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@@ -15,6 +15,7 @@ from ..model_services import get_cached_chat_services
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from ..main_graph.main_graph_builder import build_agent_graph
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from backend.app.logger import debug, info, warning, error
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from ..main_graph.state import AgentState
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from .stream_context import token_queue_var
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class AIAgentService:
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@@ -251,71 +252,107 @@ class AIAgentService:
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chunk_count = 0
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full_message_content = ""
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try:
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info(f"📡 开始调用 graph.astream()...")
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event_count = 0
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async for chunk in self.graph.astream(
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input_state,
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config=config,
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stream_mode=["messages", "updates"],
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version="v2",
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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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# 创建 token 队列
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token_queue = asyncio.Queue()
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# 设置上下文变量
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token_queue_var.set(token_queue)
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# 事件:graph 执行完成
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graph_done = asyncio.Event()
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graph_error = None
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async def run_graph():
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"""在后台运行 graph,并把 chunk 放进队列,同时也处理 events"""
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nonlocal chunk_count, full_message_content, graph_error
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try:
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info(f"📡 开始调用 graph.astream()...")
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# 记录原始 chunk 信息(前 10 个和后 10 个)
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if chunk_count <= 10 or chunk_count % 50 == 0:
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info(f" [{chunk_count}] chunk_type={chunk_type}, data={type(chunk.get('data'))}")
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event_count = 0
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async for chunk in self.graph.astream(
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input_state,
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config=config,
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stream_mode=["messages", "updates"],
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version="v2",
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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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# 记录原始 chunk 信息(前 10 个和后 10 个)
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if chunk_count <= 10 or chunk_count % 50 == 0:
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info(f" [{chunk_count}] chunk_type={chunk_type}, data={type(chunk.get('data'))}")
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if chunk_type == "messages":
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async for event in self._handle_message_chunk(
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chunk, current_node, tool_calls_in_progress
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):
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if event.get("type") == "_update_state":
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current_node = event.get("current_node", current_node)
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else:
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event_count += 1
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# 记录前 10 个事件
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if event_count <= 10:
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info(f" → yield event #{event_count}: {event.get('type')}")
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# 如果是 agent 节点的 token,收集完整消息
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if (
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event.get("type") == "llm_token"
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and event.get("node") == "agent"
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and "token" in event
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):
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full_message_content += event["token"]
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yield event
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if chunk_type == "messages":
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async for event in self._handle_message_chunk(
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chunk, current_node, tool_calls_in_progress
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):
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if event.get("type") == "_update_state":
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nonlocal current_node
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current_node = event.get("current_node", current_node)
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else:
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event_count += 1
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# 记录前 10 个事件
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if event_count <= 10:
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info(f" → yield event #{event_count}: {event.get('type')}")
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# 如果是 agent 节点的 token,收集完整消息
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if (
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event.get("type") == "llm_token"
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and event.get("node") == "agent"
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and "token" in event
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):
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full_message_content += event["token"]
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await token_queue.put(event)
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elif chunk_type == "updates":
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async for event in self._handle_updates_chunk(
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chunk, tool_calls_in_progress, actual_model_used
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):
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if event.get("type") == "_update_state":
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actual_model_used = event.get("actual_model_used", actual_model_used)
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else:
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event_count += 1
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if event_count <= 10:
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info(f" → yield event #{event_count}: {event.get('type')}")
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yield event
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elif chunk_type == "updates":
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async for event in self._handle_updates_chunk(
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chunk, tool_calls_in_progress, actual_model_used
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):
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if event.get("type") == "_update_state":
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nonlocal actual_model_used
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actual_model_used = event.get("actual_model_used", actual_model_used)
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else:
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event_count += 1
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if event_count <= 10:
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info(f" → yield event #{event_count}: {event.get('type')}")
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await token_queue.put(event)
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# 完整消息集合完成后,一次性打印
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info(f"✅ graph.astream() 完成,共 {chunk_count} 个 chunks, {event_count} 个 events")
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if full_message_content:
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info(f"📄 完整消息内容: {repr(full_message_content)}")
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# 完整消息集合完成后,一次性打印
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info(f"✅ graph.astream() 完成,共 {chunk_count} 个 chunks, {event_count} 个 events")
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if full_message_content:
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info(f"📄 完整消息内容: {repr(full_message_content)}")
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except Exception as e:
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error(f"❌ 执行图时出错: {e}")
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import traceback
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error(f"📋 堆栈: {traceback.format_exc()}")
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graph_error = e
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await token_queue.put({
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"type": "error",
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"message": str(e)
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})
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finally:
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graph_done.set()
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# 启动后台任务运行 graph
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graph_task = asyncio.create_task(run_graph())
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try:
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# 从队列里取事件并 yield
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while True:
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# 尝试从队列取事件,超时检查 graph 是否完成
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try:
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event = await asyncio.wait_for(token_queue.get(), timeout=0.1)
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yield event
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except asyncio.TimeoutError:
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# 检查 graph 是否完成
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if graph_done.is_set():
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break
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# 如果 graph 有错误,已经在 run_graph 里 yield error 了
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except Exception as e:
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error(f"❌ 执行图时出错: {e}")
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import traceback
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error(f"📋 堆栈: {traceback.format_exc()}")
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yield {
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"type": "error",
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"message": str(e)
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}
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finally:
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# 无论成功或失败,都发送结束事件,保证前端平稳关闭
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if current_node:
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@@ -327,3 +364,5 @@ class AIAgentService:
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"type": "done",
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"model_used": actual_model_used
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}
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# 取消任务
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graph_task.cancel()
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