[fix] (LLM 提供商) 传递 unified_msg_origin 以获取正确的 LLM 提供商

src/analysis/llm_analyzer.py

@@ -81,8 +81,6 @@ class LLMAnalyzer:
                     # 确保使用当前指定的模型
                     if provider is None:
                         provider = self.context.get_using_provider(umo=umo)
-                        
-                        # 安全地获取 provider ID
                         provider_id = 'unknown'
                         if provider:
                             try:
@@ -90,10 +88,7 @@ class LLMAnalyzer:
                                 provider_id = meta.id
                             except Exception as e:
                                 logger.debug(f"获取提供商ID失败: {e}")
-                        
                         logger.info(f"获取到的 provider ID: {provider_id}")
-                        
-                        # 如果获取失败，尝试使用全局默认提供商或者回退方案
                         if not provider or provider_id == 'unknown':
                             logger.warning(f"获取的提供商不正确 (Provider ID: {provider_id})")
 
@@ -118,7 +113,7 @@ class LLMAnalyzer:
         logger.error(f"LLM请求全部重试失败: {last_exc}")
         return None
 
-    async def analyze_topics(self, messages: List[Dict]) -> Tuple[List[SummaryTopic], TokenUsage]:
+    async def analyze_topics(self, messages: List[Dict], umo: str = None) -> Tuple[List[SummaryTopic], TokenUsage]:
         """使用LLM分析话题"""
         try:
             # 提取文本消息
@@ -203,12 +198,7 @@ class LLMAnalyzer:
 """
 
             # 调用LLM
-            provider = self.context.get_using_provider()
-            if not provider:
-                logger.warning("未配置LLM提供商，跳过话题分析")
-                return [], TokenUsage()
-
-            response = await self._call_provider_with_retry(provider, prompt, max_tokens=10000, temperature=0.6)
+            response = await self._call_provider_with_retry(None, prompt, max_tokens=10000, temperature=0.6, umo=umo)
             if response is None:
                 logger.error("话题分析调用LLM失败: provider返回None（重试失败）")
                 return [], TokenUsage()
@@ -359,7 +349,7 @@ class LLMAnalyzer:
             logger.error(f"正则表达式提取失败: {e}")
             return []
 
-    async def analyze_user_titles(self, messages: List[Dict], user_analysis: Dict) -> Tuple[List[UserTitle], TokenUsage]:
+    async def analyze_user_titles(self, messages: List[Dict], user_analysis: Dict, umo: str = None) -> Tuple[List[UserTitle], TokenUsage]:
         """使用LLM分析用户称号"""
         try:
             # 准备用户数据
@@ -430,12 +420,7 @@ class LLMAnalyzer:
 """
 
             # 调用LLM
-            provider = self.context.get_using_provider()
-            if not provider:
-                logger.warning("未配置LLM提供商，跳过用户称号分析")
-                return [], TokenUsage()
-
-            response = await self._call_provider_with_retry(provider, prompt, max_tokens=1500, temperature=0.5)
+            response = await self._call_provider_with_retry(None, prompt, max_tokens=1500, temperature=0.5, umo=umo)
             if response is None:
                 logger.error("用户称号分析调用LLM失败: provider返回None（重试失败）")
                 return [], TokenUsage()
@@ -477,7 +462,7 @@ class LLMAnalyzer:
             logger.error(f"用户称号分析失败: {e}")
             return [], TokenUsage()
 
-    async def analyze_golden_quotes(self, messages: List[Dict]) -> Tuple[List[GoldenQuote], TokenUsage]:
+    async def analyze_golden_quotes(self, messages: List[Dict], umo: str = None) -> Tuple[List[GoldenQuote], TokenUsage]:
         """使用LLM分析群聊金句"""
         try:
             # 提取有趣的文本消息
@@ -538,12 +523,7 @@ class LLMAnalyzer:
 """
 
             # 调用LLM
-            provider = self.context.get_using_provider()
-            if not provider:
-                logger.warning("未配置LLM提供商，跳过金句分析")
-                return [], TokenUsage()
-
-            response = await self._call_provider_with_retry(provider, prompt, max_tokens=1500, temperature=0.7)
+            response = await self._call_provider_with_retry(None, prompt, max_tokens=1500, temperature=0.7, umo=umo)
             if response is None:
                 logger.error("金句分析调用LLM失败: provider返回None（重试失败）")
                 return [], TokenUsage()

src/scheduler/auto_scheduler.py

@@ -30,6 +30,21 @@ class AutoScheduler:
         """设置bot QQ号（保持向后兼容）"""
         self.bot_manager.set_bot_qq_id(bot_qq_id)
 
+    def _get_platform_id(self):
+        """获取平台ID"""
+        try:
+            if hasattr(self.bot_manager, '_context') and self.bot_manager._context:
+                context = self.bot_manager._context
+                if hasattr(context, 'platform_manager') and hasattr(context.platform_manager, 'platform_insts'):
+                    platforms = context.platform_manager.platform_insts
+                    for platform in platforms:
+                        if hasattr(platform, 'metadata') and hasattr(platform.metadata, 'id'):
+                            platform_id = platform.metadata.id
+                            return platform_id
+            return "aiocqhttp"  # 默认值
+        except Exception as e:
+            return "aiocqhttp"  # 默认值
+
     async def start_scheduler(self):
         """启动定时任务调度器"""
         if not self.config_manager.get_enable_auto_analysis():
@@ -144,8 +159,10 @@ class AutoScheduler:
 
             logger.info(f"群 {group_id} 获取到 {len(messages)} 条消息，开始分析")
 
-            # 进行分析
-            analysis_result = await self.analyzer.analyze_messages(messages, group_id)
+            # 进行分析 - 构造正确的 unified_msg_origin
+            platform_id = self._get_platform_id()
+            umo = f"{platform_id}:group:{group_id}" if platform_id else None
+            analysis_result = await self.analyzer.analyze_messages(messages, group_id, umo)
             if not analysis_result:
                 logger.error(f"群 {group_id} 分析失败")
                 return

src/utils/helpers.py

@@ -28,7 +28,7 @@ class MessageAnalyzer:
         else:
             await self.message_handler.set_bot_qq_id(bot_instance)
 
-    async def analyze_messages(self, messages: List[Dict], group_id: str) -> Dict:
+    async def analyze_messages(self, messages: List[Dict], group_id: str, unified_msg_origin: str = None) -> Dict:
         """完整的消息分析流程"""
         try:
             # 基础统计
@@ -45,20 +45,20 @@ class MessageAnalyzer:
 
             # 话题分析
             if self.config_manager.get_topic_analysis_enabled():
-                topics, topic_tokens = await self.llm_analyzer.analyze_topics(messages)
+                topics, topic_tokens = await self.llm_analyzer.analyze_topics(messages, umo=unified_msg_origin)
                 total_token_usage.prompt_tokens += topic_tokens.prompt_tokens
                 total_token_usage.completion_tokens += topic_tokens.completion_tokens
                 total_token_usage.total_tokens += topic_tokens.total_tokens
 
             # 用户称号分析
             if self.config_manager.get_user_title_analysis_enabled():
-                user_titles, title_tokens = await self.llm_analyzer.analyze_user_titles(messages, user_analysis)
+                user_titles, title_tokens = await self.llm_analyzer.analyze_user_titles(messages, user_analysis, umo=unified_msg_origin)
                 total_token_usage.prompt_tokens += title_tokens.prompt_tokens
                 total_token_usage.completion_tokens += title_tokens.completion_tokens
                 total_token_usage.total_tokens += title_tokens.total_tokens
 
             # 金句分析
-            golden_quotes, quote_tokens = await self.llm_analyzer.analyze_golden_quotes(messages)
+            golden_quotes, quote_tokens = await self.llm_analyzer.analyze_golden_quotes(messages, umo=unified_msg_origin)
             total_token_usage.prompt_tokens += quote_tokens.prompt_tokens
             total_token_usage.completion_tokens += quote_tokens.completion_tokens
             total_token_usage.total_tokens += quote_tokens.total_tokens