添加调试日志，排查Task was destroyed问题
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构建并部署 AI Agent 服务 / deploy (push) Successful in 6m41s
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@@ -151,123 +151,140 @@ class AIAgentService:
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# ========================================
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# ========================================
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# ========== React 循环路径 ==========
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# ========== React 循环路径 ==========
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info(f"🚀 开始执行 React 图，模型: {model_name}")
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current_node = None
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current_node = None
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tool_calls_in_progress = {}
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tool_calls_in_progress = {}
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async for chunk in graph.astream(
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try:
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input_state,
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info(f"📡 开始调用 graph.astream()...")
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config=config,
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chunk_count = 0
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stream_mode=["messages", "updates", "custom"],
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async for chunk in graph.astream(
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version="v2",
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input_state,
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subgraphs=True
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config=config,
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):
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stream_mode=["messages", "updates", "custom"],
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chunk_type = chunk["type"]
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version="v2",
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processed_event = {}
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subgraphs=True
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):
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chunk_count += 1
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chunk_type = chunk["type"]
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info(f"📦 收到第 {chunk_count} 个chunk, type: {chunk_type}")
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processed_event = {}
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if chunk_type == "messages":
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if chunk_type == "messages":
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message_chunk, metadata = chunk["data"]
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message_chunk, metadata = chunk["data"]
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node_name = metadata.get("langgraph_node", "unknown")
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node_name = metadata.get("langgraph_node", "unknown")
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info(f"📨 处理消息chunk, node: {node_name}")
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# 检测节点变化，发送节点开始事件
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# 检测节点变化，发送节点开始事件
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if node_name != current_node:
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if node_name != current_node:
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if current_node:
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if current_node:
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yield {
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"type": "node_end",
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"node": current_node
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}
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yield {
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"type": "node_start",
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"node": node_name
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}
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current_node = node_name
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# 处理消息内容
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token_content = getattr(message_chunk, 'content', str(message_chunk))
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reasoning_token = ""
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if hasattr(message_chunk, 'additional_kwargs'):
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reasoning_token = message_chunk.additional_kwargs.get("reasoning_content", "")
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# 处理思考过程
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if reasoning_token:
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processed_event = {
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"type": "llm_token",
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"node": node_name,
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"reasoning_token": reasoning_token
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}
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# 处理工具调用
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elif hasattr(message_chunk, 'tool_calls') and message_chunk.tool_calls:
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for tool_call in message_chunk.tool_calls:
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tool_call_id = tool_call.get("id", "")
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tool_name = tool_call.get("name", "")
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tool_args = tool_call.get("args", {})
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# 记录工具调用开始
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if tool_call_id not in tool_calls_in_progress:
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tool_calls_in_progress[tool_call_id] = {
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"name": tool_name,
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"args": tool_args
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}
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yield {
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yield {
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"type": "tool_call_start",
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"type": "node_end",
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"tool": tool_name,
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"node": current_node
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"args": tool_args,
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"id": tool_call_id
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}
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}
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# 处理普通 token
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yield {
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elif token_content:
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"type": "node_start",
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processed_event = {
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"node": node_name
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"type": "llm_token",
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}
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"node": node_name,
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current_node = node_name
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"token": token_content,
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"reasoning_token": reasoning_token
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}
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elif chunk_type == "updates":
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# 处理消息内容
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updates_data = chunk["data"]
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token_content = getattr(message_chunk, 'content', str(message_chunk))
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serialized_data = self._serialize_value(updates_data)
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reasoning_token = ""
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if hasattr(message_chunk, 'additional_kwargs'):
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reasoning_token = message_chunk.additional_kwargs.get("reasoning_content", "")
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# 检查是否有人工审核请求
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# 处理思考过程
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if "review_pending" in serialized_data and serialized_data["review_pending"]:
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if reasoning_token:
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review_id = serialized_data.get("review_id", "")
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processed_event = {
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content_to_review = serialized_data.get("content_to_review", "")
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"type": "llm_token",
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yield {
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"node": node_name,
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"type": "human_review_request",
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"reasoning_token": reasoning_token
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"review_id": review_id,
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}
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"content": content_to_review
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# 处理工具调用
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}
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elif hasattr(message_chunk, 'tool_calls') and message_chunk.tool_calls:
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for tool_call in message_chunk.tool_calls:
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tool_call_id = tool_call.get("id", "")
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tool_name = tool_call.get("name", "")
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tool_args = tool_call.get("args", {})
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# 检查是否有工具结果
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# 记录工具调用开始
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if "messages" in serialized_data:
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if tool_call_id not in tool_calls_in_progress:
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for msg in serialized_data["messages"]:
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tool_calls_in_progress[tool_call_id] = {
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# 检测工具结果消息
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"name": tool_name,
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if msg.get("role") == "tool":
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"args": tool_args
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tool_call_id = msg.get("tool_call_id", "")
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tool_name = msg.get("name", "")
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tool_output = msg.get("content", "")
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if tool_call_id in tool_calls_in_progress:
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yield {
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"type": "tool_call_end",
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"tool": tool_name,
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"id": tool_call_id,
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"result": tool_output
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}
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}
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del tool_calls_in_progress[tool_call_id]
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yield {
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"type": "tool_call_start",
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"tool": tool_name,
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"args": tool_args,
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"id": tool_call_id
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}
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# 处理普通 token
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elif token_content:
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processed_event = {
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"type": "llm_token",
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"node": node_name,
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"token": token_content,
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"reasoning_token": reasoning_token
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}
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processed_event = {
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elif chunk_type == "updates":
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"type": "state_update",
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info(f"🔄 处理updates chunk")
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"data": serialized_data
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updates_data = chunk["data"]
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}
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serialized_data = self._serialize_value(updates_data)
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elif chunk_type == "custom":
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# 检查是否有人工审核请求
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serialized_data = self._serialize_value(chunk["data"])
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if "review_pending" in serialized_data and serialized_data["review_pending"]:
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processed_event = {
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review_id = serialized_data.get("review_id", "")
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"type": "custom",
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content_to_review = serialized_data.get("content_to_review", "")
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"data": serialized_data
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yield {
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}
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"type": "human_review_request",
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"review_id": review_id,
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"content": content_to_review
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}
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if processed_event:
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# 检查是否有工具结果
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yield processed_event
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if "messages" in serialized_data:
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for msg in serialized_data["messages"]:
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# 检测工具结果消息
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if msg.get("role") == "tool":
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tool_call_id = msg.get("tool_call_id", "")
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tool_name = msg.get("name", "")
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tool_output = msg.get("content", "")
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if tool_call_id in tool_calls_in_progress:
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yield {
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"type": "tool_call_end",
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"tool": tool_name,
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"id": tool_call_id,
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"result": tool_output
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}
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del tool_calls_in_progress[tool_call_id]
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processed_event = {
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"type": "state_update",
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"data": serialized_data
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}
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elif chunk_type == "custom":
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info(f"🎯 处理custom chunk")
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serialized_data = self._serialize_value(chunk["data"])
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processed_event = {
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"type": "custom",
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"data": serialized_data
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}
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if processed_event:
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yield processed_event
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info(f"✅ graph.astream() 完成，共 {chunk_count} 个chunks")
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except Exception as e:
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error(f"❌ 执行 React 图时出错: {e}")
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import traceback
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error(f"📋 堆栈: {traceback.format_exc()}")
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raise
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# 发送结束事件
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# 发送结束事件
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if current_node:
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if current_node:
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