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调整对应的调用

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UnCLAS-Prommer
2025-07-30 17:07:55 +08:00
parent 3c40ceda4c
commit 6c0edd0ad7
40 changed files with 580 additions and 1236 deletions
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84
src/mais4u/mai_think.py
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@@ -2,13 +2,15 @@ from src.chat.message_receive.chat_stream import get_chat_manager
import time
from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
from src.llm_models.utils_model import LLMRequest
from src.config.config import global_config
from src.config.config import model_config
from src.chat.message_receive.message import MessageRecvS4U
from src.mais4u.mais4u_chat.s4u_msg_processor import S4UMessageProcessor
from src.mais4u.mais4u_chat.internal_manager import internal_manager
from src.common.logger import get_logger
logger = get_logger(__name__)
def init_prompt():
Prompt(
"""
@@ -32,10 +34,8 @@ def init_prompt():
)
class MaiThinking:
def __init__(self,chat_id):
def __init__(self, chat_id):
self.chat_id = chat_id
self.chat_stream = get_chat_manager().get_stream(chat_id)
self.platform = self.chat_stream.platform
@@ -44,11 +44,11 @@ class MaiThinking:
self.is_group = True
else:
self.is_group = False
self.s4u_message_processor = S4UMessageProcessor()
self.mind = ""
self.memory_block = ""
self.relation_info_block = ""
self.time_block = ""
@@ -59,17 +59,13 @@ class MaiThinking:
self.identity = ""
self.sender = ""
self.target = ""
self.thinking_model = LLMRequest(
model=global_config.model.replyer_1,
request_type="thinking",
)
self.thinking_model = LLMRequest(model_set=model_config.model_task_config.replyer_1, request_type="thinking")
async def do_think_before_response(self):
pass
async def do_think_after_response(self,reponse:str):
async def do_think_after_response(self, reponse: str):
prompt = await global_prompt_manager.format_prompt(
"after_response_think_prompt",
mind=self.mind,
@@ -85,47 +81,44 @@ class MaiThinking:
sender=self.sender,
target=self.target,
)
result, _ = await self.thinking_model.generate_response_async(prompt)
self.mind = result
logger.info(f"[{self.chat_id}] 思考前想法：{self.mind}")
# logger.info(f"[{self.chat_id}] 思考前prompt：{prompt}")
logger.info(f"[{self.chat_id}] 思考后想法：{self.mind}")
msg_recv = await self.build_internal_message_recv(self.mind)
await self.s4u_message_processor.process_message(msg_recv)
internal_manager.set_internal_state(self.mind)
async def do_think_when_receive_message(self):
pass
async def build_internal_message_recv(self,message_text:str):
async def build_internal_message_recv(self, message_text: str):
msg_id = f"internal_{time.time()}"
message_dict = {
"message_info": {
"message_id": msg_id,
"time": time.time(),
"user_info": {
"user_id": "internal", # 内部用户ID
"user_nickname": "内心", # 内部昵称
"platform": self.platform, # 平台标记为 internal
"user_id": "internal", # 内部用户ID
"user_nickname": "内心", # 内部昵称
"platform": self.platform, # 平台标记为 internal
# 其他 user_info 字段按需补充
},
"platform": self.platform, # 平台
"platform": self.platform, # 平台
# 其他 message_info 字段按需补充
},
"message_segment": {
"type": "text", # 消息类型
"data": message_text, # 消息内容
"type": "text", # 消息类型
"data": message_text, # 消息内容
# 其他 segment 字段按需补充
},
"raw_message": message_text, # 原始消息内容
"processed_plain_text": message_text, # 处理后的纯文本
"raw_message": message_text, # 原始消息内容
"processed_plain_text": message_text, # 处理后的纯文本
# 下面这些字段可选，根据 MessageRecv 需要
"is_emoji": False,
"has_emoji": False,
@@ -139,45 +132,36 @@ class MaiThinking:
"priority_info": {"message_priority": 10.0}, # 内部消息可设高优先级
"interest_value": 1.0,
}
if self.is_group:
message_dict["message_info"]["group_info"] = {
"platform": self.platform,
"group_id": self.chat_stream.group_info.group_id,
"group_name": self.chat_stream.group_info.group_name,
}
msg_recv = MessageRecvS4U(message_dict)
msg_recv.chat_info = self.chat_info
msg_recv.chat_stream = self.chat_stream
msg_recv.is_internal = True
return msg_recv
class MaiThinkingManager:
def __init__(self):
self.mai_think_list = []
def get_mai_think(self,chat_id):
def get_mai_think(self, chat_id):
for mai_think in self.mai_think_list:
if mai_think.chat_id == chat_id:
return mai_think
mai_think = MaiThinking(chat_id)
self.mai_think_list.append(mai_think)
return mai_think
mai_thinking_manager = MaiThinkingManager()
init_prompt()