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