初始化

server/agent_service.py

@@ -1,5 +1,3 @@
-import asyncio
-
 from autogen_agentchat.agents import AssistantAgent
 from autogen_agentchat.messages import MultiModalMessage, TextMessage
 from autogen_core import Image
@@ -7,12 +5,11 @@ from autogen_core.models import ModelFamily
 from autogen_ext.models.ollama import OllamaChatCompletionClient
 
 from . import config
-from .mcp_tools import load_mcp_tools
 
 
 class AvatarAgentService:
     def __init__(self) -> None:
-        self._model_client = OllamaChatCompletionClient(
+        model_client = OllamaChatCompletionClient(
             model=config.OLLAMA_MODEL,
             model_info={
                 "vision": True,
@@ -22,34 +19,18 @@ class AvatarAgentService:
                 "structured_output": True,
             },
         )
-        self._agent: AssistantAgent | None = None
-        self._agent_lock = asyncio.Lock()
-
-    async def _create_agent(self) -> AssistantAgent:
-        tools = await load_mcp_tools()
-        return AssistantAgent(
+        self._agent = AssistantAgent(
             name="avatar",
-            model_client=self._model_client,
+            model_client=model_client,
             system_message=config.SYSTEM_MESSAGE,
-            tools=tools or None,
-            reflect_on_tool_use=bool(tools),
         )
 
-    async def _get_agent(self) -> AssistantAgent:
-        if self._agent is not None:
-            return self._agent
-        async with self._agent_lock:
-            if self._agent is None:
-                self._agent = await self._create_agent()
-        return self._agent
-
     async def reply(self, user_text: str, image_b64: str) -> str:
-        agent = await self._get_agent()
         user_image = Image.from_base64(image_b64)
         multimodal_task = MultiModalMessage(source="user", content=[user_text, user_image])
 
         ai_response = ""
-        async for message in agent.run_stream(task=multimodal_task):
+        async for message in self._agent.run_stream(task=multimodal_task):
             if isinstance(message, TextMessage) and message.source == "avatar":
                 ai_response = message.content