Completely refactor the LLM integration method to easily replace the LLM used by each module and optimize the retransmission mechanism.

QueryEngine/nodes/base_node.py

@@ -5,14 +5,14 @@
 
 from abc import ABC, abstractmethod
 from typing import Any, Dict, Optional
-from ..llms.base import BaseLLM
+from ..llms.base import LLMClient
 from ..state.state import State
 
 
 class BaseNode(ABC):
     """节点基类"""
     
-    def __init__(self, llm_client: BaseLLM, node_name: str = ""):
+    def __init__(self, llm_client: LLMClient, node_name: str = ""):
         """
         初始化节点
         

QueryEngine/nodes/formatting_node.py

@@ -67,11 +67,10 @@ class ReportFormattingNode(BaseNode):
             
             self.log_info("正在格式化最终报告")
             
-            # 调用LLM，传递更大的max_tokens以支持长文本报告
+            # 调用LLM生成Markdown格式
             response = self.llm_client.invoke(
-                SYSTEM_PROMPT_REPORT_FORMATTING, 
-                message, 
-                max_tokens=8192  # 支持一万字的报告输出
+                SYSTEM_PROMPT_REPORT_FORMATTING,
+                message,
             )
             
             # 处理响应

QueryEngine/nodes/summary_node.py

@@ -98,11 +98,10 @@ class FirstSummaryNode(StateMutationNode):
             
             self.log_info("正在生成首次段落总结")
             
-            # 调用LLM，增加max_tokens以支持更长的总结
+            # 调用LLM生成总结
             response = self.llm_client.invoke(
-                SYSTEM_PROMPT_FIRST_SUMMARY, 
+                SYSTEM_PROMPT_FIRST_SUMMARY,
                 message,
-                max_tokens=8192  # 支持更长的总结内容
             )
             
             # 处理响应
@@ -267,11 +266,10 @@ class ReflectionSummaryNode(StateMutationNode):
             
             self.log_info("正在生成反思总结")
             
-            # 调用LLM，增加max_tokens以支持更长的总结
+            # 调用LLM生成总结
             response = self.llm_client.invoke(
-                SYSTEM_PROMPT_REFLECTION_SUMMARY, 
+                SYSTEM_PROMPT_REFLECTION_SUMMARY,
                 message,
-                max_tokens=8192  # 支持更长的总结内容
             )
             
             # 处理响应