Files
LangBot/pkg/platform/sources/wecombot.py
2025-11-05 12:14:01 +08:00

212 lines
8.0 KiB
Python

from __future__ import annotations
import typing
import asyncio
import traceback
import datetime
import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
import langbot_plugin.api.entities.builtin.platform.message as platform_message
import langbot_plugin.api.entities.builtin.platform.events as platform_events
import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
import pydantic
from ..logger import EventLogger
from libs.wecom_ai_bot_api.wecombotevent import WecomBotEvent
from libs.wecom_ai_bot_api.api import WecomBotClient
from ...core import app
class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
@staticmethod
async def yiri2target(message_chain: platform_message.MessageChain):
content = ''
for msg in message_chain:
if type(msg) is platform_message.Plain:
content += msg.text
return content
@staticmethod
async def target2yiri(event: WecomBotEvent):
yiri_msg_list = []
if event.type == 'group':
yiri_msg_list.append(platform_message.At(target=event.ai_bot_id))
yiri_msg_list.append(platform_message.Source(id=event.message_id, time=datetime.datetime.now()))
yiri_msg_list.append(platform_message.Plain(text=event.content))
if event.picurl != '':
yiri_msg_list.append(platform_message.Image(base64=event.picurl))
chain = platform_message.MessageChain(yiri_msg_list)
return chain
class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
@staticmethod
async def yiri2target(event:platform_events.MessageEvent):
return event.source_platform_object
@staticmethod
async def target2yiri(event:WecomBotEvent):
message_chain = await WecomBotMessageConverter.target2yiri(event)
if event.type == 'single':
return platform_events.FriendMessage(
sender=platform_entities.Friend(
id=event.userid,
nickname=event.username,
remark='',
),
message_chain=message_chain,
time=datetime.datetime.now().timestamp(),
source_platform_object=event,
)
elif event.type == 'group':
try:
sender = platform_entities.GroupMember(
id=event.userid,
permission='MEMBER',
member_name=event.username,
group=platform_entities.Group(
id=str(event.chatid),
name=event.chatname,
permission=platform_entities.Permission.Member,
),
special_title='',
join_timestamp=0,
last_speak_timestamp=0,
mute_time_remaining=0,
)
time = datetime.datetime.now().timestamp()
return platform_events.GroupMessage(
sender=sender,
message_chain=message_chain,
time=time,
source_platform_object=event,
)
except Exception:
print(traceback.format_exc())
class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
bot: WecomBotClient
bot_account_id: str
message_converter: WecomBotMessageConverter = WecomBotMessageConverter()
event_converter: WecomBotEventConverter = WecomBotEventConverter()
config: dict
def __init__(self, config: dict, logger: EventLogger):
required_keys = ['Token', 'EncodingAESKey', 'Corpid', 'BotId', 'port']
missing_keys = [key for key in required_keys if key not in config]
if missing_keys:
raise Exception(f'WecomBot 缺少配置项: {missing_keys}')
# 创建运行时 bot 对象
bot = WecomBotClient(
Token=config['Token'],
EnCodingAESKey=config['EncodingAESKey'],
Corpid=config['Corpid'],
logger=logger,
)
bot_account_id = config['BotId']
super().__init__(
config=config,
logger=logger,
bot=bot,
bot_account_id=bot_account_id,
)
async def reply_message(self, message_source:platform_events.MessageEvent, message:platform_message.MessageChain,quote_origin: bool = False):
content = await self.message_converter.yiri2target(message)
await self.bot.set_message(message_source.source_platform_object.message_id, content)
async def reply_message_chunk(
self,
message_source: platform_events.MessageEvent,
bot_message,
message: platform_message.MessageChain,
quote_origin: bool = False,
is_final: bool = False,
):
"""将流水线增量输出写入企业微信 stream 会话。
Args:
message_source: 流水线提供的原始消息事件。
bot_message: 当前片段对应的模型元信息(未使用)。
message: 需要回复的消息链。
quote_origin: 是否引用原消息(企业微信暂不支持)。
is_final: 标记当前片段是否为最终回复。
Returns:
dict: 包含 `stream` 键,标识写入是否成功。
Example:
在流水线 `reply_message_chunk` 调用中自动触发,无需手动调用。
"""
# 转换为纯文本(智能机器人当前协议仅支持文本流)
content = await self.message_converter.yiri2target(message)
msg_id = message_source.source_platform_object.message_id
# 将片段推送到 WecomBotClient 中的队列,返回值用于判断是否走降级逻辑
success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
if not success and is_final:
# 未命中流式队列时使用旧有 set_message 兜底
await self.bot.set_message(msg_id, content)
return {'stream': success}
async def is_stream_output_supported(self) -> bool:
"""智能机器人侧默认开启流式能力。
Returns:
bool: 恒定返回 True。
Example:
流水线执行阶段会调用此方法以确认是否启用流式。"""
return True
async def send_message(self, target_type, target_id, message):
pass
def register_listener(
self,
event_type: typing.Type[platform_events.Event],
callback: typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
):
async def on_message(event: WecomBotEvent):
try:
return await callback(await self.event_converter.target2yiri(event), self)
except Exception:
await self.logger.error(f'Error in wecombot callback: {traceback.format_exc()}')
print(traceback.format_exc())
try:
if event_type == platform_events.FriendMessage:
self.bot.on_message('single')(on_message)
elif event_type == platform_events.GroupMessage:
self.bot.on_message('group')(on_message)
except Exception:
print(traceback.format_exc())
async def run_async(self):
async def shutdown_trigger_placeholder():
while True:
await asyncio.sleep(1)
await self.bot.run_task(
host='0.0.0.0',
port=self.config['port'],
shutdown_trigger=shutdown_trigger_placeholder,
)
async def kill(self) -> bool:
return False
async def unregister_listener(
self,
event_type: type,
callback: typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
):
return super().unregister_listener(event_type, callback)
async def is_muted(self, group_id: int) -> bool:
pass