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feat: 为工具管理器添加参数类型规范化处理，并基于渠道能力动态生成提示词中的格式要求

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jxxghp
2026-01-15 20:55:35 +08:00
parent 1bf9862e47
commit 1641d432dd
10 changed files with 324 additions and 282 deletions
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98
app/agent/__init__.py
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@@ -1,5 +1,3 @@
"""MoviePilot AI智能体实现"""
import asyncio
from typing import Dict, List, Any
@@ -11,8 +9,8 @@ from langchain_core.messages import HumanMessage, AIMessage, ToolCall, ToolMessa
from langchain_core.runnables.history import RunnableWithMessageHistory
from app.agent.callback import StreamingCallbackHandler
from app.agent.memory import ConversationMemoryManager
from app.agent.prompt import PromptManager
from app.agent.memory import conversation_manager
from app.agent.prompt import prompt_manager
from app.agent.tools.factory import MoviePilotToolFactory
from app.chain import ChainBase
from app.core.config import settings
@@ -27,7 +25,9 @@ class AgentChain(ChainBase):
class MoviePilotAgent:
"""MoviePilot AI智能体"""
"""
MoviePilot AI智能体
"""
def __init__(self, session_id: str, user_id: str = None,
channel: str = None, source: str = None, username: str = None):
@@ -40,12 +40,6 @@ class MoviePilotAgent:
# 消息助手
self.message_helper = MessageHelper()
# 记忆管理器
self.memory_manager = ConversationMemoryManager()
# 提示词管理器
self.prompt_manager = PromptManager()
# 回调处理器
self.callback_handler = StreamingCallbackHandler(
session_id=session_id
@@ -64,30 +58,37 @@ class MoviePilotAgent:
self.agent_executor = self._create_agent_executor()
def _initialize_llm(self):
"""初始化LLM模型"""
"""
初始化LLM模型
"""
return LLMHelper.get_llm(streaming=True, callbacks=[self.callback_handler])
def _initialize_tools(self) -> List:
"""初始化工具列表"""
"""
初始化工具列表
"""
return MoviePilotToolFactory.create_tools(
session_id=self.session_id,
user_id=self.user_id,
channel=self.channel,
source=self.source,
username=self.username,
callback_handler=self.callback_handler,
memory_mananger=self.memory_manager
callback_handler=self.callback_handler
)
@staticmethod
def _initialize_session_store() -> Dict[str, InMemoryChatMessageHistory]:
"""初始化内存存储"""
"""
初始化内存存储
"""
return {}
def get_session_history(self, session_id: str) -> InMemoryChatMessageHistory:
"""获取会话历史"""
"""
获取会话历史
"""
chat_history = InMemoryChatMessageHistory()
messages: List[dict] = self.memory_manager.get_recent_messages_for_agent(
messages: List[dict] = conversation_manager.get_recent_messages_for_agent(
session_id=session_id,
user_id=self.user_id
)
@@ -119,7 +120,9 @@ class MoviePilotAgent:
@staticmethod
def _initialize_prompt() -> ChatPromptTemplate:
"""初始化提示词模板"""
"""
初始化提示词模板
"""
try:
prompt_template = ChatPromptTemplate.from_messages([
("system", "{system_prompt}"),
@@ -134,7 +137,9 @@ class MoviePilotAgent:
raise e
def _create_agent_executor(self) -> RunnableWithMessageHistory:
"""创建Agent执行器"""
"""
创建Agent执行器
"""
try:
agent = create_openai_tools_agent(
llm=self.llm,
@@ -161,10 +166,12 @@ class MoviePilotAgent:
raise e
async def process_message(self, message: str) -> str:
"""处理用户消息"""
"""
处理用户消息
"""
try:
# 添加用户消息到记忆
await self.memory_manager.add_memory(
await conversation_manager.add_conversation(
self.session_id,
user_id=self.user_id,
role="user",
@@ -173,7 +180,7 @@ class MoviePilotAgent:
# 构建输入上下文
input_context = {
"system_prompt": self.prompt_manager.get_agent_prompt(channel=self.channel),
"system_prompt": prompt_manager.get_agent_prompt(channel=self.channel),
"input": message
}
@@ -190,7 +197,7 @@ class MoviePilotAgent:
await self.send_agent_message(agent_message)
# 添加Agent回复到记忆
await self.memory_manager.add_memory(
await conversation_manager.add_conversation(
session_id=self.session_id,
user_id=self.user_id,
role="agent",
@@ -210,7 +217,9 @@ class MoviePilotAgent:
return error_message
async def _execute_agent(self, input_context: Dict[str, Any]) -> Dict[str, Any]:
"""执行LangChain Agent"""
"""
执行LangChain Agent
"""
try:
with get_openai_callback() as cb:
result = await self.agent_executor.ainvoke(
@@ -243,7 +252,9 @@ class MoviePilotAgent:
}
async def send_agent_message(self, message: str, title: str = "MoviePilot助手"):
"""通过原渠道发送消息给用户"""
"""
通过原渠道发送消息给用户
"""
await AgentChain().async_post_message(
Notification(
channel=self.channel,
@@ -256,24 +267,32 @@ class MoviePilotAgent:
)
async def cleanup(self):
"""清理智能体资源"""
"""
清理智能体资源
"""
logger.info(f"MoviePilot智能体已清理: session_id={self.session_id}")
class AgentManager:
"""AI智能体管理器"""
"""
AI智能体管理器
"""
def __init__(self):
self.active_agents: Dict[str, MoviePilotAgent] = {}
self.memory_manager = ConversationMemoryManager()
async def initialize(self):
"""初始化管理器"""
await self.memory_manager.initialize()
@staticmethod
async def initialize():
"""
初始化管理器
"""
await conversation_manager.initialize()
async def close(self):
"""关闭管理器"""
await self.memory_manager.close()
"""
关闭管理器
"""
await conversation_manager.close()
# 清理所有活跃的智能体
for agent in self.active_agents.values():
await agent.cleanup()
@@ -281,7 +300,9 @@ class AgentManager:
async def process_message(self, session_id: str, user_id: str, message: str,
channel: str = None, source: str = None, username: str = None) -> str:
"""处理用户消息"""
"""
处理用户消息
"""
# 获取或创建Agent实例
if session_id not in self.active_agents:
logger.info(f"创建新的AI智能体实例，session_id: {session_id}, user_id: {user_id}")
@@ -292,7 +313,6 @@ class AgentManager:
source=source,
username=username
)
agent.memory_manager = self.memory_manager
self.active_agents[session_id] = agent
else:
agent = self.active_agents[session_id]
@@ -309,12 +329,14 @@ class AgentManager:
return await agent.process_message(message)
async def clear_session(self, session_id: str, user_id: str):
"""清空会话"""
"""
清空会话
"""
if session_id in self.active_agents:
agent = self.active_agents[session_id]
await agent.cleanup()
del self.active_agents[session_id]
await self.memory_manager.clear_memory(session_id, user_id)
await conversation_manager.clear_memory(session_id, user_id)
logger.info(f"会话 {session_id} 的记忆已清空")