diff --git a/src/chat/utils/utils_video.py b/src/chat/utils/utils_video.py
index 1e186f058..c78acd89a 100644
--- a/src/chat/utils/utils_video.py
+++ b/src/chat/utils/utils_video.py
@@ -747,7 +747,7 @@ class VideoAnalyzer:
                         os.unlink(temp_path)
 
                 # 保存分析结果到数据库（仅保存成功的结果）
-                if success:
+                if success and not result.startswith("❌"):
                     metadata = {"filename": filename, "file_size": len(video_bytes), "analysis_timestamp": time.time()}
                     self._store_video_result(video_hash=video_hash, description=result, metadata=metadata)
                     logger.info("✅ 分析结果已保存到数据库")
diff --git a/src/plugins/built_in/core_actions/emoji.py b/src/plugins/built_in/core_actions/emoji.py
index fe03f4478..69a236159 100644
--- a/src/plugins/built_in/core_actions/emoji.py
+++ b/src/plugins/built_in/core_actions/emoji.py
@@ -152,10 +152,10 @@ class EmojiAction(BaseAction):
 
                     # 调用LLM
                     models = llm_api.get_available_models()
-                    chat_model_config = models.get("planner")
+                    chat_model_config = models.get("utils")
                     if not chat_model_config:
-                        logger.error(f"{self.log_prefix} 未找到'planner'模型配置，无法调用LLM")
-                        return False, "未找到'planner'模型配置"
+                        logger.error(f"{self.log_prefix} 未找到'utils'模型配置，无法调用LLM")
+                        return False, "未找到'utils'模型配置"
 
                     success, chosen_emotion, _, _ = await llm_api.generate_with_model(
                         prompt, model_config=chat_model_config, request_type="emoji"
@@ -212,10 +212,10 @@ class EmojiAction(BaseAction):
 
                 # 调用LLM
                 models = llm_api.get_available_models()
-                chat_model_config = models.get("planner")
+                chat_model_config = models.get("utils")
                 if not chat_model_config:
-                    logger.error(f"{self.log_prefix} 未找到'planner'模型配置，无法调用LLM")
-                    return False, "未找到'planner'模型配置"
+                    logger.error(f"{self.log_prefix} 未找到'utils'模型配置，无法调用LLM")
+                    return False, "未找到'utils'模型配置"
 
                 success, chosen_description, _, _ = await llm_api.generate_with_model(
                     prompt, model_config=chat_model_config, request_type="emoji"