610 lines
23 KiB
Python
610 lines
23 KiB
Python
"""Handoffs 服务 - 基于 LangGraph 的多 Agent 协作"""
|
||
import json
|
||
import uuid
|
||
from typing import List, Dict, Any, Optional, AsyncGenerator
|
||
from typing_extensions import TypedDict
|
||
|
||
from langchain_core.messages import HumanMessage, AIMessage, BaseMessage
|
||
from langgraph.graph import StateGraph, START, END
|
||
from langgraph.types import Command
|
||
from langgraph.checkpoint.memory import MemorySaver
|
||
from langchain_core.tools import tool
|
||
from pydantic import BaseModel, Field
|
||
from sqlalchemy.orm import Session
|
||
|
||
from app.core.logging_config import get_business_logger
|
||
from app.core.models import RedBearLLM, RedBearModelConfig
|
||
from app.models.models_model import ModelType
|
||
from app.services.model_service import ModelApiKeyService
|
||
|
||
logger = get_business_logger()
|
||
|
||
|
||
# ==================== 状态定义 ====================
|
||
|
||
class HandoffState(TypedDict):
|
||
"""Handoff 状态"""
|
||
messages: List[BaseMessage]
|
||
active_agent: Optional[str]
|
||
|
||
|
||
# ==================== 工具输入模型 ====================
|
||
|
||
class TransferInput(BaseModel):
|
||
"""转移工具的输入参数"""
|
||
reason: str = Field(description="转移原因")
|
||
|
||
|
||
# ==================== 工具创建 ====================
|
||
|
||
def create_transfer_tool(target_agent: str, description: str):
|
||
"""动态创建转移工具
|
||
|
||
Args:
|
||
target_agent: 目标 Agent 名称
|
||
description: 工具描述
|
||
|
||
Returns:
|
||
转移工具函数
|
||
"""
|
||
tool_name = f"transfer_to_{target_agent}"
|
||
|
||
@tool(tool_name, args_schema=TransferInput)
|
||
def transfer_tool(reason: str) -> Command:
|
||
"""动态生成的转移工具"""
|
||
return Command(
|
||
goto=target_agent,
|
||
update={"active_agent": target_agent},
|
||
)
|
||
|
||
transfer_tool.__doc__ = description
|
||
transfer_tool.description = description
|
||
return transfer_tool
|
||
|
||
|
||
def create_tools_for_agent(agent_name: str, configs: Dict) -> List:
|
||
"""根据 Agent 配置动态创建其可用的转移工具
|
||
|
||
Args:
|
||
agent_name: 当前 Agent 名称
|
||
configs: Agent 配置字典
|
||
|
||
Returns:
|
||
该 Agent 可用的工具列表
|
||
"""
|
||
config = configs.get(agent_name, {})
|
||
can_transfer_to = config.get("can_transfer_to", [])
|
||
|
||
tools = []
|
||
for target_agent in can_transfer_to:
|
||
target_config = configs.get(target_agent, {})
|
||
description = target_config.get("description", f"转移到 {target_agent}")
|
||
tools.append(create_transfer_tool(target_agent, description))
|
||
|
||
return tools
|
||
|
||
|
||
# ==================== Agent 节点创建 ====================
|
||
|
||
def create_agent_node(agent_name: str, system_prompt: str, tools: List,
|
||
model_config: RedBearModelConfig):
|
||
"""创建 Agent 节点（非流式）"""
|
||
llm = RedBearLLM(model_config, type=ModelType.CHAT)
|
||
|
||
# 绑定工具
|
||
if tools:
|
||
llm = llm.bind_tools(tools)
|
||
|
||
async def agent_node(state: HandoffState) -> Dict[str, Any]:
|
||
"""Agent 节点执行函数"""
|
||
logger.debug(f"Agent {agent_name} 执行, active_agent: {state.get('active_agent')}")
|
||
|
||
messages = state.get("messages", [])
|
||
full_messages = [{"role": "system", "content": system_prompt}] + messages
|
||
|
||
response = await llm.ainvoke(full_messages)
|
||
|
||
# 检查工具调用
|
||
if hasattr(response, 'tool_calls') and response.tool_calls:
|
||
tool_call = response.tool_calls[0]
|
||
tool_name = tool_call["name"] if isinstance(tool_call, dict) else tool_call.name
|
||
tool_args = tool_call["args"] if isinstance(tool_call, dict) else tool_call.args
|
||
|
||
if isinstance(tool_args, str):
|
||
try:
|
||
tool_args = json.loads(tool_args)
|
||
except (json.JSONDecodeError, ValueError):
|
||
tool_args = {}
|
||
|
||
if not tool_args.get("reason"):
|
||
tool_args["reason"] = "用户请求转移"
|
||
|
||
for t in tools:
|
||
if t.name == tool_name:
|
||
logger.info(f"Agent {agent_name} 调用工具: {tool_name}")
|
||
result = t.invoke(tool_args)
|
||
if isinstance(result, Command):
|
||
return result
|
||
|
||
return {"messages": [response]}
|
||
|
||
return agent_node
|
||
|
||
|
||
def create_streaming_agent_node(agent_name: str, system_prompt: str, tools: List,
|
||
model_config: RedBearModelConfig):
|
||
"""创建支持流式输出的 Agent 节点"""
|
||
llm = RedBearLLM(model_config, type=ModelType.CHAT)
|
||
|
||
# 绑定工具
|
||
if tools:
|
||
llm = llm.bind_tools(tools)
|
||
|
||
async def agent_node(state: HandoffState):
|
||
"""Agent 节点执行函数（流式）"""
|
||
logger.debug(f"Agent {agent_name} 流式执行, active_agent: {state.get('active_agent')}")
|
||
|
||
messages = state.get("messages", [])
|
||
full_messages = [{"role": "system", "content": system_prompt}] + messages
|
||
|
||
full_content = ""
|
||
collected_tool_calls = {}
|
||
|
||
async for chunk in llm.astream(full_messages):
|
||
if hasattr(chunk, 'content') and chunk.content:
|
||
full_content += chunk.content
|
||
|
||
# 收集工具调用
|
||
if hasattr(chunk, 'tool_calls') and chunk.tool_calls:
|
||
for tc in chunk.tool_calls:
|
||
tc_id = tc.get("id") if isinstance(tc, dict) else getattr(tc, 'id', "0")
|
||
tc_id = tc_id or "0"
|
||
if tc_id not in collected_tool_calls:
|
||
collected_tool_calls[tc_id] = {"id": tc_id, "name": "", "args": ""}
|
||
|
||
tc_name = tc.get("name") if isinstance(tc, dict) else getattr(tc, 'name', None)
|
||
tc_args = tc.get("args") if isinstance(tc, dict) else getattr(tc, 'args', None)
|
||
|
||
if tc_name:
|
||
collected_tool_calls[tc_id]["name"] = tc_name
|
||
if tc_args:
|
||
if isinstance(tc_args, dict):
|
||
collected_tool_calls[tc_id]["args"] = tc_args
|
||
elif isinstance(tc_args, str):
|
||
if isinstance(collected_tool_calls[tc_id]["args"], str):
|
||
collected_tool_calls[tc_id]["args"] += tc_args
|
||
|
||
# 处理 tool_call_chunks
|
||
if hasattr(chunk, 'tool_call_chunks') and chunk.tool_call_chunks:
|
||
for tc_chunk in chunk.tool_call_chunks:
|
||
idx = str(tc_chunk.get("index", 0) if isinstance(tc_chunk, dict) else getattr(tc_chunk, 'index', 0))
|
||
if idx not in collected_tool_calls:
|
||
tc_id = tc_chunk.get("id", idx) if isinstance(tc_chunk, dict) else getattr(tc_chunk, 'id', idx)
|
||
collected_tool_calls[idx] = {"id": tc_id, "name": "", "args": ""}
|
||
|
||
tc_id = tc_chunk.get("id") if isinstance(tc_chunk, dict) else getattr(tc_chunk, 'id', None)
|
||
tc_name = tc_chunk.get("name") if isinstance(tc_chunk, dict) else getattr(tc_chunk, 'name', None)
|
||
tc_args = tc_chunk.get("args") if isinstance(tc_chunk, dict) else getattr(tc_chunk, 'args', None)
|
||
|
||
if tc_id:
|
||
collected_tool_calls[idx]["id"] = tc_id
|
||
if tc_name:
|
||
collected_tool_calls[idx]["name"] = tc_name
|
||
if tc_args:
|
||
if isinstance(collected_tool_calls[idx]["args"], str):
|
||
collected_tool_calls[idx]["args"] += tc_args
|
||
|
||
# 解析工具调用
|
||
tool_calls_list = list(collected_tool_calls.values())
|
||
for tc in tool_calls_list:
|
||
if isinstance(tc.get("args"), str) and tc["args"]:
|
||
try:
|
||
tc["args"] = json.loads(tc["args"])
|
||
except (json.JSONDecodeError, ValueError):
|
||
tc["args"] = {}
|
||
elif not tc.get("args"):
|
||
tc["args"] = {}
|
||
|
||
# 执行工具调用
|
||
if tool_calls_list and tool_calls_list[0].get("name"):
|
||
tool_call = tool_calls_list[0]
|
||
tool_name = tool_call.get("name", "")
|
||
tool_args = tool_call.get("args", {})
|
||
|
||
if not tool_args.get("reason"):
|
||
tool_args["reason"] = "用户请求转移"
|
||
|
||
for t in tools:
|
||
if t.name == tool_name:
|
||
logger.info(f"Agent {agent_name} 调用工具: {tool_name}")
|
||
result = t.invoke(tool_args)
|
||
if isinstance(result, Command):
|
||
return result
|
||
|
||
return {"messages": [AIMessage(content=full_content)]}
|
||
|
||
return agent_node
|
||
|
||
|
||
# ==================== 路由函数 ====================
|
||
|
||
def create_route_initial(default_agent: str):
|
||
"""创建初始路由函数"""
|
||
def route_initial(state: HandoffState) -> str:
|
||
active = state.get("active_agent")
|
||
if active:
|
||
return active
|
||
return default_agent
|
||
return route_initial
|
||
|
||
|
||
def route_after_agent(state: HandoffState) -> str:
|
||
"""Agent 执行后的路由"""
|
||
messages = state.get("messages", [])
|
||
if messages:
|
||
last_msg = messages[-1]
|
||
if isinstance(last_msg, AIMessage) and not getattr(last_msg, 'tool_calls', None):
|
||
return END
|
||
return state.get("active_agent", END)
|
||
|
||
|
||
# ==================== 配置转换 ====================
|
||
|
||
def convert_multi_agent_config_to_handoffs(
|
||
multi_agent_config: Dict,
|
||
db: Session
|
||
) -> Dict[str, Dict]:
|
||
"""将 multi_agent_config 转换为 handoffs 配置格式
|
||
|
||
Args:
|
||
multi_agent_config: 数据库中的多 Agent 配置
|
||
db: 数据库会话
|
||
|
||
Returns:
|
||
agent_configs 字典，每个 Agent 包含自己的 model_config
|
||
"""
|
||
from app.models import AppRelease, App
|
||
|
||
sub_agents = multi_agent_config.get("sub_agents", [])
|
||
agent_configs = {}
|
||
agent_names = []
|
||
|
||
# 遍历子 Agent，构建配置
|
||
for sub_agent in sub_agents:
|
||
agent_id = sub_agent.get("agent_id") # 可能是 release_id 或 app_id
|
||
agent_name = sub_agent.get("name", f"agent_{agent_id[:8] if agent_id else 'unknown'}")
|
||
# 使用安全的 agent name（去除特殊字符）
|
||
safe_name = agent_name.replace(" ", "_").replace("-", "_").lower()
|
||
agent_names.append(safe_name)
|
||
|
||
# 从 AppRelease 获取 Agent 的系统提示词和模型配置
|
||
system_prompt = f"你是 {agent_name}。"
|
||
capabilities = sub_agent.get("capabilities", [])
|
||
model_config = None
|
||
release = None
|
||
|
||
if agent_id:
|
||
try:
|
||
agent_id_uuid = uuid.UUID(agent_id) if isinstance(agent_id, str) else agent_id
|
||
|
||
# 先尝试作为 release_id 查询
|
||
release = db.get(AppRelease, agent_id_uuid)
|
||
|
||
# 如果找不到，尝试作为 app_id 查询，获取 current_release
|
||
if not release:
|
||
app = db.get(App, agent_id_uuid)
|
||
if app and app.current_release_id:
|
||
release = db.get(AppRelease, app.current_release_id)
|
||
|
||
if release:
|
||
# 从 release.config 获取 system_prompt
|
||
if release.config:
|
||
config_data = release.config
|
||
release_system_prompt = config_data.get("system_prompt")
|
||
if release_system_prompt:
|
||
system_prompt = release_system_prompt
|
||
|
||
# 获取该 Agent 的模型配置
|
||
if release.default_model_config_id:
|
||
model_api_key = ModelApiKeyService.get_a_api_key(db, release.default_model_config_id)
|
||
if model_api_key:
|
||
model_config = RedBearModelConfig(
|
||
model_name=model_api_key.model_name,
|
||
provider=model_api_key.provider,
|
||
api_key=model_api_key.api_key,
|
||
base_url=model_api_key.api_base,
|
||
extra_params={
|
||
"temperature": 0.7,
|
||
"max_tokens": 2000,
|
||
"streaming": True
|
||
}
|
||
)
|
||
logger.debug(f"Agent {agent_name} 使用模型: {model_api_key.model_name}")
|
||
else:
|
||
logger.warning(f"Agent {agent_name} 模型配置无效: {release.default_model_config_id}")
|
||
else:
|
||
logger.warning(f"Agent {agent_name} 没有配置 default_model_config_id")
|
||
else:
|
||
logger.warning(f"Agent {agent_name} 找不到发布版本: agent_id={agent_id}")
|
||
except Exception as e:
|
||
logger.warning(f"获取 Agent {agent_name} 配置失败: {str(e)}")
|
||
|
||
# 如果有 capabilities，添加到系统提示词
|
||
if capabilities:
|
||
if not system_prompt.endswith("。"):
|
||
system_prompt += "。"
|
||
system_prompt += f" 你的专长是: {', '.join(capabilities)}。"
|
||
|
||
agent_configs[safe_name] = {
|
||
"agent_id": agent_id,
|
||
"name": agent_name,
|
||
"description": f"转移到 {agent_name}。{sub_agent.get('role') or ''}",
|
||
"system_prompt": system_prompt,
|
||
"capabilities": capabilities,
|
||
"model_config": model_config, # 每个 Agent 自己的模型配置
|
||
"can_transfer_to": [] # 稍后填充
|
||
}
|
||
|
||
# 设置每个 Agent 可以转移到的其他 Agent
|
||
for safe_name in agent_names:
|
||
agent_configs[safe_name]["can_transfer_to"] = [
|
||
name for name in agent_names if name != safe_name
|
||
]
|
||
# 更新系统提示词，添加转移说明
|
||
other_agents = agent_configs[safe_name]["can_transfer_to"]
|
||
if other_agents:
|
||
transfer_instructions = "\n如果用户的问题不在你的专长范围内，可以使用以下工具转移到其他 Agent："
|
||
for other_name in other_agents:
|
||
other_config = agent_configs[other_name]
|
||
transfer_instructions += f"\n- transfer_to_{other_name}: {other_config['description']}"
|
||
agent_configs[safe_name]["system_prompt"] += transfer_instructions
|
||
|
||
return agent_configs
|
||
|
||
|
||
# ==================== Handoffs 服务类 ====================
|
||
|
||
class HandoffsService:
|
||
"""Handoffs 服务 - 管理多 Agent 协作"""
|
||
|
||
def __init__(
|
||
self,
|
||
agent_configs: Dict[str, Dict],
|
||
streaming: bool = True
|
||
):
|
||
"""初始化 Handoffs 服务
|
||
|
||
Args:
|
||
agent_configs: Agent 配置字典，每个 Agent 包含自己的 model_config
|
||
streaming: 是否启用流式输出
|
||
"""
|
||
self.agent_configs = agent_configs
|
||
self.streaming = streaming
|
||
self._graph = None
|
||
|
||
# 验证每个 Agent 都有模型配置
|
||
for agent_name, config in agent_configs.items():
|
||
if not config.get("model_config"):
|
||
raise ValueError(f"Agent {agent_name} 没有配置模型")
|
||
|
||
logger.info(f"HandoffsService 初始化, agents: {list(self.agent_configs.keys())}")
|
||
|
||
def _build_graph(self):
|
||
"""构建 LangGraph 图"""
|
||
builder = StateGraph(HandoffState)
|
||
agent_names = list(self.agent_configs.keys())
|
||
|
||
if not agent_names:
|
||
|
||
raise ValueError("至少需要一个 Agent 配置")
|
||
|
||
for agent_name in agent_names:
|
||
config = self.agent_configs[agent_name]
|
||
tools = create_tools_for_agent(agent_name, self.agent_configs)
|
||
|
||
# 使用每个 Agent 自己的模型配置
|
||
agent_model_config = config.get("model_config")
|
||
|
||
if self.streaming:
|
||
agent_node = create_streaming_agent_node(
|
||
agent_name=agent_name,
|
||
system_prompt=config.get("system_prompt", f"你是 {agent_name}"),
|
||
tools=tools,
|
||
model_config=agent_model_config
|
||
)
|
||
else:
|
||
agent_node = create_agent_node(
|
||
agent_name=agent_name,
|
||
system_prompt=config.get("system_prompt", f"你是 {agent_name}"),
|
||
tools=tools,
|
||
model_config=agent_model_config
|
||
)
|
||
builder.add_node(agent_name, agent_node)
|
||
|
||
# 添加边
|
||
default_agent = agent_names[0]
|
||
builder.add_conditional_edges(START, create_route_initial(default_agent), agent_names)
|
||
|
||
for agent_name in agent_names:
|
||
builder.add_conditional_edges(agent_name, route_after_agent, agent_names + [END])
|
||
|
||
memory = MemorySaver()
|
||
return builder.compile(checkpointer=memory)
|
||
|
||
@property
|
||
def graph(self):
|
||
"""获取图实例（懒加载）"""
|
||
if self._graph is None:
|
||
self._graph = self._build_graph()
|
||
return self._graph
|
||
|
||
def reset(self):
|
||
"""重置图实例"""
|
||
self._graph = None
|
||
logger.info("HandoffsService 图已重置")
|
||
|
||
async def chat(
|
||
self,
|
||
message: str,
|
||
conversation_id: str = None
|
||
) -> Dict[str, Any]:
|
||
"""非流式聊天"""
|
||
conversation_id = conversation_id or f"conv-{uuid.uuid4().hex[:8]}"
|
||
config = {"configurable": {"thread_id": str(conversation_id)}}
|
||
|
||
logger.info(f"Handoffs chat: conversation_id={conversation_id}, message={message[:50]}...")
|
||
|
||
result = await self.graph.ainvoke({
|
||
"messages": [HumanMessage(content=message)]
|
||
}, config=config)
|
||
|
||
# 提取响应
|
||
response_content = ""
|
||
for msg in result.get("messages", []):
|
||
if isinstance(msg, AIMessage):
|
||
response_content = msg.content
|
||
break
|
||
|
||
return {
|
||
"conversation_id": str(conversation_id),
|
||
"active_agent": result.get("active_agent"),
|
||
"response": response_content,
|
||
"message_count": len(result.get("messages", []))
|
||
}
|
||
|
||
async def chat_stream(
|
||
self,
|
||
message: str,
|
||
conversation_id: str = None
|
||
) -> AsyncGenerator[str, None]:
|
||
"""流式聊天"""
|
||
conversation_id = conversation_id or f"conv-{uuid.uuid4().hex[:8]}"
|
||
config = {"configurable": {"thread_id": str(conversation_id)}}
|
||
|
||
logger.info(f"Handoffs stream chat: conversation_id={conversation_id}, message={message[:50]}...")
|
||
|
||
# 发送开始事件
|
||
yield f"event: start\ndata: {json.dumps({'conversation_id': str(conversation_id)}, ensure_ascii=False)}\n\n"
|
||
|
||
current_agent = None
|
||
|
||
try:
|
||
async for event in self.graph.astream_events(
|
||
{"messages": [HumanMessage(content=message)]},
|
||
config=config,
|
||
version="v2"
|
||
):
|
||
kind = event["event"]
|
||
|
||
# 捕获节点开始（Agent 切换）
|
||
if kind == "on_chain_start":
|
||
node_name = event.get("name", "")
|
||
if node_name in self.agent_configs:
|
||
if current_agent != node_name:
|
||
current_agent = node_name
|
||
agent_display_name = self.agent_configs[node_name].get("name", node_name)
|
||
yield f"event: agent\ndata: {json.dumps({'agent': node_name, 'agent_name': agent_display_name}, ensure_ascii=False)}\n\n"
|
||
|
||
# 捕获 LLM 流式输出
|
||
elif kind == "on_chat_model_stream":
|
||
content = event["data"]["chunk"].content
|
||
if content:
|
||
yield f"event: message\ndata: {json.dumps({'content': content}, ensure_ascii=False)}\n\n"
|
||
|
||
# 捕获工具调用（Handoff）
|
||
elif kind == "on_tool_start":
|
||
tool_name = event.get("name", "")
|
||
if tool_name.startswith("transfer_to_"):
|
||
target_agent = tool_name.replace("transfer_to_", "")
|
||
target_name = self.agent_configs.get(target_agent, {}).get("name", target_agent)
|
||
yield f"event: handoff\ndata: {json.dumps({'from': current_agent, 'to': target_agent, 'to_name': target_name}, ensure_ascii=False)}\n\n"
|
||
|
||
# 发送结束事件
|
||
yield f"event: end\ndata: {json.dumps({'conversation_id': str(conversation_id), 'final_agent': current_agent}, ensure_ascii=False)}\n\n"
|
||
|
||
except Exception as e:
|
||
logger.error(f"Handoffs stream error: {str(e)}")
|
||
yield f"event: error\ndata: {json.dumps({'error': str(e)}, ensure_ascii=False)}\n\n"
|
||
|
||
def get_agents(self) -> List[Dict[str, Any]]:
|
||
"""获取可用的 Agent 列表"""
|
||
agents = []
|
||
for name, config in self.agent_configs.items():
|
||
agents.append({
|
||
"id": name,
|
||
"name": config.get("name", name),
|
||
"description": config.get("description", ""),
|
||
"capabilities": config.get("capabilities", []),
|
||
"can_transfer_to": config.get("can_transfer_to", [])
|
||
})
|
||
return agents
|
||
|
||
|
||
# ==================== 服务工厂 ====================
|
||
|
||
# 缓存服务实例（按 app_id）
|
||
_service_cache: Dict[str, HandoffsService] = {}
|
||
|
||
|
||
def get_handoffs_service_for_app(
|
||
app_id: uuid.UUID,
|
||
db: Session,
|
||
streaming: bool = True
|
||
) -> HandoffsService:
|
||
"""根据 app_id 获取 Handoffs 服务实例
|
||
|
||
Args:
|
||
app_id: 应用 ID
|
||
db: 数据库会话
|
||
streaming: 是否流式
|
||
|
||
Returns:
|
||
HandoffsService 实例
|
||
"""
|
||
from app.services.multi_agent_service import MultiAgentService
|
||
|
||
cache_key = f"{app_id}_{streaming}"
|
||
|
||
# 检查缓存
|
||
if cache_key in _service_cache:
|
||
return _service_cache[cache_key]
|
||
|
||
# 获取多 Agent 配置
|
||
multi_agent_service = MultiAgentService(db)
|
||
multi_agent_config = multi_agent_service.get_multi_agent_configs(app_id)
|
||
|
||
if not multi_agent_config:
|
||
raise ValueError(f"应用 {app_id} 没有多 Agent 配置")
|
||
|
||
# 转换配置（每个 Agent 包含自己的 model_config）
|
||
agent_configs = convert_multi_agent_config_to_handoffs(multi_agent_config, db)
|
||
|
||
if not agent_configs:
|
||
raise ValueError(f"应用 {app_id} 没有配置子 Agent")
|
||
|
||
# 创建服务
|
||
service = HandoffsService(agent_configs, streaming)
|
||
|
||
# 缓存
|
||
_service_cache[cache_key] = service
|
||
|
||
return service
|
||
|
||
|
||
def reset_handoffs_service_cache(app_id: uuid.UUID = None):
|
||
"""重置服务缓存
|
||
|
||
Args:
|
||
app_id: 应用 ID，如果为 None 则清除所有缓存
|
||
"""
|
||
global _service_cache
|
||
|
||
if app_id:
|
||
keys_to_remove = [k for k in _service_cache if k.startswith(str(app_id))]
|
||
for key in keys_to_remove:
|
||
del _service_cache[key]
|
||
else:
|
||
_service_cache = {}
|
||
|
||
logger.info(f"Handoffs 服务缓存已重置: app_id={app_id}")
|