feat: 新增 react_reason 循环思考过程的流式显示
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构建并部署 AI Agent 服务 / deploy (push) Successful in 5m38s
- 修改 react_nodes.py,在推理时保存推理过程到状态 - 修改 agent_service.py,检测并发送推理过程事件到前端 - 修改 chat_area.py,接收并显示推理过程 - 修改 useChat.ts,添加对推理过程事件的支持
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@@ -26,11 +26,12 @@ from app.main_graph.utils.retry_utils import (
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RetryConfig,
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SUBGRAPH_RETRY_CONFIG
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)
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from app.logger import info
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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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def react_reason_node(state: MainGraphState, config: Optional[Dict[str, Any]] = None) -> MainGraphState:
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"""
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React 模式推理节点:判断下一步做什么
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@@ -38,6 +39,22 @@ def react_reason_node(state: MainGraphState) -> MainGraphState:
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"""
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state.current_phase = "react_reasoning"
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state.reasoning_step += 1
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# 发送推理开始事件
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if config:
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try:
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from langchain_core.runnables.config import RunnableConfig
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# 尝试获取回调管理器并发送自定义事件
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callbacks = config.get("callbacks")
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if callbacks:
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from langchain_core.callbacks.manager import adispatch_custom_event
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# 注意:这是异步操作,我们需要特殊处理
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# 这里我们使用自定义流式写入器(如果存在)
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pass
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except Exception as e:
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info(f"[react_reason] 无法发送回调事件: {e}")
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info(f"[react_reason] 第 {state.reasoning_step} 次推理开始")
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# 检查是否超过最大步数
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if state.reasoning_step > state.max_steps:
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@@ -61,6 +78,10 @@ def react_reason_node(state: MainGraphState) -> MainGraphState:
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# 使用 intent.py 进行推理
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# 注意:这里使用同步版本,内部会根据情况处理
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result: ReasoningResult = react_reason(state.user_query, context)
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info(f"[react_reason] 推理结果: action={result.action.name}, confidence={result.confidence}")
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if result.reasoning:
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info(f"[react_reason] 推理过程: {result.reasoning}")
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# 记录推理历史
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state.reasoning_history.append({
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@@ -83,6 +104,16 @@ def react_reason_node(state: MainGraphState) -> MainGraphState:
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# 确定下一步动作
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state.last_action = result.action.name
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# 发送推理完成事件(通过状态更新,agent_service 会处理)
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# 我们在状态中保存推理内容,以便 agent_service 可以通过 state_update 事件发送
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state.debug_info["latest_reasoning"] = {
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"step": state.reasoning_step,
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"action": result.action.name,
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"confidence": result.confidence,
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"reasoning": result.reasoning,
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"sent": False # 标记是否已发送到前端
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}
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return state
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