From 8a59daae6cfc4a56e771173b448f1adc92155799 Mon Sep 17 00:00:00 2001 From: jinye_huang Date: Fri, 25 Jul 2025 12:05:31 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E5=A4=8D=E4=BA=86=E6=8F=90=E7=A4=BA?= =?UTF-8?q?=E8=AF=8D=E4=B8=AD=E6=95=B0=E6=8D=AE=E5=BA=93=E8=B0=83=E5=BA=A6?= =?UTF-8?q?=E9=97=AE=E9=A2=98?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- api/routers/__pycache__/tweet.cpython-312.pyc | Bin 14671 -> 14722 bytes api/routers/tweet.py | 126 +++++-------- .../database_service.cpython-312.pyc | Bin 42883 -> 45481 bytes .../prompt_builder.cpython-312.pyc | Bin 18609 -> 19764 bytes .../prompt_service.cpython-312.pyc | Bin 31390 -> 32336 bytes .../__pycache__/tweet.cpython-312.pyc | Bin 16419 -> 16888 bytes api/services/prompt_builder.py | 177 +++++++----------- api/services/tweet.py | 106 +++++------ 8 files changed, 170 insertions(+), 239 deletions(-) diff --git a/api/routers/__pycache__/tweet.cpython-312.pyc 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z>R-qgi1FWtWAGH**u3kL0c3A_60C(Mp{TXxDFQw=y7LMGFm0*la}|Lb6p;17yi9U` h2ZbX3U{K0& 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, 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zP6n#$Hyx^NT$j`dn!sXuurN5j;tHNxE@dsw7=g)f=QH6$&xU*Z!-x9W&ZBWMl3%=7 z86=l#*!-#(iPat?dn~{V^3PJS?X!sE#01idN8gUZ&n=4rxf`^CRn4mBQ;UT?gW=Xe z)^&U%uJ}U8zS96wUPMI@6`dFx92^=QWNJf4nqi$Mx 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}")