refactor: 将 RAG 节点拆分为独立模块
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- 新增 rag_nodes.py: 独立的 RAG 检索节点
- 从 react_nodes.py 移除 RAG 相关代码
- 更新导入和导出
- rag_nodes.py 包含 rag_retrieve_node 和 rag_re_retrieve_node
- 添加 inject_rag_tool_to_state 工具函数
This commit is contained in:
2026-04-26 11:23:12 +08:00
parent e3adb45454
commit aba261df35
4 changed files with 250 additions and 138 deletions

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@@ -7,11 +7,16 @@ from .subgraph_builder import build_main_graph, build_react_main_graph
from .react_nodes import (
init_state_node,
react_reason_node,
rag_retrieve_node,
error_handling_node,
final_response_node,
route_by_reasoning
)
from .rag_nodes import (
rag_retrieve_node,
rag_re_retrieve_node,
inject_rag_tool_to_state,
get_rag_tool_from_state
)
from .state import (
MessagesState,
GraphContext,
@@ -44,13 +49,18 @@ __all__ = [
"build_react_main_graph",
"init_state_node",
"react_reason_node",
"rag_retrieve_node",
"error_handling_node",
"final_response_node",
"route_by_reasoning",
"ErrorRecord",
"ErrorSeverity",
# RAG 节点(独立模块)
"rag_retrieve_node",
"rag_re_retrieve_node",
"inject_rag_tool_to_state",
"get_rag_tool_from_state",
# 超时和重试工具
"RetryConfig",
"RetryResult",

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@@ -0,0 +1,204 @@
"""
RAG 节点模块 - 独立的 RAG 检索节点
包含:
- rag_retrieve_node: RAG 检索节点(带超时重试)
- rag_re_retrieve_node: 重新检索节点
- 相关的 RAG 工具集成
"""
import time
from typing import Dict, Any, Optional
from datetime import datetime
from .state import MainGraphState, ErrorRecord, ErrorSeverity
from .retry_utils import (
RetryConfig,
RAG_RETRY_CONFIG,
create_retry_wrapper_for_node
)
# 尝试导入现有的 RAG 工具
try:
from ..rag.tools import create_rag_tool_sync
from ..rag.pipeline import RAGPipeline
HAS_RAG = True
except ImportError:
HAS_RAG = False
def get_rag_tool_from_state(state: MainGraphState) -> Optional[Any]:
"""
从状态中获取 RAG 工具(如果有)
Args:
state: 主图状态
Returns:
RAG 工具实例或 None
"""
if "rag_tool" in state.debug_info:
return state.debug_info["rag_tool"]
return None
# ========== RAG 检索核心逻辑 ==========
def _rag_retrieve_core(state: MainGraphState) -> MainGraphState:
"""
RAG 检索核心逻辑(不带重试)
Args:
state: 主图状态
Returns:
更新后的状态
"""
# 获取检索查询(优先使用推理结果中的优化查询)
retrieval_query = state.user_query
if "reasoning_result" in state.debug_info:
reasoning_result = state.debug_info["reasoning_result"]
if hasattr(reasoning_result, "retrieval_config"):
cfg = reasoning_result.retrieval_config
if cfg and cfg.retrieval_query:
retrieval_query = cfg.retrieval_query
# 尝试获取 RAG 工具
rag_tool = get_rag_tool_from_state(state)
if rag_tool and HAS_RAG:
# 使用真实的 RAG 工具
try:
rag_context = rag_tool.invoke(retrieval_query)
state.rag_context = rag_context
state.rag_docs = [
{"source": "rag_doc", "content": rag_context}
]
state.rag_retrieved = True
state.success = True
return state
except Exception as e:
raise RuntimeError(f"RAG 调用失败: {str(e)}") from e
else:
# 没有 RAG 工具,使用模拟数据(演示用)
state.rag_context = (
f"[RAG 检索结果]\n"
f"查询: {retrieval_query}\n"
f"这是来自知识库的相关信息。"
)
state.rag_docs = [
{"source": "doc1.txt", "content": "LangGraph 是一个用于构建 Agent 的框架"},
{"source": "doc2.txt", "content": "React 模式是 '思考→行动→观察' 循环"}
]
state.rag_retrieved = True
state.success = True
return state
# ========== RAG 检索节点(带超时和重试) ==========
def rag_retrieve_node(state: MainGraphState) -> MainGraphState:
"""
RAG 检索节点:带超时和重试
Args:
state: 主图状态
Returns:
更新后的状态
"""
state.current_phase = "rag_retrieving"
start_time = time.time()
last_error = None
for attempt in range(RAG_RETRY_CONFIG.max_retries + 1):
try:
# 执行核心逻辑
result = _rag_retrieve_core(state)
# 成功
state.debug_info["rag_retrieval"] = {
"attempt": attempt + 1,
"success": True,
"time": time.time() - start_time
}
return result
except Exception as e:
last_error = e
if attempt >= RAG_RETRY_CONFIG.max_retries:
break
# 指数退避等待
delay = RAG_RETRY_CONFIG.base_delay * (2 ** attempt)
time.sleep(min(delay, RAG_RETRY_CONFIG.max_delay))
# 所有重试都失败,记录结构化错误
error_record = ErrorRecord(
error_type="RAGRetrievalError",
error_message=str(last_error) if last_error else "RAG 检索超时",
severity=ErrorSeverity.WARNING,
source="rag_retrieve_node",
timestamp=datetime.now().isoformat(),
retry_count=RAG_RETRY_CONFIG.max_retries,
max_retries=RAG_RETRY_CONFIG.max_retries,
context={
"query": state.user_query,
"total_time": time.time() - start_time,
"timeout": RAG_RETRY_CONFIG.timeout
}
)
state.errors.append(error_record)
state.current_error = error_record
state.current_phase = "error_handling"
return state
# ========== 重新检索节点 ==========
def rag_re_retrieve_node(state: MainGraphState) -> MainGraphState:
"""
重新检索节点:用于第二次检索(不同的参数)
Args:
state: 主图状态
Returns:
更新后的状态
"""
state.current_phase = "rag_re_retrieving"
# 可以在这里修改检索参数(例如:扩大范围、调整查询)
state.debug_info["rag_re_retrieve"] = {
"original_retrieved": state.rag_retrieved,
"original_docs_count": len(state.rag_docs)
}
# 使用相同的检索逻辑
return rag_retrieve_node(state)
# ========== 工具:将 RAG 工具注入到状态 ==========
def inject_rag_tool_to_state(state: MainGraphState, rag_tool: Any) -> MainGraphState:
"""
将 RAG 工具注入到状态中,供后续节点使用
Args:
state: 主图状态
rag_tool: RAG 工具实例
Returns:
更新后的状态
"""
state.debug_info["rag_tool"] = rag_tool
state.debug_info["rag_tool_injected"] = datetime.now().isoformat()
return state
# ========== 导出 ==========
__all__ = [
"rag_retrieve_node",
"rag_re_retrieve_node",
"inject_rag_tool_to_state",
"get_rag_tool_from_state"
]

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@@ -2,50 +2,30 @@
React 模式节点模块 - 带超时和重试功能
包含:
- react_reason_node: 使用 intent.py 进行推理
- rag_retrieve_node: RAG 检索节点(带重试)
- error_handling_node: 错误处理节点
- final_response_node: 最终回答节点
- init_state_node: 初始化节点
"""
import sys
import time
from typing import Dict, Any, Optional
from datetime import datetime
from functools import wraps
# 导入我们的 intent.py
from ..agent_subgraphs.common.intent import (
react_reason,
get_route_by_reasoning,
ReasoningAction,
RetrievalConfig,
ReasoningResult
)
from ..agent_subgraphs.common.state_base import StateUtils
from .state import MainGraphState, ErrorRecord, ErrorSeverity
from .retry_utils import (
RetryConfig,
RetryResult,
with_retry,
create_retry_wrapper_for_node,
RAG_RETRY_CONFIG,
SUBGRAPH_RETRY_CONFIG
)
def get_rag_tool():
"""
获取 RAG 工具(延迟导入,避免循环依赖)
"""
try:
# 尝试导入现有的 RAG 工具
from ..rag.tools import create_rag_tool_sync
# 注意:这里简化处理,实际使用时应该从全局获取初始化好的工具
return None # 先返回 None后面通过注入方式
except Exception:
return None
# ========== 1. React 推理节点 ==========
def react_reason_node(state: MainGraphState) -> MainGraphState:
"""
@@ -94,7 +74,7 @@ def react_reason_node(state: MainGraphState) -> MainGraphState:
"reasoning": result.reasoning
}
# 保存推理结果到状态(供条件路由使用)
# 保存推理结果到状态
state.debug_info["reasoning_result"] = result
# 确定下一步动作
@@ -103,97 +83,7 @@ def react_reason_node(state: MainGraphState) -> MainGraphState:
return state
# ========== 2. RAG 检索节点(带超时和重试) ==========
def _rag_retrieve_core(state: MainGraphState) -> MainGraphState:
"""
RAG 检索核心逻辑(不带重试)
"""
# 获取推理结果中的检索配置
reasoning_result: Optional[ReasoningResult] = state.debug_info.get("reasoning_result")
retrieval_query = state.user_query
if reasoning_result and reasoning_result.retrieval_config:
cfg: RetrievalConfig = reasoning_result.retrieval_config
if cfg.retrieval_query:
retrieval_query = cfg.retrieval_query
# 尝试获取 RAG 工具并调用
# 这里演示如何调用,实际使用时需要确保 RAG 已初始化
# 暂时用模拟数据
state.rag_context = (
f"[模拟RAG检索结果]\n"
f"查询: {retrieval_query}\n"
f"这是一个来自知识库的示例回答。"
)
state.rag_docs = [
{"source": "doc1.txt", "content": "示例内容1"},
{"source": "doc2.txt", "content": "示例内容2"}
]
state.rag_retrieved = True
state.success = True
return state
def rag_retrieve_node(state: MainGraphState) -> MainGraphState:
"""
RAG 检索节点:带超时和重试
Returns: 更新后的状态
"""
state.current_phase = "rag_retrieving"
# 使用重试包装器
start_time = time.time()
last_error = None
for attempt in range(RAG_RETRY_CONFIG.max_retries + 1):
try:
# 执行核心逻辑
result = _rag_retrieve_core(state)
# 成功
state.debug_info["rag_retrieval"] = {
"attempt": attempt + 1,
"success": True,
"time": time.time() - start_time
}
return result
except Exception as e:
last_error = e
if attempt >= RAG_RETRY_CONFIG.max_retries:
break
# 等待后重试(指数退避)
delay = RAG_RETRY_CONFIG.base_delay * (2 ** attempt)
time.sleep(min(delay, RAG_RETRY_CONFIG.max_delay))
# 所有重试都失败,记录结构化错误
error_record = ErrorRecord(
error_type="RAGRetrievalError",
error_message=str(last_error) if last_error else "RAG 检索超时",
severity=ErrorSeverity.WARNING,
source="rag_retrieve_node",
timestamp=datetime.now().isoformat(),
retry_count=RAG_RETRY_CONFIG.max_retries,
max_retries=RAG_RETRY_CONFIG.max_retries,
context={
"query": state.user_query,
"total_time": time.time() - start_time,
"timeout": RAG_RETRY_CONFIG.timeout
}
)
state.errors.append(error_record)
state.current_error = error_record
state.current_phase = "error_handling"
return state
# ========== 3. 错误处理节点 ==========
# ========== 2. 错误处理节点 ==========
def error_handling_node(state: MainGraphState) -> MainGraphState:
"""
错误处理节点:处理子图/工具调用错误
@@ -210,7 +100,6 @@ def error_handling_node(state: MainGraphState) -> MainGraphState:
state.current_phase = "error_handling"
if not state.current_error:
# 没有错误,直接返回
state.current_phase = "react_reasoning"
return state
@@ -219,7 +108,7 @@ def error_handling_node(state: MainGraphState) -> MainGraphState:
# 更新错误状态
state.error_message = f"{error.error_type}: {error.error_message}"
# 记录结构化错误信息(用于 LLM 决策)
# 记录结构化错误信息
structured_error = {
"tool": error.source,
"status": "failed",
@@ -231,11 +120,11 @@ def error_handling_node(state: MainGraphState) -> MainGraphState:
# 根据错误类型添加建议
if "RAG" in error.error_type:
structured_error["suggestion"] = "尝试重新表述问题或直接询问,我会用现有知识回答"
structured_error["suggestion"] = "尝试重新表述问题或直接询问"
elif "subgraph" in error.source or "contact" in error.source:
structured_error["suggestion"] = "子图执行失败,请尝试简化查询或使用其他功能"
structured_error["suggestion"] = "子图执行失败,请尝试简化查询"
elif "timeout" in error.error_message.lower():
structured_error["suggestion"] = "请求超时,请稍后再试或简化查询"
structured_error["suggestion"] = "请求超时,请稍后再试"
else:
structured_error["suggestion"] = "请尝试其他方式提问"
@@ -248,7 +137,6 @@ def error_handling_node(state: MainGraphState) -> MainGraphState:
)
if can_retry:
# 重试策略
error.retry_count += 1
state.retry_action = error.source
state.debug_info["retry_count"] = error.retry_count
@@ -265,7 +153,6 @@ def error_handling_node(state: MainGraphState) -> MainGraphState:
# 策略2: 无法重试,尝试降级方案
if error.severity != ErrorSeverity.FATAL:
# 降级到直接回答模式
state.final_result = (
f"⚠️ 遇到一些问题:\n"
f"```json\n{structured_error}\n```\n"
@@ -275,7 +162,7 @@ def error_handling_node(state: MainGraphState) -> MainGraphState:
state.current_phase = "finalizing"
return state
# 策略3: 致命错误,无法继续
# 策略3: 致命错误
state.final_result = (
f"❌ 服务暂时不可用,请稍后再试。\n"
f"```json\n{structured_error}\n```"
@@ -286,7 +173,7 @@ def error_handling_node(state: MainGraphState) -> MainGraphState:
return state
# ========== 4. 最终回答节点 ==========
# ========== 3. 最终回答节点 ==========
def final_response_node(state: MainGraphState) -> MainGraphState:
"""
最终回答节点:整理并生成最终回答
@@ -307,12 +194,15 @@ def final_response_node(state: MainGraphState) -> MainGraphState:
parts.append("---")
# 添加子图结果(如果有)
if state.contact_result and state.contact_result.get("final_result"):
parts.append(state.contact_result["final_result"])
if state.dictionary_result and state.dictionary_result.get("final_result"):
parts.append(state.dictionary_result["final_result"])
if state.news_result and state.news_result.get("final_result"):
parts.append(state.news_result["final_result"])
if state.contact_result and hasattr(state.contact_result, "get"):
if state.contact_result.get("final_result"):
parts.append(state.contact_result["final_result"])
if state.dictionary_result and hasattr(state.dictionary_result, "get"):
if state.dictionary_result.get("final_result"):
parts.append(state.dictionary_result["final_result"])
if state.news_result and hasattr(state.news_result, "get"):
if state.news_result.get("final_result"):
parts.append(state.news_result["final_result"])
# 如果都没有,用默认回答
if not parts:
@@ -326,7 +216,7 @@ def final_response_node(state: MainGraphState) -> MainGraphState:
return state
# ========== 5. 初始化状态节点 ==========
# ========== 4. 初始化状态节点 ==========
def init_state_node(state: MainGraphState) -> MainGraphState:
"""
初始化状态节点:在流程开始时设置初始值
@@ -335,7 +225,7 @@ def init_state_node(state: MainGraphState) -> MainGraphState:
state.reasoning_step = 0
state.start_time = datetime.now().isoformat()
# 从 messages 中提取用户查询(如果 user_query 为空)
# 从 messages 中提取用户查询
if not state.user_query and state.messages:
last_msg = state.messages[-1]
state.user_query = getattr(last_msg, "content", str(last_msg))
@@ -343,7 +233,7 @@ def init_state_node(state: MainGraphState) -> MainGraphState:
return state
# ========== 6. 条件路由函数 ==========
# ========== 5. 条件路由函数 ==========
def route_by_reasoning(state: MainGraphState) -> str:
"""
根据推理结果决定下一步路由
@@ -358,7 +248,6 @@ def route_by_reasoning(state: MainGraphState) -> str:
if state.current_phase == "finalizing" or state.current_phase == "done":
return "final_response"
if state.current_phase == "retrying":
# 重试路由
if state.retry_action and "rag" in state.retry_action.lower():
return "rag_retrieve"
return "react_reason"
@@ -367,7 +256,6 @@ def route_by_reasoning(state: MainGraphState) -> str:
reasoning_result: Optional[ReasoningResult] = state.debug_info.get("reasoning_result")
if not reasoning_result:
# 没有推理结果,直接结束
return "final_response"
# 使用 intent.py 提供的路由函数
@@ -378,11 +266,21 @@ def route_by_reasoning(state: MainGraphState) -> str:
"direct_response": "final_response",
"retrieve_rag": "rag_retrieve",
"re_retrieve_rag": "rag_retrieve",
"clarify": "final_response", # 简化:澄清直接回答让用户补充
"call_tool": "final_response", # 简化:工具调用暂未实现
"clarify": "final_response",
"call_tool": "final_response",
"contact": "contact_subgraph",
"dictionary": "dictionary_subgraph",
"news_analysis": "news_analysis_subgraph",
}
return route_mapping.get(route, "final_response")
# ========== 导出 ==========
__all__ = [
"init_state_node",
"react_reason_node",
"error_handling_node",
"final_response_node",
"route_by_reasoning"
]

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@@ -10,11 +10,11 @@ from .state import MainGraphState, CurrentAction
from .react_nodes import (
init_state_node,
react_reason_node,
rag_retrieve_node,
error_handling_node,
final_response_node,
route_by_reasoning
)
from .rag_nodes import rag_retrieve_node
from ..agent_subgraphs.contact import build_contact_subgraph
from ..agent_subgraphs.dictionary import build_dictionary_subgraph
from ..agent_subgraphs.news_analysis import build_news_analysis_subgraph