fix: 修复 RAG 无限循环问题和导入错误

主要修复：
1. 修复 RAG 推理无限循环问题（大小写不匹配 + 缺少已检索结果检查）
2. 修复 intent_classifier.py 的绝对导入错误
3. 删除旧的 start.sh 脚本，添加新的启动脚本
4. 优化路由逻辑和状态管理

backend/app/agent/agent_service.py

@@ -7,14 +7,14 @@ import json
 import asyncio
 
 # 本地模块
-from app.main_graph.utils.main_graph_builder import build_react_main_graph
-from app.main_graph.tools.graph_tools import AVAILABLE_TOOLS, TOOLS_BY_NAME
-from app.main_graph.config import set_stream_writer
+from ..main_graph.utils.main_graph_builder import build_react_main_graph
+from ..main_graph.tools.graph_tools import AVAILABLE_TOOLS, TOOLS_BY_NAME
+from ..main_graph.config import set_stream_writer
 from ..model_services.chat_services import get_all_chat_services, LocalVLLMChatProvider
-from app.main_graph.utils.rag_initializer import init_rag_tool
-from app.core.intent_classifier import get_intent_classifier
-from app.logger import info, warning, error
-from app.main_graph.state import MainGraphState, CurrentAction
+from ..main_graph.utils.rag_initializer import init_rag_tool
+from ..core.intent_classifier import get_intent_classifier
+from ..logger import info, warning, error
+from ..main_graph.state import MainGraphState, CurrentAction
 
 
 class AIAgentService:
@@ -32,7 +32,7 @@ class AIAgentService:
 
     async def initialize(self):
         # 0. 初始化 Mem0 客户端
-        from app.memory.mem0_client import Mem0Client
+        from ..memory.mem0_client import Mem0Client
         # 创建一个临时的 LLM 用于 Mem0（用第一个可用的）
         chat_services = get_all_chat_services()
         temp_llm = None
@@ -49,7 +49,7 @@ class AIAgentService:
             self.tools.append(rag_tool)
             self.tools_by_name[rag_tool.name] = rag_tool
             # 关键：设置全局 RAG 工具，供 rag_nodes.py 使用
-            from app.main_graph.nodes.rag_nodes import set_global_rag_tool
+            from ..main_graph.nodes.rag_nodes import set_global_rag_tool
             set_global_rag_tool(rag_tool)
 
         # 2. 构建各模型的 Graph（使用新版 React 模式）
@@ -86,7 +86,7 @@ class AIAgentService:
             "metadata": {"user_id": user_id}
         }
         # 新版状态输入：传入完整的 MainGraphState，关键是 user_query
-        from app.main_graph.state import MainGraphState, CurrentAction
+        from ..main_graph.state import MainGraphState, CurrentAction
         input_state = {
             "user_query": message,
             "messages": [{"role": "user", "content": message}],

backend/app/core/intent.py

@@ -132,8 +132,17 @@ class ReactIntentReasoner:
         
         # 关键修改：不要在第一次 rag_retrieve 后就直接回答，允许再推理一次
         # 让推理逻辑有机会判断 RAG 结果好不好，要不要再检索或转 web search
-        rag_count = previous_actions.count("rag_retrieve")
+        previous_actions = context.get("previous_actions", [])
+        rag_count = previous_actions.count("RETRIEVE_RAG")  # 修复：大写
         web_search_count = previous_actions.count("web_search")
+        retrieved_docs = context.get("retrieved_docs", [])
+        
+        # 如果已经有检索文档了，直接回答
+        if retrieved_docs and len(retrieved_docs) > 0:
+            result.action = ReasoningAction.DIRECT_RESPONSE
+            result.confidence = 0.95
+            result.reasoning = "已获取检索文档，直接回答"
+            return result
         
         # 只有当 rag 或 web search 已经超过 1 次，或者已经有推理在 rag 之后，才直接回答
         if rag_count >= 2 or web_search_count >= 1:

backend/app/core/intent_classifier.py

@@ -6,7 +6,7 @@ from typing import Optional, Dict, Any
 import sys
 import os
 
-from backend.app.model_services.chat_services import get_small_llm_service
+from ..model_services.chat_services import get_small_llm_service
 
 
 class IntentType(Enum):

backend/app/main_graph/nodes/hybrid_router.py

@@ -8,10 +8,10 @@ from typing import Dict, Any, Optional, List
 from dataclasses import dataclass, field
 from datetime import datetime
 
-from app.main_graph.state import MainGraphState
-from app.logger import info, debug
-from app.model_services.chat_services import get_small_llm_service, get_chat_service
-from app.main_graph.nodes.rag_nodes import rag_retrieve_node
+from ..state import MainGraphState
+from ...logger import info, debug
+from ...model_services.chat_services import get_small_llm_service, get_chat_service
+from .rag_nodes import rag_retrieve_node
 
 
 # ========== 核心数据类型 ==========
@@ -367,8 +367,8 @@ async def fast_rag_node(state: MainGraphState, config: Optional[Dict[str, Any]]
             debug(f"[Fast RAG] 发送事件失败: {e}")
     
     try:
-        # 先尝试 RAG 检索
-        state = rag_retrieve_node(state, config)
+        # 先尝试 RAG 检索 - 注意：rag_retrieve_node 是异步函数，需要 await
+        state = await rag_retrieve_node(state, config)
         
         # 检查检索结果
         rag_docs = getattr(state, "rag_docs", [])

backend/app/main_graph/nodes/react_nodes.py

@@ -364,11 +364,15 @@ def route_by_reasoning(state: MainGraphState) -> str:
     if "subgraph_completed" in previous_actions or state.final_result:
         return "llm_call"
     
-    # 关键修复：如果已经执行过 rag_retrieve 并且又执行过推理，直接去 LLM_CALL
-    # 这样的流程：推理1 → RAG → 推理2（判断 RAG 结果） → LLM_CALL
-    rag_count = previous_actions.count("rag_retrieve")
-    if rag_count >= 1 and len(previous_actions) >= rag_count + 1:
-        info(f"[route_by_reasoning] 已完成 RAG 检索和结果判断，直接去 llm_call")
+    # 关键修复：检测 RAG 重复循环 - 如果发现"RETRIEVE_RAG"出现超过1次，直接去 LLM
+    rag_count = previous_actions.count("RETRIEVE_RAG")
+    if rag_count >= 2:
+        info(f"[route_by_reasoning] 检测到 RAG 重复循环（{rag_count}次），直接去 llm_call")
+        return "llm_call"
+    
+    # 关键修复：如果已经有 rag_docs 或 rag_context，说明已经检索过了，直接去 LLM
+    if (state.rag_docs and len(state.rag_docs) > 0) or (state.rag_context and len(state.rag_context) > 0):
+        info(f"[route_by_reasoning] 检测到已存在 RAG 检索结果，直接去 llm_call")
         return "llm_call"
     
     # 关键修复：限制最多 3 次推理，避免无限循环

backend/app/main_graph/utils/main_graph_builder.py

@@ -2,19 +2,19 @@
 整合后的完整主图构建器 - 所有节点都直接操作 MainGraphState
 """
 
-from app.main_graph.graph import StateGraph, START, END
+from ..graph import StateGraph, START, END
 from typing import Dict, Any, Optional
 from langchain_core.runnables.config import RunnableConfig
 
-from app.main_graph.state import MainGraphState
-from app.main_graph.nodes.react_nodes import (
+from ..state import MainGraphState
+from ..nodes.react_nodes import (
     init_state_node,
     react_reason_node,
     web_search_node,
     error_handling_node,
     route_by_reasoning
 )
-from app.main_graph.nodes.hybrid_router import (
+from ..nodes.hybrid_router import (
     hybrid_router_node,
     fast_chitchat_node,
     fast_rag_node,
@@ -22,17 +22,17 @@ from app.main_graph.nodes.hybrid_router import (
     route_from_hybrid_decision,
     check_fast_path_success
 )
-from app.main_graph.nodes.llm_call import create_llm_call_node
-from app.main_graph.nodes.rag_nodes import rag_retrieve_node
-from app.main_graph.nodes.retrieve_memory import create_retrieve_memory_node
-from app.main_graph.nodes.memory_trigger import memory_trigger_node, set_mem0_client
-from app.main_graph.nodes.summarize import create_summarize_node
-from app.main_graph.nodes.finalize import finalize_node
-from app.subgraphs.contact import build_contact_subgraph
-from app.subgraphs.dictionary import build_dictionary_subgraph
-from app.subgraphs.news_analysis import build_news_analysis_subgraph
-from app.memory.mem0_client import Mem0Client
-from app.logger import info, debug
+from ..nodes.llm_call import create_llm_call_node
+from ..nodes.rag_nodes import rag_retrieve_node
+from ..nodes.retrieve_memory import create_retrieve_memory_node
+from ..nodes.memory_trigger import memory_trigger_node, set_mem0_client
+from ..nodes.summarize import create_summarize_node
+from ..nodes.finalize import finalize_node
+from ...subgraphs.contact import build_contact_subgraph
+from ...subgraphs.dictionary import build_dictionary_subgraph
+from ...subgraphs.news_analysis import build_news_analysis_subgraph
+from ...memory.mem0_client import Mem0Client
+from ...logger import info, debug
 
 
 # ========== 检查是否需要总结 ==========
@@ -140,7 +140,7 @@ def wrap_subgraph_for_error_handling(subgraph, name: str):
             
         except Exception as e:
             # 捕获子图错误，传递给主图
-            from app.main_graph.state import ErrorRecord, ErrorSeverity
+            from ..state import ErrorRecord, ErrorSeverity
             from datetime import datetime
             
             error_record = ErrorRecord(