This commit is contained in:
UnCLAS-Prommer
2025-07-21 01:25:39 +08:00
12 changed files with 491 additions and 76 deletions

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@@ -14,13 +14,15 @@ from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_ch
from src.chat.planner_actions.planner import ActionPlanner
from src.chat.planner_actions.action_modifier import ActionModifier
from src.chat.planner_actions.action_manager import ActionManager
from src.chat.focus_chat.hfc_utils import CycleDetail
from src.chat.chat_loop.hfc_utils import CycleDetail
from src.person_info.relationship_builder_manager import relationship_builder_manager
from src.person_info.person_info import get_person_info_manager
from src.plugin_system.base.component_types import ActionInfo, ChatMode
from src.plugin_system.apis import generator_api, send_api, message_api
from src.chat.willing.willing_manager import get_willing_manager
from src.chat.mai_thinking.mai_think import mai_thinking_manager
ENABLE_THINKING = True
ERROR_LOOP_INFO = {
"loop_plan_info": {
@@ -331,7 +333,11 @@ class HeartFChatting:
logger.info(f"[{self.log_prefix}] {global_config.bot.nickname} 决定的回复内容: {content}")
# 发送回复 (不再需要传入 chat)
await self._send_response(response_set, reply_to_str, loop_start_time,message_data)
reply_text = await self._send_response(response_set, reply_to_str, loop_start_time,message_data)
if ENABLE_THINKING:
await mai_thinking_manager.get_mai_think(self.stream_id).do_think_after_response(reply_text)
return True

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@@ -2,7 +2,7 @@ from rich.traceback import install
from src.common.logger import get_logger
from src.chat.message_receive.chat_stream import get_chat_manager
from src.chat.focus_chat.heartFC_chat import HeartFChatting
from src.chat.chat_loop.heartFC_chat import HeartFChatting
from src.chat.utils.utils import get_chat_type_and_target_info
logger = get_logger("sub_heartflow")

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@@ -0,0 +1,182 @@
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.chat.message_receive.message import MessageSending, MessageRecv, MessageRecvS4U
from src.mais4u.mais4u_chat.s4u_msg_processor import S4UMessageProcessor
from src.common.logger import get_logger
logger = get_logger(__name__)
def init_prompt():
Prompt(
"""
你之前的内心想法是:{mind}
{memory_block}
{relation_info_block}
{chat_target}
{time_block}
{chat_info}
{identity}
你刚刚在{chat_target_2},你你刚刚的心情是:{mood_state}
---------------------
在这样的情况下,你对上面的内容,你对 {sender} 发送的 消息 “{target}” 进行了回复
你刚刚选择回复的内容是:{reponse}
现在,根据你之前的想法和回复的内容,推测你现在的想法,思考你现在的想法是什么,为什么做出上面的回复内容
请不要浮夸和夸张修辞,不要输出多余内容(包括前后缀,冒号和引号,括号()表情包at或 @等 )。只输出想法:""",
"after_response_think_prompt",
)
class MaiThinking:
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
if self.chat_stream.group_info:
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 = ""
self.chat_target = ""
self.chat_target_2 = ""
self.chat_info = ""
self.mood_state = ""
self.identity = ""
self.sender = ""
self.target = ""
self.thinking_model = LLMRequest(
model=global_config.model.replyer_1,
request_type="thinking",
)
async def do_think_before_response(self):
pass
async def do_think_after_response(self,reponse:str):
prompt = await global_prompt_manager.format_prompt(
"after_response_think_prompt",
mind=self.mind,
reponse=reponse,
memory_block=self.memory_block,
relation_info_block=self.relation_info_block,
time_block=self.time_block,
chat_target=self.chat_target,
chat_target_2=self.chat_target_2,
chat_info=self.chat_info,
mood_state=self.mood_state,
identity=self.identity,
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)
async def do_think_when_receive_message(self):
pass
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
# 其他 user_info 字段按需补充
},
"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
# 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
# 下面这些字段可选,根据 MessageRecv 需要
"is_emoji": False,
"has_emoji": False,
"is_picid": False,
"has_picid": False,
"is_voice": False,
"is_mentioned": False,
"is_command": False,
"is_internal": True,
"priority_mode": "interest",
"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):
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()

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@@ -208,8 +208,11 @@ class MessageRecvS4U(MessageRecv):
self.superchat_price = None
self.superchat_message_text = None
self.is_screen = False
self.is_internal = False
self.voice_done = None
self.chat_info = None
async def process(self) -> None:
self.processed_plain_text = await self._process_message_segments(self.message_segment)

View File

@@ -102,6 +102,7 @@ class MessageStorage:
)
except Exception:
logger.exception("存储消息失败")
logger.error(f"消息:{message}")
traceback.print_exc()
# 如果需要其他存储相关的函数,可以在这里添加

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@@ -6,7 +6,7 @@ import re
from typing import List, Optional, Dict, Any, Tuple
from datetime import datetime
from src.chat.mai_thinking.mai_think import mai_thinking_manager
from src.common.logger import get_logger
from src.config.config import global_config
from src.individuality.individuality import get_individuality
@@ -762,6 +762,26 @@ class DefaultReplyer:
message_list_before_now_long, target_user_id
)
mai_think = mai_thinking_manager.get_mai_think(chat_id)
mai_think.memory_block = memory_block
mai_think.relation_info_block = relation_info
mai_think.time_block = time_block
mai_think.chat_target = chat_target_1
mai_think.chat_target_2 = chat_target_2
# mai_think.chat_info = chat_talking_prompt
mai_think.mood_state = mood_prompt
mai_think.identity = identity_block
mai_think.sender = sender
mai_think.target = target
mai_think.chat_info = f"""
{background_dialogue_prompt}
--------------------------------
{time_block}
这是你和{sender}的对话,你们正在交流中:
{core_dialogue_prompt}"""
# 使用 s4u 风格的模板
template_name = "s4u_style_prompt"
@@ -786,6 +806,42 @@ class DefaultReplyer:
keywords_reaction_prompt=keywords_reaction_prompt,
moderation_prompt=moderation_prompt_block,
)
else:
mai_think = mai_thinking_manager.get_mai_think(chat_id)
mai_think.memory_block = memory_block
mai_think.relation_info_block = relation_info
mai_think.time_block = time_block
mai_think.chat_target = chat_target_1
mai_think.chat_target_2 = chat_target_2
mai_think.chat_info = chat_talking_prompt
mai_think.mood_state = mood_prompt
mai_think.identity = identity_block
mai_think.sender = sender
mai_think.target = target
# 使用原有的模式
return await global_prompt_manager.format_prompt(
template_name,
expression_habits_block=expression_habits_block,
chat_target=chat_target_1,
chat_info=chat_talking_prompt,
memory_block=memory_block,
tool_info_block=tool_info_block,
knowledge_prompt=prompt_info,
extra_info_block=extra_info_block,
relation_info_block=relation_info,
time_block=time_block,
reply_target_block=reply_target_block,
moderation_prompt=moderation_prompt_block,
keywords_reaction_prompt=keywords_reaction_prompt,
identity=identity_block,
target_message=target,
sender_name=sender,
config_expression_style=global_config.expression.expression_style,
action_descriptions=action_descriptions,
chat_target_2=chat_target_2,
mood_state=mood_prompt,
)
async def build_prompt_rewrite_context(
self,

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@@ -2,7 +2,7 @@ import asyncio
import traceback
import time
import random
from typing import Optional, Dict, Tuple # 导入类型提示
from typing import Optional, Dict, Tuple, List # 导入类型提示
from maim_message import UserInfo, Seg
from src.common.logger import get_logger
from src.chat.message_receive.chat_stream import ChatStream, get_chat_manager
@@ -42,6 +42,8 @@ class MessageSenderContainer:
self.voice_done = ""
async def add_message(self, chunk: str):
"""向队列中添加一个消息块。"""
await self.queue.put(chunk)
@@ -195,6 +197,7 @@ class S4UChat:
self.gpt = S4UStreamGenerator()
self.interest_dict: Dict[str, float] = {} # 用户兴趣分
self.internal_message :List[MessageRecvS4U] = []
self.msg_id = ""
self.voice_done = ""
@@ -240,7 +243,7 @@ class S4UChat:
score += self._get_interest_score(message.message_info.user_info.user_id)
return score
def decay_interest_score(self,message: MessageRecvS4U|MessageRecv):
def decay_interest_score(self):
for person_id, score in self.interest_dict.items():
if score > 0:
self.interest_dict[person_id] = score * 0.95
@@ -249,7 +252,7 @@ class S4UChat:
async def add_message(self, message: MessageRecvS4U|MessageRecv) -> None:
self.decay_interest_score(message)
self.decay_interest_score()
"""根据VIP状态和中断逻辑将消息放入相应队列。"""
user_id = message.message_info.user_info.user_id
@@ -259,8 +262,8 @@ class S4UChat:
try:
is_gift = message.is_gift
is_superchat = message.is_superchat
print(is_gift)
print(is_superchat)
# print(is_gift)
# print(is_superchat)
if is_gift:
await self.relationship_builder.build_relation(immediate_build=person_id)
# 安全地增加兴趣分如果person_id不存在则先初始化为1.0
@@ -388,6 +391,18 @@ class S4UChat:
queue_name = "vip"
# 其次处理普通队列
elif not self._normal_queue.empty():
# 判断 normal 队列是否只有一条消息,且 internal_message 有内容
if self._normal_queue.qsize() == 1 and self.internal_message:
if random.random() < 0.5:
# 50% 概率用 internal_message 最新一条
message = self.internal_message[-1]
priority = 0 # internal_message 没有优先级,设为 0
queue_name = "internal"
neg_priority = 0
entry_count = 0
logger.info(f"[{self.stream_name}] 触发 internal_message 生成回复: {getattr(message, 'processed_plain_text', str(message))[:20]}...")
# 不要从 normal 队列取出消息,保留在队列中
else:
neg_priority, entry_count, timestamp, message = self._normal_queue.get_nowait()
priority = -neg_priority
# 检查普通消息是否超时
@@ -398,6 +413,25 @@ class S4UChat:
self._normal_queue.task_done()
continue # 处理下一条
queue_name = "normal"
else:
neg_priority, entry_count, timestamp, message = self._normal_queue.get_nowait()
priority = -neg_priority
# 检查普通消息是否超时
if time.time() - timestamp > s4u_config.message_timeout_seconds:
logger.info(
f"[{self.stream_name}] Discarding stale normal message: {message.processed_plain_text[:20]}..."
)
self._normal_queue.task_done()
continue # 处理下一条
queue_name = "normal"
else:
if self.internal_message:
message = self.internal_message[-1]
priority = 0
neg_priority = 0
entry_count = 0
queue_name = "internal"
logger.info(f"[{self.stream_name}] normal/vip 队列都空,触发 internal_message 回复: {getattr(message, 'processed_plain_text', str(message))[:20]}...")
else:
continue # 没有消息了,回去等事件
@@ -421,6 +455,9 @@ class S4UChat:
# 标记任务完成
if queue_name == "vip":
self._vip_queue.task_done()
elif queue_name == "internal":
# 如果使用 internal_message 生成回复,则不从 normal 队列中移除
pass
else:
self._normal_queue.task_done()

View File

@@ -4,6 +4,7 @@ from typing import Tuple
from src.chat.memory_system.Hippocampus import hippocampus_manager
from src.chat.message_receive.message import MessageRecv, MessageRecvS4U
from maim_message.message_base import GroupInfo,UserInfo
from src.chat.message_receive.storage import MessageStorage
from src.chat.message_receive.chat_stream import get_chat_manager
from src.chat.utils.timer_calculator import Timer
@@ -93,6 +94,9 @@ class S4UMessageProcessor:
group_info=groupinfo,
)
if await self.handle_internal_message(message):
return
if await self.hadle_if_voice_done(message):
return
@@ -137,6 +141,32 @@ class S4UMessageProcessor:
else:
logger.info(f"[S4U]{userinfo.user_nickname}:{message.processed_plain_text}")
async def handle_internal_message(self, message: MessageRecvS4U):
if message.is_internal:
group_info = GroupInfo(platform = "amaidesu_default",group_id = 114514,group_name = "内心")
chat = await get_chat_manager().get_or_create_stream(
platform = "amaidesu_default",
user_info = message.message_info.user_info,
group_info = group_info
)
s4u_chat = get_s4u_chat_manager().get_or_create_chat(chat)
message.message_info.group_info = s4u_chat.chat_stream.group_info
message.message_info.platform = s4u_chat.chat_stream.platform
s4u_chat.internal_message.append(message)
s4u_chat._new_message_event.set()
logger.info(f"[{s4u_chat.stream_name}] 添加内部消息-------------------------------------------------------: {message.processed_plain_text}")
return True
return False
async def handle_screen_message(self, message: MessageRecvS4U):
if message.is_screen:
screen_manager.set_screen(message.screen_info)

View File

@@ -16,6 +16,7 @@ from src.mais4u.mais4u_chat.super_chat_manager import get_super_chat_manager
from src.mais4u.mais4u_chat.screen_manager import screen_manager
from src.chat.express.expression_selector import expression_selector
from .s4u_mood_manager import mood_manager
from src.person_info.person_info import PersonInfoManager, get_person_info_manager
logger = get_logger("prompt")
@@ -59,6 +60,37 @@ def init_prompt():
"s4u_prompt", # New template for private CHAT chat
)
Prompt(
"""
你的名字是麦麦, 是千石可乐开发的程序可以在QQ微信等平台发言你现在正在哔哩哔哩作为虚拟主播进行直播
虽然是个AI但你在努力扮演真人, 人设的配色是橙色和紫色和绿色
你有一头法式橙色卷发,你很可爱,穿戴英式侦探风格学院风裙子和帽子,你正在一个教室场景里进行虚拟线上直播。不过不要刻意提及这些内容,自然回复
你可以看见用户发送的弹幕礼物和superchat
你可以看见面前的屏幕,目前屏幕的内容是:
{screen_info}
{memory_block}
{expression_habits_block}
{sc_info}
{time_block}
{chat_info_danmu}
--------------------------------
以上是你和弹幕的对话与此同时你在与QQ群友聊天聊天记录如下
{chat_info_qq}
--------------------------------
你刚刚回复了QQ群你内心的想法是{mind}
请根据你内心的想法,组织一条回复,在直播间进行发言,可以点名吐槽对象,让观众知道你在说谁
{gift_info}
回复简短一些,平淡一些,可以参考贴吧,知乎和微博的回复风格。不要浮夸,有逻辑和条理。
表现的有个性,不要随意服从他人要求,积极互动。你现在的心情是:{mood_state}
不要输出多余内容(包括前后缀,冒号和引号,括号()表情包at或 @等 )。
你的发言:
""",
"s4u_prompt_internal", # New template for private CHAT chat
)
class PromptBuilder:
def __init__(self):
@@ -148,6 +180,7 @@ class PromptBuilder:
limit=300,
)
talk_type = message.message_info.platform + ":" + str(message.chat_stream.user_info.user_id)
core_dialogue_list = []
@@ -219,7 +252,20 @@ class PromptBuilder:
for msg in all_msg_seg_list:
core_msg_str += msg
return core_msg_str, background_dialogue_prompt
all_dialogue_prompt = get_raw_msg_before_timestamp_with_chat(
chat_id=chat_stream.stream_id,
timestamp=time.time(),
limit=20,
)
all_dialogue_prompt_str = build_readable_messages(
all_dialogue_prompt,
timestamp_mode="normal_no_YMD",
show_pic=False,
)
return core_msg_str, background_dialogue_prompt,all_dialogue_prompt_str
def build_gift_info(self, message: MessageRecvS4U):
if message.is_gift:
@@ -234,18 +280,34 @@ class PromptBuilder:
super_chat_manager = get_super_chat_manager()
return super_chat_manager.build_superchat_summary_string(message.chat_stream.stream_id)
async def build_prompt_normal(
self,
message: MessageRecvS4U,
chat_stream: ChatStream,
message_txt: str,
sender_name: str = "某人",
) -> str:
person_id = PersonInfoManager.get_person_id(
message.chat_stream.user_info.platform, message.chat_stream.user_info.user_id
)
person_info_manager = get_person_info_manager()
person_name = await person_info_manager.get_value(person_id, "person_name")
if message.chat_stream.user_info.user_nickname:
if person_name:
sender_name = f"[{message.chat_stream.user_info.user_nickname}]你叫ta{person_name}"
else:
sender_name = f"[{message.chat_stream.user_info.user_nickname}]"
else:
sender_name = f"用户({message.chat_stream.user_info.user_id})"
relation_info_block, memory_block, expression_habits_block = await asyncio.gather(
self.build_relation_info(chat_stream), self.build_memory_block(message_txt), self.build_expression_habits(chat_stream, message_txt, sender_name)
)
core_dialogue_prompt, background_dialogue_prompt = self.build_chat_history_prompts(chat_stream, message)
core_dialogue_prompt, background_dialogue_prompt,all_dialogue_prompt = self.build_chat_history_prompts(chat_stream, message)
gift_info = self.build_gift_info(message)
@@ -259,6 +321,7 @@ class PromptBuilder:
template_name = "s4u_prompt"
if not message.is_internal:
prompt = await global_prompt_manager.format_prompt(
template_name,
time_block=time_block,
@@ -274,6 +337,23 @@ class PromptBuilder:
message_txt=message_txt,
mood_state=mood.mood_state,
)
else:
prompt = await global_prompt_manager.format_prompt(
"s4u_prompt_internal",
time_block=time_block,
expression_habits_block=expression_habits_block,
relation_info_block=relation_info_block,
memory_block=memory_block,
screen_info=screen_info,
gift_info=gift_info,
sc_info=sc_info,
chat_info_danmu=all_dialogue_prompt,
chat_info_qq=message.chat_info,
mind=message.processed_plain_text,
mood_state=mood.mood_state,
)
print(prompt)

View File

@@ -2,7 +2,7 @@ import os
from typing import AsyncGenerator
from src.mais4u.openai_client import AsyncOpenAIClient
from src.config.config import global_config
from src.chat.message_receive.message import MessageRecv
from src.chat.message_receive.message import MessageRecvS4U
from src.mais4u.mais4u_chat.s4u_prompt import prompt_builder
from src.common.logger import get_logger
from src.person_info.person_info import PersonInfoManager, get_person_info_manager
@@ -46,15 +46,7 @@ class S4UStreamGenerator:
re.UNICODE | re.DOTALL,
)
async def generate_response(
self, message: MessageRecv, previous_reply_context: str = ""
) -> AsyncGenerator[str, None]:
"""根据当前模型类型选择对应的生成函数"""
# 从global_config中获取模型概率值并选择模型
self.partial_response = ""
current_client = self.client_1
self.current_model_name = self.model_1_name
async def build_last_internal_message(self,message:MessageRecvS4U,previous_reply_context:str = ""):
person_id = PersonInfoManager.get_person_id(
message.chat_stream.user_info.platform, message.chat_stream.user_info.user_id
)
@@ -78,13 +70,30 @@ class S4UStreamGenerator:
[这是用户发来的新消息, 你需要结合上下文,对此进行回复]:
{message.processed_plain_text}
"""
return True,message_txt
else:
message_txt = message.processed_plain_text
return False,message_txt
async def generate_response(
self, message: MessageRecvS4U, previous_reply_context: str = ""
) -> AsyncGenerator[str, None]:
"""根据当前模型类型选择对应的生成函数"""
# 从global_config中获取模型概率值并选择模型
self.partial_response = ""
message_txt = message.processed_plain_text
if not message.is_internal:
interupted,message_txt_added = await self.build_last_internal_message(message,previous_reply_context)
if interupted:
message_txt = message_txt_added
prompt = await prompt_builder.build_prompt_normal(
message=message,
message_txt=message_txt,
sender_name=sender_name,
chat_stream=message.chat_stream,
)
@@ -92,6 +101,10 @@ class S4UStreamGenerator:
f"{self.current_model_name}思考:{message_txt[:30] + '...' if len(message_txt) > 30 else message_txt}"
) # noqa: E501
current_client = self.client_1
self.current_model_name = self.model_1_name
extra_kwargs = {}
if self.replyer_1_config.get("enable_thinking") is not None:
extra_kwargs["enable_thinking"] = self.replyer_1_config.get("enable_thinking")

View File

@@ -25,12 +25,14 @@ from src.plugin_system.apis import generator_api, message_api
from src.plugins.built_in.core_actions.no_reply import NoReplyAction
from src.plugins.built_in.core_actions.emoji import EmojiAction
from src.person_info.person_info import get_person_info_manager
from src.chat.mai_thinking.mai_think import mai_thinking_manager
logger = get_logger("core_actions")
# 常量定义
WAITING_TIME_THRESHOLD = 1200 # 等待新消息时间阈值,单位秒
ENABLE_THINKING = True
class ReplyAction(BaseAction):
"""回复动作 - 参与聊天回复"""
@@ -131,6 +133,11 @@ class ReplyAction(BaseAction):
# 存储动作记录
reply_text = f"你对{person_name}进行了回复:{reply_text}"
if ENABLE_THINKING:
await mai_thinking_manager.get_mai_think(self.chat_id).do_think_after_response(reply_text)
await self.store_action_info(
action_build_into_prompt=False,
action_prompt_display=reply_text,