feat: 统一LLM错误处理并添加系统错误回复配置

在多个LLM提供者中移除try-catch块，将错误处理统一到connection.py的流处理层
添加system_error_response配置项，支持自定义系统错误时的回复内容
在意图识别和流处理中捕获异常时返回配置的错误回复，避免硬编码错误信息

Fixes #2075

main/xiaozhi-server/core/providers/intent/intent_llm/intent_llm.py

@@ -2,11 +2,14 @@ from typing import List, Dict
 from ..base import IntentProviderBase
 from plugins_func.functions.play_music import initialize_music_handler
 from config.logger import setup_logging
+from core.utils.util import get_system_error_response
 import re
 import json
 import hashlib
 import time
 
+
+
 TAG = __name__
 logger = setup_logging()
 
@@ -115,12 +118,16 @@ class IntentProvider(IntentProviderBase):
         return prompt
 
     def replyResult(self, text: str, original_text: str):
-        llm_result = self.llm.response_no_stream(
-            system_prompt=text,
-            user_prompt="请根据以上内容，像人类一样说话的口吻回复用户，要求简洁，请直接返回结果。用户现在说："
-            + original_text,
-        )
-        return llm_result
+        try:
+            llm_result = self.llm.response_no_stream(
+                system_prompt=text,
+                user_prompt="请根据以上内容，像人类一样说话的口吻回复用户，要求简洁，请直接返回结果。用户现在说："
+                + original_text,
+            )
+            return llm_result
+        except Exception as e:
+            logger.bind(tag=TAG).error(f"Error in generating reply result: {e}")
+            return get_system_error_response(self.config)
 
     async def detect_intent(self, conn, dialogue_history: List[Dict], text: str) -> str:
         if not self.llm:
@@ -194,9 +201,13 @@ class IntentProvider(IntentProviderBase):
         llm_start_time = time.time()
         logger.bind(tag=TAG).debug(f"开始LLM意图识别调用, 模型: {model_info}")
 
-        intent = self.llm.response_no_stream(
-            system_prompt=prompt_music, user_prompt=user_prompt
-        )
+        try:
+            intent = self.llm.response_no_stream(
+                system_prompt=prompt_music, user_prompt=user_prompt
+            )
+        except Exception as e:
+            logger.bind(tag=TAG).error(f"Error in intent detection LLM call: {e}")
+            return '{"function_call": {"name": "continue_chat"}}'
 
         # 记录LLM调用完成时间
         llm_time = time.time() - llm_start_time