_prompt(self, topic: Dict[str, Any], content: Dict[str, Any]) -> Tuple[str, str]:
         """
-        构建内容审核提示词
-        
-        Args:
-            topic: 选题信息
-            content: 生成的内容
-            
-        Returns:
-            系统提示词和用户提示词的元组
+        构建内容审核提示词 (已重构)
+        此方法现在依赖于一个预先填充好完整信息的topic对象。
         """
-        # 获取内容生成配置
         content_config = self._ensure_content_config()
-        
-        # 从配置中获取审核提示词模板路径
-        system_prompt_path = content_config.judger_system_prompt
-        user_prompt_path = content_config.judger_user_prompt
-        
-        # 创建提示词模板
-        template = PromptTemplate(system_prompt_path, user_prompt_path)
-        
-        # 获取景区信息
-        object_name = topic.get("object", "")
-        object_content = self.prompt_service.get_scenic_spot_info(object_name)
-        
-        # 获取产品信息
-        product_name = topic.get("product", "")
-        product_content = self.prompt_service.get_product_info(product_name)
-        
-        # 获取参考内容
+        template = PromptTemplate(content_config.judger_system_prompt, content_config.judger_user_prompt)
+
+        # 从预填充的topic对象中直接获取信息
+        spot_obj = topic.get('scenic_spot_object', {})
+        object_content = f"{spot_obj.get('name', '')}\n{spot_obj.get('description', '')}"
+
+        product_obj = topic.get('product_object', {})
+        product_content = f"{product_obj.get('productName', '')}\n{product_obj.get('detailedDescription', '')}"
+
         refer_content = self.prompt_service.get_refer_content("judge")
-        
-        # 构建系统提示词
         system_prompt = template.get_system_prompt()
         
-        # 格式化内容
         import json
         tweet_content = json.dumps(content, ensure_ascii=False, indent=4)
         
-        # 构建用户提示词
         user_prompt = template.build_user_prompt(
             tweet_content=tweet_content,
             object_content=object_content,
@@ -371,7 +332,7 @@ class PromptBuilderService:
             refer_content=refer_content
         )
         
-        return system_prompt, user_prompt 
+        return system_prompt, user_prompt
 
     def build_judge_prompt_with_params(self, topic: Dict[str, Any], content: Dict[str, Any],
                                      styles: Optional[List[str]] = None,
diff --git a/api/services/tweet.py b/api/services/tweet.py
index d703297..49fe64c 100644
--- a/api/services/tweet.py
+++ b/api/services/tweet.py
@@ -48,11 +48,15 @@ class TweetService:
         self.prompt_service = PromptService(config_manager)
         self.prompt_builder = PromptBuilderService(config_manager, self.prompt_service)
         
-    async def generate_topics(self, dates: Optional[str] = None, numTopics: int = 5, 
-                            styles: Optional[List[str]] = None, 
+    async def generate_topics(self, dates: Optional[str] = None, numTopics: int = 5,
+                            styles: Optional[List[str]] = None,
                             audiences: Optional[List[str]] = None,
                             scenic_spots: Optional[List[str]] = None,
-                            products: Optional[List[str]] = None) -> Tuple[str, List[Dict[str, Any]]]:
+                            products: Optional[List[str]] = None,
+                            style_objects: Optional[List[Dict[str, Any]]] = None,
+                            audience_objects: Optional[List[Dict[str, Any]]] = None,
+                            scenic_spot_objects: Optional[List[Dict[str, Any]]] = None,
+                            product_objects: Optional[List[Dict[str, Any]]] = None) -> Tuple[str, List[Dict[str, Any]]]:
         """
         生成选题
         
@@ -63,6 +67,10 @@ class TweetService:
             audiences: 受众列表
             scenic_spots: 景区列表
             products: 产品列表
+            style_objects: 风格对象列表
+            audience_objects: 受众对象列表
+            scenic_spot_objects: 景区对象列表
+            product_objects: 产品对象列表
             
         Returns:
             请求ID和生成的选题列表
@@ -82,7 +90,11 @@ class TweetService:
             styles=styles,
             audiences=audiences,
             dates=dates,
-            numTopics=numTopics
+            numTopics=numTopics,
+            style_objects=style_objects,
+            audience_objects=audience_objects,
+            scenic_spot_objects=scenic_spot_objects,
+            product_objects=product_objects
         )
         
         # 使用预构建的提示词生成选题
@@ -97,11 +109,11 @@ class TweetService:
         logger.info(f"选题生成完成，请求ID: {requestId}, 数量: {len(topics)}")
         return requestId, topics
         
-    async def generate_content(self, topic: Optional[Dict[str, Any]] = None, 
-                             styles: Optional[List[str]] = None,
-                             audiences: Optional[List[str]] = None,
-                             scenic_spots: Optional[List[str]] = None,
-                             products: Optional[List[str]] = None,
+    async def generate_content(self, topic: Optional[Dict[str, Any]] = None,
+                             style_objects: Optional[List[Dict[str, Any]]] = None,
+                             audience_objects: Optional[List[Dict[str, Any]]] = None,
+                             scenic_spot_objects: Optional[List[Dict[str, Any]]] = None,
+                             product_objects: Optional[List[Dict[str, Any]]] = None,
                              autoJudge: bool = False) -> Tuple[str, str, Dict[str, Any]]:
         """
         为选题生成内容
@@ -117,25 +129,28 @@ class TweetService:
         Returns:
             请求ID、选题索引和生成的内容（包含judgeSuccess状态）
         """
-        # 如果没有提供topic，创建一个基础的topic
         if not topic:
             topic = {"index": "1", "date": "2024-07-01"}
         
         topicIndex = topic.get('index', 'N/A')
         logger.info(f"开始为选题 {topicIndex} 生成内容{'（含审核）' if autoJudge else ''}")
         
-        # 创建topic的副本并应用覆盖参数
+        # 核心修改：创建一个增强版的topic，将所有需要的信息预先填充好
         enhanced_topic = topic.copy()
-        if styles and len(styles) > 0:
-            enhanced_topic['style'] = styles[0]  # 使用第一个风格
-        if audiences and len(audiences) > 0:
-            enhanced_topic['targetAudience'] = audiences[0]  # 使用第一个受众
-        if scenic_spots and len(scenic_spots) > 0:
-            enhanced_topic['object'] = scenic_spots[0]  # 使用第一个景区
-        if products and len(products) > 0:
-            enhanced_topic['product'] = products[0]  # 使用第一个产品
-        
-        # 使用PromptBuilderService构建提示词
+        if style_objects:
+            enhanced_topic['style_object'] = style_objects[0]
+            enhanced_topic['style'] = style_objects[0].get('styleName')
+        if audience_objects:
+            enhanced_topic['audience_object'] = audience_objects[0]
+            enhanced_topic['targetAudience'] = audience_objects[0].get('audienceName')
+        if scenic_spot_objects:
+            enhanced_topic['scenic_spot_object'] = scenic_spot_objects[0]
+            enhanced_topic['object'] = scenic_spot_objects[0].get('name')
+        if product_objects:
+            enhanced_topic['product_object'] = product_objects[0]
+            enhanced_topic['product'] = product_objects[0].get('productName')
+
+        # 使用PromptBuilderService构建提示词，现在它只需要enhanced_topic
         system_prompt, user_prompt = self.prompt_builder.build_content_prompt(enhanced_topic, "content")
         
         # 使用预构建的提示词生成内容
@@ -207,61 +222,42 @@ class TweetService:
         return requestId, topicIndex, content
         
     async def judge_content(self, topic: Optional[Dict[str, Any]] = None, content: Dict[str, Any] = {},
-                          styles: Optional[List[str]] = None,
-                          audiences: Optional[List[str]] = None,
-                          scenic_spots: Optional[List[str]] = None,
-                          products: Optional[List[str]] = None) -> Tuple[str, str, Dict[str, Any], bool]:
+                          style_objects: Optional[List[Dict[str, Any]]] = None,
+                          audience_objects: Optional[List[Dict[str, Any]]] = None,
+                          scenic_spot_objects: Optional[List[Dict[str, Any]]] = None,
+                          product_objects: Optional[List[Dict[str, Any]]] = None) -> Tuple[str, str, Dict[str, Any], bool]:
         """
-        审核内容
-        
-        Args:
-            topic: 选题信息
-            content: 要审核的内容
-            styles: 风格列表
-            audiences: 受众列表
-            scenic_spots: 景区列表
-            products: 产品列表
-            
-        Returns:
-            请求ID、选题索引、审核后的内容和审核是否成功
+        审核内容 (已重构)
         """
-        # 如果没有提供topic，创建一个基础的topic
         if not topic:
             topic = {"index": "1", "date": "2024-07-01"}
-        
-        # 如果没有提供content，返回错误
         if not content:
             content = {"title": "未提供内容", "content": "未提供内容"}
         
         topicIndex = topic.get('index', 'unknown')
         logger.info(f"开始审核选题 {topicIndex} 的内容")
         
-        # 创建topic的副本并应用覆盖参数
+        # 构建包含所有预取信息的enhanced_topic
         enhanced_topic = topic.copy()
-        if styles and len(styles) > 0:
-            enhanced_topic['style'] = styles[0]  # 使用第一个风格
-        if audiences and len(audiences) > 0:
-            enhanced_topic['targetAudience'] = audiences[0]  # 使用第一个受众
-        if scenic_spots and len(scenic_spots) > 0:
-            enhanced_topic['object'] = scenic_spots[0]  # 使用第一个景区
-        if products and len(products) > 0:
-            enhanced_topic['product'] = products[0]  # 使用第一个产品
-        
-        # 使用PromptBuilderService构建提示词
+        if style_objects:
+            enhanced_topic['style_object'] = style_objects[0]
+        if audience_objects:
+            enhanced_topic['audience_object'] = audience_objects[0]
+        if scenic_spot_objects:
+            enhanced_topic['scenic_spot_object'] = scenic_spot_objects[0]
+        if product_objects:
+            enhanced_topic['product_object'] = product_objects[0]
+            
         system_prompt, user_prompt = self.prompt_builder.build_judge_prompt(enhanced_topic, content)
         
-        # 使用预构建的提示词进行审核
         judged_data = await self.content_judger.judge_content_with_prompt(content, enhanced_topic, system_prompt, user_prompt)
         
-        # 提取审核是否成功（content_judger返回judge_success字段）
         judgeSuccess = judged_data.get('judge_success', False)
         
-        # 统一字段命名：移除judge_success，添加judgeSuccess
         if 'judge_success' in judged_data:
             judged_data = {k: v for k, v in judged_data.items() if k != 'judge_success'}
             judged_data['judgeSuccess'] = judgeSuccess
         
-        # 生成请求ID
         requestId = f"judge-{datetime.now().strftime('%Y%m%d-%H%M%S')}-{str(uuid.uuid4())[:8]}"
         
         logger.info(f"内容审核完成，请求ID: {requestId}, 选题索引: {topicIndex}, 审核结果: {judgeSuccess}")