+
@@ -21,8 +21,8 @@
画师：略nd
-
MaiBot(麦麦)
-+
MaiBot(麦麦)
+
一款专注于 群组聊天 的赛博网友
探索本项目的文档 »
diff --git a/src/api/reload_config.py b/src/api/reload_config.py
index a5f36e3db..1772800b6 100644
--- a/src/api/reload_config.py
+++ b/src/api/reload_config.py
@@ -1,6 +1,6 @@
from fastapi import HTTPException
from rich.traceback import install
-from src.config.config import BotConfig
+from src.config.config import Config
from src.common.logger_manager import get_logger
import os
@@ -14,8 +14,8 @@ async def reload_config():
from src.config import config as config_module
logger.debug("正在重载配置文件...")
- bot_config_path = os.path.join(BotConfig.get_config_dir(), "bot_config.toml")
- config_module.global_config = BotConfig.load_config(config_path=bot_config_path)
+ bot_config_path = os.path.join(Config.get_config_dir(), "bot_config.toml")
+ config_module.global_config = Config.load_config(config_path=bot_config_path)
logger.debug("配置文件重载成功")
return {"status": "reloaded"}
except FileNotFoundError as e:
diff --git a/src/chat/emoji_system/emoji_manager.py b/src/chat/emoji_system/emoji_manager.py
index 2cdead064..fda0a63fd 100644
--- a/src/chat/emoji_system/emoji_manager.py
+++ b/src/chat/emoji_system/emoji_manager.py
@@ -369,15 +369,16 @@ class EmojiManager:
def __init__(self) -> None:
self._initialized = None
self._scan_task = None
- self.vlm = LLMRequest(model=global_config.vlm, temperature=0.3, max_tokens=1000, request_type="emoji")
+
+ self.vlm = LLMRequest(model=global_config.model.vlm, temperature=0.3, max_tokens=1000, request_type="emoji")
self.llm_emotion_judge = LLMRequest(
- model=global_config.llm_normal, max_tokens=600, request_type="emoji"
+ model=global_config.model.normal, max_tokens=600, request_type="emoji"
) # 更高的温度，更少的token（后续可以根据情绪来调整温度）
self.emoji_num = 0
- self.emoji_num_max = global_config.max_emoji_num
- self.emoji_num_max_reach_deletion = global_config.max_reach_deletion
- self.emoji_objects: List[MaiEmoji] = [] # 存储MaiEmoji对象的列表，使用类型注解明确列表元素类型
+ self.emoji_num_max = global_config.emoji.max_reg_num
+ self.emoji_num_max_reach_deletion = global_config.emoji.do_replace
+ self.emoji_objects: list[MaiEmoji] = [] # 存储MaiEmoji对象的列表，使用类型注解明确列表元素类型
logger.info("启动表情包管理器")
@@ -587,18 +588,18 @@ class EmojiManager:
logger.warning(f"[警告] 表情包目录不存在: {EMOJI_DIR}")
os.makedirs(EMOJI_DIR, exist_ok=True)
logger.info(f"[创建] 已创建表情包目录: {EMOJI_DIR}")
- await asyncio.sleep(global_config.EMOJI_CHECK_INTERVAL * 60)
+ await asyncio.sleep(global_config.emoji.check_interval * 60)
continue
# 检查目录是否为空
files = os.listdir(EMOJI_DIR)
if not files:
logger.warning(f"[警告] 表情包目录为空: {EMOJI_DIR}")
- await asyncio.sleep(global_config.EMOJI_CHECK_INTERVAL * 60)
+ await asyncio.sleep(global_config.emoji.check_interval * 60)
continue
# 检查是否需要处理表情包(数量超过最大值或不足)
- if (self.emoji_num > self.emoji_num_max and global_config.max_reach_deletion) or (
+ if (self.emoji_num > self.emoji_num_max and global_config.emoji.do_replace) or (
self.emoji_num < self.emoji_num_max
):
try:
@@ -625,7 +626,7 @@ class EmojiManager:
except Exception as e:
logger.error(f"[错误] 扫描表情包目录失败: {str(e)}")
- await asyncio.sleep(global_config.EMOJI_CHECK_INTERVAL * 60)
+ await asyncio.sleep(global_config.emoji.check_interval * 60)
async def get_all_emoji_from_db(self) -> None:
"""获取所有表情包并初始化为MaiEmoji类对象，更新 self.emoji_objects"""
@@ -764,7 +765,7 @@ class EmojiManager:
# 构建提示词
prompt = (
- f"{global_config.BOT_NICKNAME}的表情包存储已满({self.emoji_num}/{self.emoji_num_max})，"
+ f"{global_config.bot.nickname}的表情包存储已满({self.emoji_num}/{self.emoji_num_max})，"
f"需要决定是否删除一个旧表情包来为新表情包腾出空间。\n\n"
f"新表情包信息：\n"
f"描述: {new_emoji.description}\n\n"
@@ -847,10 +848,10 @@ class EmojiManager:
description, _ = await self.vlm.generate_response_for_image(prompt, image_base64, image_format)
# 审核表情包
- if global_config.EMOJI_CHECK:
+ if global_config.emoji.content_filtration:
prompt = f'''
这是一个表情包，请对这个表情包进行审核，标准如下：
- 1. 必须符合"{global_config.EMOJI_CHECK_PROMPT}"的要求
+ 1. 必须符合"{global_config.emoji.filtration_prompt}"的要求
2. 不能是色情、暴力、等违法违规内容，必须符合公序良俗
3. 不能是任何形式的截图，聊天记录或视频截图
4. 不要出现5个以上文字
diff --git a/src/chat/focus_chat/expressors/default_expressor.py b/src/chat/focus_chat/expressors/default_expressor.py
index 37c50c0dc..c5aa5f9a4 100644
--- a/src/chat/focus_chat/expressors/default_expressor.py
+++ b/src/chat/focus_chat/expressors/default_expressor.py
@@ -25,9 +25,10 @@ logger = get_logger("expressor")
class DefaultExpressor:
def __init__(self, chat_id: str):
self.log_prefix = "expressor"
+ # TODO: API-Adapter修改标记
self.express_model = LLMRequest(
- model=global_config.llm_normal,
- temperature=global_config.llm_normal["temp"],
+ model=global_config.model.normal,
+ temperature=global_config.model.normal["temp"],
max_tokens=256,
request_type="response_heartflow",
)
@@ -51,8 +52,8 @@ class DefaultExpressor:
messageinfo = anchor_message.message_info
thinking_time_point = parse_thinking_id_to_timestamp(thinking_id)
bot_user_info = UserInfo(
- user_id=global_config.BOT_QQ,
- user_nickname=global_config.BOT_NICKNAME,
+ user_id=global_config.bot.qq_account,
+ user_nickname=global_config.bot.nickname,
platform=messageinfo.platform,
)
# logger.debug(f"创建思考消息：{anchor_message}")
@@ -141,7 +142,7 @@ class DefaultExpressor:
try:
# 1. 获取情绪影响因子并调整模型温度
arousal_multiplier = mood_manager.get_arousal_multiplier()
- current_temp = float(global_config.llm_normal["temp"]) * arousal_multiplier
+ current_temp = float(global_config.model.normal["temp"]) * arousal_multiplier
self.express_model.params["temperature"] = current_temp # 动态调整温度
# 2. 获取信息捕捉器
@@ -183,6 +184,7 @@ class DefaultExpressor:
try:
with Timer("LLM生成", {}): # 内部计时器，可选保留
+ # TODO: API-Adapter修改标记
# logger.info(f"{self.log_prefix}[Replier-{thinking_id}]\nPrompt:\n{prompt}\n")
content, reasoning_content, model_name = await self.express_model.generate_response(prompt)
@@ -330,8 +332,8 @@ class DefaultExpressor:
thinking_start_time = await self.heart_fc_sender.get_thinking_start_time(self.chat_id, thinking_id)
bot_user_info = UserInfo(
- user_id=global_config.BOT_QQ,
- user_nickname=global_config.BOT_NICKNAME,
+ user_id=global_config.bot.qq_account,
+ user_nickname=global_config.bot.nickname,
platform=self.chat_stream.platform,
)
diff --git a/src/chat/focus_chat/expressors/exprssion_learner.py b/src/chat/focus_chat/expressors/exprssion_learner.py
index 942162bc8..7766fde56 100644
--- a/src/chat/focus_chat/expressors/exprssion_learner.py
+++ b/src/chat/focus_chat/expressors/exprssion_learner.py
@@ -77,8 +77,9 @@ def init_prompt() -> None:
class ExpressionLearner:
def __init__(self) -> None:
+ # TODO: API-Adapter修改标记
self.express_learn_model: LLMRequest = LLMRequest(
- model=global_config.llm_normal,
+ model=global_config.model.normal,
temperature=0.1,
max_tokens=256,
request_type="response_heartflow",
@@ -289,7 +290,7 @@ class ExpressionLearner:
# 构建prompt
prompt = await global_prompt_manager.format_prompt(
"personality_expression_prompt",
- personality=global_config.expression_style,
+ personality=global_config.personality.expression_style,
)
# logger.info(f"个性表达方式提取prompt: {prompt}")
diff --git a/src/chat/focus_chat/heartflow_processor.py b/src/chat/focus_chat/heartflow_processor.py
index bbfa4ce46..a4cf360a5 100644
--- a/src/chat/focus_chat/heartflow_processor.py
+++ b/src/chat/focus_chat/heartflow_processor.py
@@ -112,7 +112,7 @@ def _check_ban_words(text: str, chat, userinfo) -> bool:
Returns:
bool: 是否包含过滤词
"""
- for word in global_config.ban_words:
+ for word in global_config.chat.ban_words:
if word in text:
chat_name = chat.group_info.group_name if chat.group_info else "私聊"
logger.info(f"[{chat_name}]{userinfo.user_nickname}:{text}")
@@ -132,7 +132,7 @@ def _check_ban_regex(text: str, chat, userinfo) -> bool:
Returns:
bool: 是否匹配过滤正则
"""
- for pattern in global_config.ban_msgs_regex:
+ for pattern in global_config.chat.ban_msgs_regex:
if pattern.search(text):
chat_name = chat.group_info.group_name if chat.group_info else "私聊"
logger.info(f"[{chat_name}]{userinfo.user_nickname}:{text}")
diff --git a/src/chat/focus_chat/heartflow_prompt_builder.py b/src/chat/focus_chat/heartflow_prompt_builder.py
index edf671232..c0912bc86 100644
--- a/src/chat/focus_chat/heartflow_prompt_builder.py
+++ b/src/chat/focus_chat/heartflow_prompt_builder.py
@@ -7,15 +7,12 @@ from src.chat.person_info.relationship_manager import relationship_manager
from src.chat.utils.utils import get_embedding
import time
from typing import Union, Optional
-
-# from common.database.database import db
+from src.common.database import db
from src.chat.utils.utils import get_recent_group_speaker
from src.manager.mood_manager import mood_manager
from src.chat.memory_system.Hippocampus import HippocampusManager
from src.chat.knowledge.knowledge_lib import qa_manager
from src.chat.focus_chat.expressors.exprssion_learner import expression_learner
-
-# import traceback
import random
import json
import math
@@ -147,7 +144,7 @@ async def _build_prompt_focus(
message_list_before_now = get_raw_msg_before_timestamp_with_chat(
chat_id=chat_stream.stream_id,
timestamp=time.time(),
- limit=global_config.observation_context_size,
+ limit=global_config.chat.observation_context_size,
)
chat_talking_prompt = await build_readable_messages(
message_list_before_now,
@@ -214,7 +211,7 @@ async def _build_prompt_focus(
chat_target=chat_target_1, # Used in group template
# chat_talking_prompt=chat_talking_prompt,
chat_info=chat_talking_prompt,
- bot_name=global_config.BOT_NICKNAME,
+ bot_name=global_config.bot.nickname,
# prompt_personality=prompt_personality,
prompt_personality="",
reason=reason,
@@ -230,7 +227,7 @@ async def _build_prompt_focus(
info_from_tools=structured_info_prompt,
sender_name=effective_sender_name, # Used in private template
chat_talking_prompt=chat_talking_prompt,
- bot_name=global_config.BOT_NICKNAME,
+ bot_name=global_config.bot.nickname,
prompt_personality=prompt_personality,
# chat_target and chat_target_2 are not used in private template
current_mind_info=current_mind_info,
@@ -285,7 +282,7 @@ class PromptBuilder:
who_chat_in_group = get_recent_group_speaker(
chat_stream.stream_id,
(chat_stream.user_info.platform, chat_stream.user_info.user_id) if chat_stream.user_info else None,
- limit=global_config.observation_context_size,
+ limit=global_config.chat.observation_context_size,
)
elif chat_stream.user_info:
who_chat_in_group.append(
@@ -333,7 +330,7 @@ class PromptBuilder:
message_list_before_now = get_raw_msg_before_timestamp_with_chat(
chat_id=chat_stream.stream_id,
timestamp=time.time(),
- limit=global_config.observation_context_size,
+ limit=global_config.chat.observation_context_size,
)
chat_talking_prompt = await build_readable_messages(
message_list_before_now,
@@ -345,18 +342,15 @@ class PromptBuilder:
# 关键词检测与反应
keywords_reaction_prompt = ""
- for rule in global_config.keywords_reaction_rules:
- if rule.get("enable", False):
- if any(keyword in message_txt.lower() for keyword in rule.get("keywords", [])):
- logger.info(
- f"检测到以下关键词之一：{rule.get('keywords', [])}，触发反应：{rule.get('reaction', '')}"
- )
- keywords_reaction_prompt += rule.get("reaction", "") + "，"
+ for rule in global_config.keyword_reaction.rules:
+ if rule.enable:
+ if any(keyword in message_txt for keyword in rule.keywords):
+ logger.info(f"检测到以下关键词之一：{rule.keywords}，触发反应：{rule.reaction}")
+ keywords_reaction_prompt += f"{rule.reaction}，"
else:
- for pattern in rule.get("regex", []):
- result = pattern.search(message_txt)
- if result:
- reaction = rule.get("reaction", "")
+ for pattern in rule.regex:
+ if result := pattern.search(message_txt):
+ reaction = rule.reaction
for name, content in result.groupdict().items():
reaction = reaction.replace(f"[{name}]", content)
logger.info(f"匹配到以下正则表达式：{pattern}，触发反应：{reaction}")
@@ -402,8 +396,8 @@ class PromptBuilder:
chat_target_2=chat_target_2,
chat_talking_prompt=chat_talking_prompt,
message_txt=message_txt,
- bot_name=global_config.BOT_NICKNAME,
- bot_other_names="/".join(global_config.BOT_ALIAS_NAMES),
+ bot_name=global_config.bot.nickname,
+ bot_other_names="/".join(global_config.bot.alias_names),
prompt_personality=prompt_personality,
mood_prompt=mood_prompt,
reply_style1=reply_style1_chosen,
@@ -424,8 +418,8 @@ class PromptBuilder:
prompt_info=prompt_info,
chat_talking_prompt=chat_talking_prompt,
message_txt=message_txt,
- bot_name=global_config.BOT_NICKNAME,
- bot_other_names="/".join(global_config.BOT_ALIAS_NAMES),
+ bot_name=global_config.bot.nickname,
+ bot_other_names="/".join(global_config.bot.alias_names),
prompt_personality=prompt_personality,
mood_prompt=mood_prompt,
reply_style1=reply_style1_chosen,
diff --git a/src/chat/focus_chat/info_processors/chattinginfo_processor.py b/src/chat/focus_chat/info_processors/chattinginfo_processor.py
index 12bc8560a..bb70c043a 100644
--- a/src/chat/focus_chat/info_processors/chattinginfo_processor.py
+++ b/src/chat/focus_chat/info_processors/chattinginfo_processor.py
@@ -26,8 +26,9 @@ class ChattingInfoProcessor(BaseProcessor):
def __init__(self):
"""初始化观察处理器"""
super().__init__()
+ # TODO: API-Adapter修改标记
self.llm_summary = LLMRequest(
- model=global_config.llm_observation, temperature=0.7, max_tokens=300, request_type="chat_observation"
+ model=global_config.model.observation, temperature=0.7, max_tokens=300, request_type="chat_observation"
)
async def process_info(
@@ -108,12 +109,12 @@ class ChattingInfoProcessor(BaseProcessor):
"created_at": datetime.now().timestamp(),
}
- obs.mid_memorys.append(mid_memory)
- if len(obs.mid_memorys) > obs.max_mid_memory_len:
- obs.mid_memorys.pop(0) # 移除最旧的
+ obs.mid_memories.append(mid_memory)
+ if len(obs.mid_memories) > obs.max_mid_memory_len:
+ obs.mid_memories.pop(0) # 移除最旧的
mid_memory_str = "之前聊天的内容概述是：\n"
- for mid_memory_item in obs.mid_memorys: # 重命名循环变量以示区分
+ for mid_memory_item in obs.mid_memories: # 重命名循环变量以示区分
time_diff = int((datetime.now().timestamp() - mid_memory_item["created_at"]) / 60)
mid_memory_str += (
f"距离现在{time_diff}分钟前(聊天记录id:{mid_memory_item['id']})：{mid_memory_item['theme']}\n"
diff --git a/src/chat/focus_chat/info_processors/mind_processor.py b/src/chat/focus_chat/info_processors/mind_processor.py
index 1a104e123..221935e3d 100644
--- a/src/chat/focus_chat/info_processors/mind_processor.py
+++ b/src/chat/focus_chat/info_processors/mind_processor.py
@@ -81,8 +81,8 @@ class MindProcessor(BaseProcessor):
self.subheartflow_id = subheartflow_id
self.llm_model = LLMRequest(
- model=global_config.llm_sub_heartflow,
- temperature=global_config.llm_sub_heartflow["temp"],
+ model=global_config.model.sub_heartflow,
+ temperature=global_config.model.sub_heartflow["temp"],
max_tokens=800,
request_type="sub_heart_flow",
)
diff --git a/src/chat/focus_chat/info_processors/tool_processor.py b/src/chat/focus_chat/info_processors/tool_processor.py
index 8840c1ae4..57bac5f79 100644
--- a/src/chat/focus_chat/info_processors/tool_processor.py
+++ b/src/chat/focus_chat/info_processors/tool_processor.py
@@ -52,7 +52,7 @@ class ToolProcessor(BaseProcessor):
self.subheartflow_id = subheartflow_id
self.log_prefix = f"[{subheartflow_id}:ToolExecutor] "
self.llm_model = LLMRequest(
- model=global_config.llm_tool_use,
+ model=global_config.model.tool_use,
max_tokens=500,
request_type="tool_execution",
)
diff --git a/src/chat/focus_chat/memory_activator.py b/src/chat/focus_chat/memory_activator.py
index 2d7fea034..4faf43747 100644
--- a/src/chat/focus_chat/memory_activator.py
+++ b/src/chat/focus_chat/memory_activator.py
@@ -34,8 +34,9 @@ def init_prompt():
class MemoryActivator:
def __init__(self):
+ # TODO: API-Adapter修改标记
self.summary_model = LLMRequest(
- model=global_config.llm_summary, temperature=0.7, max_tokens=50, request_type="chat_observation"
+ model=global_config.model.summary, temperature=0.7, max_tokens=50, request_type="chat_observation"
)
self.running_memory = []
diff --git a/src/chat/focus_chat/planners/actions/base_action.py b/src/chat/focus_chat/planners/actions/base_action.py
index d9e619d13..82d259677 100644
--- a/src/chat/focus_chat/planners/actions/base_action.py
+++ b/src/chat/focus_chat/planners/actions/base_action.py
@@ -25,8 +25,8 @@ def register_action(cls):
logger.error(f"动作类 {cls.__name__} 缺少必要的属性: action_name 或 action_description")
return cls
- action_name = getattr(cls, "action_name") # noqa
- action_description = getattr(cls, "action_description") # noqa
+ action_name = cls.action_name
+ action_description = cls.action_description
is_default = getattr(cls, "default", False)
if not action_name or not action_description:
diff --git a/src/chat/focus_chat/planners/actions/reply_action.py b/src/chat/focus_chat/planners/actions/reply_action.py
index 3f8ca49a0..6e4f41d4d 100644
--- a/src/chat/focus_chat/planners/actions/reply_action.py
+++ b/src/chat/focus_chat/planners/actions/reply_action.py
@@ -2,8 +2,6 @@
# -*- coding: utf-8 -*-
from src.common.logger_manager import get_logger
-
-# from src.chat.utils.timer_calculator import Timer
from src.chat.focus_chat.planners.actions.base_action import BaseAction, register_action
from typing import Tuple, List
from src.chat.heart_flow.observation.observation import Observation
diff --git a/src/chat/focus_chat/planners/planner.py b/src/chat/focus_chat/planners/planner.py
index c87732d23..83c8b6791 100644
--- a/src/chat/focus_chat/planners/planner.py
+++ b/src/chat/focus_chat/planners/planner.py
@@ -4,8 +4,6 @@ from typing import List, Dict, Any, Optional
from rich.traceback import install
from src.chat.models.utils_model import LLMRequest
from src.config.config import global_config
-
-# from src.chat.focus_chat.heartflow_prompt_builder import prompt_builder
from src.chat.focus_chat.info.info_base import InfoBase
from src.chat.focus_chat.info.obs_info import ObsInfo
from src.chat.focus_chat.info.cycle_info import CycleInfo
diff --git a/src/chat/heart_flow/heartflow.py b/src/chat/heart_flow/heartflow.py
index ad876bcf0..748c8331e 100644
--- a/src/chat/heart_flow/heartflow.py
+++ b/src/chat/heart_flow/heartflow.py
@@ -35,8 +35,9 @@ class Heartflow:
self.subheartflow_manager: SubHeartflowManager = SubHeartflowManager(self.current_state)
# LLM模型配置
+ # TODO: API-Adapter修改标记
self.llm_model = LLMRequest(
- model=global_config.llm_heartflow, temperature=0.6, max_tokens=1000, request_type="heart_flow"
+ model=global_config.model.heartflow, temperature=0.6, max_tokens=1000, request_type="heart_flow"
)
# 外部依赖模块
diff --git a/src/chat/heart_flow/interest_chatting.py b/src/chat/heart_flow/interest_chatting.py
index 45f7fe952..bce372b5c 100644
--- a/src/chat/heart_flow/interest_chatting.py
+++ b/src/chat/heart_flow/interest_chatting.py
@@ -20,9 +20,9 @@ MAX_REPLY_PROBABILITY = 1
class InterestChatting:
def __init__(
self,
- decay_rate=global_config.default_decay_rate_per_second,
+ decay_rate=global_config.focus_chat.default_decay_rate_per_second,
max_interest=MAX_INTEREST,
- trigger_threshold=global_config.reply_trigger_threshold,
+ trigger_threshold=global_config.focus_chat.reply_trigger_threshold,
max_probability=MAX_REPLY_PROBABILITY,
):
# 基础属性初始化
diff --git a/src/chat/heart_flow/mai_state_manager.py b/src/chat/heart_flow/mai_state_manager.py
index 7dea910e9..017656ad2 100644
--- a/src/chat/heart_flow/mai_state_manager.py
+++ b/src/chat/heart_flow/mai_state_manager.py
@@ -18,19 +18,14 @@ enable_unlimited_hfc_chat = True # 调试用：无限专注聊天
prevent_offline_state = True
# 目前默认不启用OFFLINE状态
-# 不同状态下普通聊天的最大消息数
-base_normal_chat_num = global_config.base_normal_chat_num
-base_focused_chat_num = global_config.base_focused_chat_num
-
-
-MAX_NORMAL_CHAT_NUM_PEEKING = int(base_normal_chat_num / 2)
-MAX_NORMAL_CHAT_NUM_NORMAL = base_normal_chat_num
-MAX_NORMAL_CHAT_NUM_FOCUSED = base_normal_chat_num + 1
+MAX_NORMAL_CHAT_NUM_PEEKING = int(global_config.chat.base_normal_chat_num / 2)
+MAX_NORMAL_CHAT_NUM_NORMAL = global_config.chat.base_normal_chat_num
+MAX_NORMAL_CHAT_NUM_FOCUSED = global_config.chat.base_normal_chat_num + 1
# 不同状态下专注聊天的最大消息数
-MAX_FOCUSED_CHAT_NUM_PEEKING = int(base_focused_chat_num / 2)
-MAX_FOCUSED_CHAT_NUM_NORMAL = base_focused_chat_num
-MAX_FOCUSED_CHAT_NUM_FOCUSED = base_focused_chat_num + 2
+MAX_FOCUSED_CHAT_NUM_PEEKING = int(global_config.chat.base_focused_chat_num / 2)
+MAX_FOCUSED_CHAT_NUM_NORMAL = global_config.chat.base_focused_chat_num
+MAX_FOCUSED_CHAT_NUM_FOCUSED = global_config.chat.base_focused_chat_num + 2
# -- 状态定义 --
diff --git a/src/chat/heart_flow/observation/chatting_observation.py b/src/chat/heart_flow/observation/chatting_observation.py
index a51eba5e2..c30bc8e43 100644
--- a/src/chat/heart_flow/observation/chatting_observation.py
+++ b/src/chat/heart_flow/observation/chatting_observation.py
@@ -53,19 +53,20 @@ class ChattingObservation(Observation):
self.talking_message = []
self.talking_message_str = ""
self.talking_message_str_truncate = ""
- self.name = global_config.BOT_NICKNAME
- self.nick_name = global_config.BOT_ALIAS_NAMES
- self.max_now_obs_len = global_config.observation_context_size
- self.overlap_len = global_config.compressed_length
- self.mid_memorys = []
- self.max_mid_memory_len = global_config.compress_length_limit
+ self.name = global_config.bot.nickname
+ self.nick_name = global_config.bot.alias_names
+ self.max_now_obs_len = global_config.chat.observation_context_size
+ self.overlap_len = global_config.focus_chat.compressed_length
+ self.mid_memories = []
+ self.max_mid_memory_len = global_config.focus_chat.compress_length_limit
self.mid_memory_info = ""
self.person_list = []
self.oldest_messages = []
self.oldest_messages_str = ""
self.compressor_prompt = ""
+ # TODO: API-Adapter修改标记
self.llm_summary = LLMRequest(
- model=global_config.llm_observation, temperature=0.7, max_tokens=300, request_type="chat_observation"
+ model=global_config.model.observation, temperature=0.7, max_tokens=300, request_type="chat_observation"
)
async def initialize(self):
@@ -83,7 +84,7 @@ class ChattingObservation(Observation):
for id in ids:
print(f"id：{id}")
try:
- for mid_memory in self.mid_memorys:
+ for mid_memory in self.mid_memories:
if mid_memory["id"] == id:
mid_memory_by_id = mid_memory
msg_str = ""
@@ -101,7 +102,7 @@ class ChattingObservation(Observation):
else:
mid_memory_str = "之前的聊天内容：\n"
- for mid_memory in self.mid_memorys:
+ for mid_memory in self.mid_memories:
mid_memory_str += f"{mid_memory['theme']}\n"
return mid_memory_str + "现在群里正在聊：\n" + self.talking_message_str
diff --git a/src/chat/heart_flow/subheartflow_manager.py b/src/chat/heart_flow/subheartflow_manager.py
index a4bff8338..bf4ddf7e1 100644
--- a/src/chat/heart_flow/subheartflow_manager.py
+++ b/src/chat/heart_flow/subheartflow_manager.py
@@ -76,8 +76,9 @@ class SubHeartflowManager:
# 为 LLM 状态评估创建一个 LLMRequest 实例
# 使用与 Heartflow 相同的模型和参数
+ # TODO: API-Adapter修改标记
self.llm_state_evaluator = LLMRequest(
- model=global_config.llm_heartflow, # 与 Heartflow 一致
+ model=global_config.model.heartflow, # 与 Heartflow 一致
temperature=0.6, # 与 Heartflow 一致
max_tokens=1000, # 与 Heartflow 一致 (虽然可能不需要这么多)
request_type="subheartflow_state_eval", # 保留特定的请求类型
@@ -278,7 +279,7 @@ class SubHeartflowManager:
focused_limit = current_state.get_focused_chat_max_num()
# --- 新增：检查是否允许进入 FOCUS 模式 --- #
- if not global_config.allow_focus_mode:
+ if not global_config.chat.allow_focus_mode:
if int(time.time()) % 60 == 0: # 每60秒输出一次日志避免刷屏
logger.trace("未开启 FOCUSED 状态 (allow_focus_mode=False)")
return # 如果不允许，直接返回
@@ -766,7 +767,7 @@ class SubHeartflowManager:
focused_limit = current_mai_state.get_focused_chat_max_num()
# --- 检查是否允许 FOCUS 模式 --- #
- if not global_config.allow_focus_mode:
+ if not global_config.chat.allow_focus_mode:
# Log less frequently to avoid spam
# if int(time.time()) % 60 == 0:
# logger.debug(f"{log_prefix_task} 配置不允许进入 FOCUSED 状态")
diff --git a/src/chat/memory_system/Hippocampus.py b/src/chat/memory_system/Hippocampus.py
index 78616d824..2de769205 100644
--- a/src/chat/memory_system/Hippocampus.py
+++ b/src/chat/memory_system/Hippocampus.py
@@ -19,9 +19,10 @@ from ..utils.chat_message_builder import (
build_readable_messages,
) # 导入 build_readable_messages
from ..utils.utils import translate_timestamp_to_human_readable
-from .memory_config import MemoryConfig
from rich.traceback import install
+from ...config.config import global_config
+
install(extra_lines=3)
@@ -195,18 +196,16 @@ class Hippocampus:
self.llm_summary = None
self.entorhinal_cortex = None
self.parahippocampal_gyrus = None
- self.config = None
- def initialize(self, global_config):
- # 使用导入的 MemoryConfig dataclass 和其 from_global_config 方法
- self.config = MemoryConfig.from_global_config(global_config)
+ def initialize(self):
# 初始化子组件
self.entorhinal_cortex = EntorhinalCortex(self)
self.parahippocampal_gyrus = ParahippocampalGyrus(self)
# 从数据库加载记忆图
self.entorhinal_cortex.sync_memory_from_db()
- self.llm_topic_judge = LLMRequest(self.config.llm_topic_judge, request_type="memory")
- self.llm_summary = LLMRequest(self.config.llm_summary, request_type="memory")
+ # TODO: API-Adapter修改标记
+ self.llm_topic_judge = LLMRequest(global_config.model.topic_judge, request_type="memory")
+ self.llm_summary = LLMRequest(global_config.model.summary, request_type="memory")
def get_all_node_names(self) -> list:
"""获取记忆图中所有节点的名字列表"""
@@ -792,7 +791,6 @@ class EntorhinalCortex:
def __init__(self, hippocampus: Hippocampus):
self.hippocampus = hippocampus
self.memory_graph = hippocampus.memory_graph
- self.config = hippocampus.config
def get_memory_sample(self):
"""从数据库获取记忆样本"""
@@ -801,13 +799,13 @@ class EntorhinalCortex:
# 创建双峰分布的记忆调度器
sample_scheduler = MemoryBuildScheduler(
- n_hours1=self.config.memory_build_distribution[0],
- std_hours1=self.config.memory_build_distribution[1],
- weight1=self.config.memory_build_distribution[2],
- n_hours2=self.config.memory_build_distribution[3],
- std_hours2=self.config.memory_build_distribution[4],
- weight2=self.config.memory_build_distribution[5],
- total_samples=self.config.build_memory_sample_num,
+ n_hours1=global_config.memory.memory_build_distribution[0],
+ std_hours1=global_config.memory.memory_build_distribution[1],
+ weight1=global_config.memory.memory_build_distribution[2],
+ n_hours2=global_config.memory.memory_build_distribution[3],
+ std_hours2=global_config.memory.memory_build_distribution[4],
+ weight2=global_config.memory.memory_build_distribution[5],
+ total_samples=global_config.memory.memory_build_sample_num,
)
timestamps = sample_scheduler.get_timestamp_array()
@@ -818,7 +816,7 @@ class EntorhinalCortex:
for timestamp in timestamps:
# 调用修改后的 random_get_msg_snippet
messages = self.random_get_msg_snippet(
- timestamp, self.config.build_memory_sample_length, max_memorized_time_per_msg
+ timestamp, global_config.memory.memory_build_sample_length, max_memorized_time_per_msg
)
if messages:
time_diff = (datetime.datetime.now().timestamp() - timestamp) / 3600
@@ -1099,7 +1097,6 @@ class ParahippocampalGyrus:
def __init__(self, hippocampus: Hippocampus):
self.hippocampus = hippocampus
self.memory_graph = hippocampus.memory_graph
- self.config = hippocampus.config
async def memory_compress(self, messages: list, compress_rate=0.1):
"""压缩和总结消息内容，生成记忆主题和摘要。
@@ -1159,7 +1156,7 @@ class ParahippocampalGyrus:
# 3. 过滤掉包含禁用关键词的topic
filtered_topics = [
- topic for topic in topics if not any(keyword in topic for keyword in self.config.memory_ban_words)
+ topic for topic in topics if not any(keyword in topic for keyword in global_config.memory.memory_ban_words)
]
logger.debug(f"过滤后话题: {filtered_topics}")
@@ -1222,7 +1219,7 @@ class ParahippocampalGyrus:
bar = "█" * filled_length + "-" * (bar_length - filled_length)
logger.debug(f"进度: [{bar}] {progress:.1f}% ({i}/{len(memory_samples)})")
- compress_rate = self.config.memory_compress_rate
+ compress_rate = global_config.memory.memory_compress_rate
try:
compressed_memory, similar_topics_dict = await self.memory_compress(messages, compress_rate)
except Exception as e:
@@ -1322,7 +1319,7 @@ class ParahippocampalGyrus:
edge_data = self.memory_graph.G[source][target]
last_modified = edge_data.get("last_modified")
- if current_time - last_modified > 3600 * self.config.memory_forget_time:
+ if current_time - last_modified > 3600 * global_config.memory.memory_forget_time:
current_strength = edge_data.get("strength", 1)
new_strength = current_strength - 1
@@ -1430,8 +1427,8 @@ class ParahippocampalGyrus:
async def operation_consolidate_memory(self):
"""整合记忆：合并节点内相似的记忆项"""
start_time = time.time()
- percentage = self.config.consolidate_memory_percentage
- similarity_threshold = self.config.consolidation_similarity_threshold
+ percentage = global_config.memory.consolidate_memory_percentage
+ similarity_threshold = global_config.memory.consolidation_similarity_threshold
logger.info(f"[整合] 开始检查记忆节点... 检查比例: {percentage:.2%}, 合并阈值: {similarity_threshold}")
# 获取所有至少有2条记忆项的节点
@@ -1544,7 +1541,6 @@ class ParahippocampalGyrus:
class HippocampusManager:
_instance = None
_hippocampus = None
- _global_config = None
_initialized = False
@classmethod
@@ -1559,19 +1555,15 @@ class HippocampusManager:
raise RuntimeError("HippocampusManager 尚未初始化，请先调用 initialize 方法")
return cls._hippocampus
- def initialize(self, global_config):
+ def initialize(self):
"""初始化海马体实例"""
if self._initialized:
return self._hippocampus
- self._global_config = global_config
self._hippocampus = Hippocampus()
- self._hippocampus.initialize(global_config)
+ self._hippocampus.initialize()
self._initialized = True
- # 输出记忆系统参数信息
- config = self._hippocampus.config
-
# 输出记忆图统计信息
memory_graph = self._hippocampus.memory_graph.G
node_count = len(memory_graph.nodes())
@@ -1579,9 +1571,9 @@ class HippocampusManager:
logger.success(f"""--------------------------------
记忆系统参数配置:
- 构建间隔: {global_config.build_memory_interval}秒|样本数: {config.build_memory_sample_num},长度: {config.build_memory_sample_length}|压缩率: {config.memory_compress_rate}
- 记忆构建分布: {config.memory_build_distribution}
- 遗忘间隔: {global_config.forget_memory_interval}秒|遗忘比例: {global_config.memory_forget_percentage}|遗忘: {config.memory_forget_time}小时之后
+ 构建间隔: {global_config.memory.memory_build_interval}秒|样本数: {global_config.memory.memory_build_sample_num},长度: {global_config.memory.memory_build_sample_length}|压缩率: {global_config.memory.memory_compress_rate}
+ 记忆构建分布: {global_config.memory.memory_build_distribution}
+ 遗忘间隔: {global_config.memory.forget_memory_interval}秒|遗忘比例: {global_config.memory.memory_forget_percentage}|遗忘: {global_config.memory.memory_forget_time}小时之后
记忆图统计信息: 节点数量: {node_count}, 连接数量: {edge_count}
--------------------------------""") # noqa: E501
diff --git a/src/chat/memory_system/debug_memory.py b/src/chat/memory_system/debug_memory.py
index baf745409..b09e703a1 100644
--- a/src/chat/memory_system/debug_memory.py
+++ b/src/chat/memory_system/debug_memory.py
@@ -7,7 +7,6 @@ import os
# 添加项目根目录到系统路径
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))))
from src.chat.memory_system.Hippocampus import HippocampusManager
-from src.config.config import global_config
from rich.traceback import install
install(extra_lines=3)
@@ -19,7 +18,7 @@ async def test_memory_system():
# 初始化记忆系统
print("开始初始化记忆系统...")
hippocampus_manager = HippocampusManager.get_instance()
- hippocampus_manager.initialize(global_config=global_config)
+ hippocampus_manager.initialize()
print("记忆系统初始化完成")
# 测试记忆构建
diff --git a/src/chat/memory_system/memory_config.py b/src/chat/memory_system/memory_config.py
deleted file mode 100644
index b82e54ec1..000000000
--- a/src/chat/memory_system/memory_config.py
+++ /dev/null
@@ -1,48 +0,0 @@
-from dataclasses import dataclass
-from typing import List
-
-
-@dataclass
-class MemoryConfig:
- """记忆系统配置类"""
-
- # 记忆构建相关配置
- memory_build_distribution: List[float] # 记忆构建的时间分布参数
- build_memory_sample_num: int # 每次构建记忆的样本数量
- build_memory_sample_length: int # 每个样本的消息长度
- memory_compress_rate: float # 记忆压缩率
-
- # 记忆遗忘相关配置
- memory_forget_time: int # 记忆遗忘时间（小时）
-
- # 记忆过滤相关配置
- memory_ban_words: List[str] # 记忆过滤词列表
-
- # 新增：记忆整合相关配置
- consolidation_similarity_threshold: float # 相似度阈值
- consolidate_memory_percentage: float # 检查节点比例
- consolidate_memory_interval: int # 记忆整合间隔
-
- llm_topic_judge: str # 话题判断模型
- llm_summary: str # 话题总结模型
-
- @classmethod
- def from_global_config(cls, global_config):
- """从全局配置创建记忆系统配置"""
- # 使用 getattr 提供默认值，防止全局配置缺少这些项
- return cls(
- memory_build_distribution=getattr(
- global_config, "memory_build_distribution", (24, 12, 0.5, 168, 72, 0.5)
- ), # 添加默认值
- build_memory_sample_num=getattr(global_config, "build_memory_sample_num", 5),
- build_memory_sample_length=getattr(global_config, "build_memory_sample_length", 30),
- memory_compress_rate=getattr(global_config, "memory_compress_rate", 0.1),
- memory_forget_time=getattr(global_config, "memory_forget_time", 24 * 7),
- memory_ban_words=getattr(global_config, "memory_ban_words", []),
- # 新增加载整合配置，并提供默认值
- consolidation_similarity_threshold=getattr(global_config, "consolidation_similarity_threshold", 0.7),
- consolidate_memory_percentage=getattr(global_config, "consolidate_memory_percentage", 0.01),
- consolidate_memory_interval=getattr(global_config, "consolidate_memory_interval", 1000),
- llm_topic_judge=getattr(global_config, "llm_topic_judge", "default_judge_model"), # 添加默认模型名
- llm_summary=getattr(global_config, "llm_summary", "default_summary_model"), # 添加默认模型名
- )
diff --git a/src/chat/message_receive/bot.py b/src/chat/message_receive/bot.py
index 3c9e4420c..0e35f6f6e 100644
--- a/src/chat/message_receive/bot.py
+++ b/src/chat/message_receive/bot.py
@@ -41,7 +41,7 @@ class ChatBot:
chat_id = str(message.chat_stream.stream_id)
private_name = str(message.message_info.user_info.user_nickname)
- if global_config.enable_pfc_chatting:
+ if global_config.experimental.enable_pfc_chatting:
await self.pfc_manager.get_or_create_conversation(chat_id, private_name)
except Exception as e:
@@ -78,19 +78,19 @@ class ChatBot:
userinfo = message.message_info.user_info
# 用户黑名单拦截
- if userinfo.user_id in global_config.ban_user_id:
+ if userinfo.user_id in global_config.chat_target.ban_user_id:
logger.debug(f"用户{userinfo.user_id}被禁止回复")
return
if groupinfo is None:
logger.trace("检测到私聊消息，检查")
# 好友黑名单拦截
- if userinfo.user_id not in global_config.talk_allowed_private:
+ if userinfo.user_id not in global_config.experimental.talk_allowed_private:
logger.debug(f"用户{userinfo.user_id}没有私聊权限")
return
# 群聊黑名单拦截
- if groupinfo is not None and groupinfo.group_id not in global_config.talk_allowed_groups:
+ if groupinfo is not None and groupinfo.group_id not in global_config.chat_target.talk_allowed_groups:
logger.trace(f"群{groupinfo.group_id}被禁止回复")
return
@@ -112,7 +112,7 @@ class ChatBot:
if groupinfo is None:
logger.trace("检测到私聊消息")
# 是否在配置信息中开启私聊模式
- if global_config.enable_friend_chat:
+ if global_config.experimental.enable_friend_chat:
logger.trace("私聊模式已启用")
# 是否进入PFC
if global_config.enable_pfc_chatting:
diff --git a/src/chat/message_receive/message_buffer.py b/src/chat/message_receive/message_buffer.py
index f3cf63d0a..2df256ce5 100644
--- a/src/chat/message_receive/message_buffer.py
+++ b/src/chat/message_receive/message_buffer.py
@@ -38,7 +38,7 @@ class MessageBuffer:
async def start_caching_messages(self, message: MessageRecv):
"""添加消息，启动缓冲"""
- if not global_config.message_buffer:
+ if not global_config.chat.message_buffer:
person_id = person_info_manager.get_person_id(
message.message_info.user_info.platform, message.message_info.user_info.user_id
)
@@ -107,7 +107,7 @@ class MessageBuffer:
async def query_buffer_result(self, message: MessageRecv) -> bool:
"""查询缓冲结果，并清理"""
- if not global_config.message_buffer:
+ if not global_config.chat.message_buffer:
return True
person_id_ = self.get_person_id_(
message.message_info.platform, message.message_info.user_info.user_id, message.message_info.group_info
diff --git a/src/chat/message_receive/message_sender.py b/src/chat/message_receive/message_sender.py
index 5db34fdea..cf5877989 100644
--- a/src/chat/message_receive/message_sender.py
+++ b/src/chat/message_receive/message_sender.py
@@ -279,7 +279,7 @@ class MessageManager:
)
# 检查是否超时
- if thinking_time > global_config.thinking_timeout:
+ if thinking_time > global_config.normal_chat.thinking_timeout:
logger.warning(
f"[{chat_id}] 消息思考超时 ({thinking_time:.1f}秒)，移除消息 {message_earliest.message_info.message_id}"
)
diff --git a/src/chat/models/utils_model.py b/src/chat/models/utils_model.py
index eae0ae01a..f6528856d 100644
--- a/src/chat/models/utils_model.py
+++ b/src/chat/models/utils_model.py
@@ -110,8 +110,8 @@ class LLMRequest:
def __init__(self, model: dict, **kwargs):
# 将大写的配置键转换为小写并从config中获取实际值
try:
- self.api_key = os.environ[model["key"]]
- self.base_url = os.environ[model["base_url"]]
+ self.api_key = os.environ[f"{model['provider']}_KEY"]
+ self.base_url = os.environ[f"{model['provider']}_BASE_URL"]
except AttributeError as e:
logger.error(f"原始 model dict 信息：{model}")
logger.error(f"配置错误：找不到对应的配置项 - {str(e)}")
@@ -497,11 +497,11 @@ class LLMRequest:
logger.warning(f"检测到403错误，模型从 {old_model_name} 降级为 {self.model_name}")
# 对全局配置进行更新
- if global_config.llm_normal.get("name") == old_model_name:
- global_config.llm_normal["name"] = self.model_name
+ if global_config.model.normal.get("name") == old_model_name:
+ global_config.model.normal["name"] = self.model_name
logger.warning(f"将全局配置中的 llm_normal 模型临时降级至{self.model_name}")
- if global_config.llm_reasoning.get("name") == old_model_name:
- global_config.llm_reasoning["name"] = self.model_name
+ if global_config.model.reasoning.get("name") == old_model_name:
+ global_config.model.reasoning["name"] = self.model_name
logger.warning(f"将全局配置中的 llm_reasoning 模型临时降级至{self.model_name}")
if payload and "model" in payload:
@@ -633,7 +633,7 @@ class LLMRequest:
**params_copy,
}
if "max_tokens" not in payload and "max_completion_tokens" not in payload:
- payload["max_tokens"] = global_config.model_max_output_length
+ payload["max_tokens"] = global_config.model.model_max_output_length
# 如果 payload 中依然存在 max_tokens 且需要转换，在这里进行再次检查
if self.model_name.lower() in self.MODELS_NEEDING_TRANSFORMATION and "max_tokens" in payload:
payload["max_completion_tokens"] = payload.pop("max_tokens")
diff --git a/src/chat/normal_chat/normal_chat.py b/src/chat/normal_chat/normal_chat.py
index 9dc2454ff..96cc2b8cb 100644
--- a/src/chat/normal_chat/normal_chat.py
+++ b/src/chat/normal_chat/normal_chat.py
@@ -73,8 +73,8 @@ class NormalChat:
messageinfo = message.message_info
bot_user_info = UserInfo(
- user_id=global_config.BOT_QQ,
- user_nickname=global_config.BOT_NICKNAME,
+ user_id=global_config.bot.qq_account,
+ user_nickname=global_config.bot.nickname,
platform=messageinfo.platform,
)
@@ -121,8 +121,8 @@ class NormalChat:
message_id=thinking_id,
chat_stream=self.chat_stream, # 使用 self.chat_stream
bot_user_info=UserInfo(
- user_id=global_config.BOT_QQ,
- user_nickname=global_config.BOT_NICKNAME,
+ user_id=global_config.bot.qq_account,
+ user_nickname=global_config.bot.nickname,
platform=message.message_info.platform,
),
sender_info=message.message_info.user_info,
@@ -147,7 +147,7 @@ class NormalChat:
# 改为实例方法
async def _handle_emoji(self, message: MessageRecv, response: str):
"""处理表情包"""
- if random() < global_config.emoji_chance:
+ if random() < global_config.normal_chat.emoji_chance:
emoji_raw = await emoji_manager.get_emoji_for_text(response)
if emoji_raw:
emoji_path, description = emoji_raw
@@ -160,8 +160,8 @@ class NormalChat:
message_id="mt" + str(thinking_time_point),
chat_stream=self.chat_stream, # 使用 self.chat_stream
bot_user_info=UserInfo(
- user_id=global_config.BOT_QQ,
- user_nickname=global_config.BOT_NICKNAME,
+ user_id=global_config.bot.qq_account,
+ user_nickname=global_config.bot.nickname,
platform=message.message_info.platform,
),
sender_info=message.message_info.user_info,
@@ -186,7 +186,7 @@ class NormalChat:
label=emotion,
stance=stance, # 使用 self.chat_stream
)
- self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor)
+ self.mood_manager.update_mood_from_emotion(emotion, global_config.mood.mood_intensity_factor)
async def _reply_interested_message(self) -> None:
"""
@@ -430,7 +430,7 @@ class NormalChat:
def _check_ban_words(text: str, chat: ChatStream, userinfo: UserInfo) -> bool:
"""检查消息中是否包含过滤词"""
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id
- for word in global_config.ban_words:
+ for word in global_config.chat.ban_words:
if word in text:
logger.info(
f"[{stream_name}][{chat.group_info.group_name if chat.group_info else '私聊'}]"
@@ -445,7 +445,7 @@ class NormalChat:
def _check_ban_regex(text: str, chat: ChatStream, userinfo: UserInfo) -> bool:
"""检查消息是否匹配过滤正则表达式"""
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id
- for pattern in global_config.ban_msgs_regex:
+ for pattern in global_config.chat.ban_msgs_regex:
if pattern.search(text):
logger.info(
f"[{stream_name}][{chat.group_info.group_name if chat.group_info else '私聊'}]"
diff --git a/src/chat/normal_chat/normal_chat_generator.py b/src/chat/normal_chat/normal_chat_generator.py
index aec65ed1d..631f7baa5 100644
--- a/src/chat/normal_chat/normal_chat_generator.py
+++ b/src/chat/normal_chat/normal_chat_generator.py
@@ -15,21 +15,22 @@ logger = get_logger("llm")
class NormalChatGenerator:
def __init__(self):
+ # TODO: API-Adapter修改标记
self.model_reasoning = LLMRequest(
- model=global_config.llm_reasoning,
+ model=global_config.model.reasoning,
temperature=0.7,
max_tokens=3000,
request_type="response_reasoning",
)
self.model_normal = LLMRequest(
- model=global_config.llm_normal,
- temperature=global_config.llm_normal["temp"],
+ model=global_config.model.normal,
+ temperature=global_config.model.normal["temp"],
max_tokens=256,
request_type="response_reasoning",
)
self.model_sum = LLMRequest(
- model=global_config.llm_summary, temperature=0.7, max_tokens=3000, request_type="relation"
+ model=global_config.model.summary, temperature=0.7, max_tokens=3000, request_type="relation"
)
self.current_model_type = "r1" # 默认使用 R1
self.current_model_name = "unknown model"
@@ -37,7 +38,7 @@ class NormalChatGenerator:
async def generate_response(self, message: MessageThinking, thinking_id: str) -> Optional[Union[str, List[str]]]:
"""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
- if random.random() < global_config.model_reasoning_probability:
+ if random.random() < global_config.normal_chat.reasoning_model_probability:
self.current_model_type = "深深地"
current_model = self.model_reasoning
else:
@@ -51,7 +52,7 @@ class NormalChatGenerator:
model_response = await self._generate_response_with_model(message, current_model, thinking_id)
if model_response:
- logger.info(f"{global_config.BOT_NICKNAME}的回复是：{model_response}")
+ logger.info(f"{global_config.bot.nickname}的回复是：{model_response}")
model_response = await self._process_response(model_response)
return model_response
@@ -113,7 +114,7 @@ class NormalChatGenerator:
- "中立"：不表达明确立场或无关回应
2. 从"开心,愤怒,悲伤,惊讶,平静,害羞,恐惧,厌恶,困惑"中选出最匹配的1个情感标签
3. 按照"立场-情绪"的格式直接输出结果，例如："反对-愤怒"
- 4. 考虑回复者的人格设定为{global_config.personality_core}
+ 4. 考虑回复者的人格设定为{global_config.personality.personality_core}
对话示例：
被回复：「A就是笨」
diff --git a/src/chat/normal_chat/willing/mode_classical.py b/src/chat/normal_chat/willing/mode_classical.py
index e96aa77a7..a9f04273a 100644
--- a/src/chat/normal_chat/willing/mode_classical.py
+++ b/src/chat/normal_chat/willing/mode_classical.py
@@ -1,18 +1,20 @@
import asyncio
+
+from src.config.config import global_config
from .willing_manager import BaseWillingManager
class ClassicalWillingManager(BaseWillingManager):
def __init__(self):
super().__init__()
- self._decay_task: asyncio.Task = None
+ self._decay_task: asyncio.Task | None = None
async def _decay_reply_willing(self):
"""定期衰减回复意愿"""
while True:
await asyncio.sleep(1)
for chat_id in self.chat_reply_willing:
- self.chat_reply_willing[chat_id] = max(0, self.chat_reply_willing[chat_id] * 0.9)
+ self.chat_reply_willing[chat_id] = max(0.0, self.chat_reply_willing[chat_id] * 0.9)
async def async_task_starter(self):
if self._decay_task is None:
@@ -23,35 +25,33 @@ class ClassicalWillingManager(BaseWillingManager):
chat_id = willing_info.chat_id
current_willing = self.chat_reply_willing.get(chat_id, 0)
- interested_rate = willing_info.interested_rate * self.global_config.response_interested_rate_amplifier
+ interested_rate = willing_info.interested_rate * global_config.normal_chat.response_interested_rate_amplifier
if interested_rate > 0.4:
current_willing += interested_rate - 0.3
- if willing_info.is_mentioned_bot and current_willing < 1.0:
- current_willing += 1
- elif willing_info.is_mentioned_bot:
- current_willing += 0.05
+ if willing_info.is_mentioned_bot:
+ current_willing += 1 if current_willing < 1.0 else 0.05
is_emoji_not_reply = False
if willing_info.is_emoji:
- if self.global_config.emoji_response_penalty != 0:
- current_willing *= self.global_config.emoji_response_penalty
+ if global_config.normal_chat.emoji_response_penalty != 0:
+ current_willing *= global_config.normal_chat.emoji_response_penalty
else:
is_emoji_not_reply = True
self.chat_reply_willing[chat_id] = min(current_willing, 3.0)
reply_probability = min(
- max((current_willing - 0.5), 0.01) * self.global_config.response_willing_amplifier * 2, 1
+ max((current_willing - 0.5), 0.01) * global_config.normal_chat.response_willing_amplifier * 2, 1
)
# 检查群组权限（如果是群聊）
if (
willing_info.group_info
- and willing_info.group_info.group_id in self.global_config.talk_frequency_down_groups
+ and willing_info.group_info.group_id in global_config.chat_target.talk_frequency_down_groups
):
- reply_probability = reply_probability / self.global_config.down_frequency_rate
+ reply_probability = reply_probability / global_config.normal_chat.down_frequency_rate
if is_emoji_not_reply:
reply_probability = 0
@@ -61,7 +61,7 @@ class ClassicalWillingManager(BaseWillingManager):
async def before_generate_reply_handle(self, message_id):
chat_id = self.ongoing_messages[message_id].chat_id
current_willing = self.chat_reply_willing.get(chat_id, 0)
- self.chat_reply_willing[chat_id] = max(0, current_willing - 1.8)
+ self.chat_reply_willing[chat_id] = max(0.0, current_willing - 1.8)
async def after_generate_reply_handle(self, message_id):
if message_id not in self.ongoing_messages:
@@ -70,7 +70,7 @@ class ClassicalWillingManager(BaseWillingManager):
chat_id = self.ongoing_messages[message_id].chat_id
current_willing = self.chat_reply_willing.get(chat_id, 0)
if current_willing < 1:
- self.chat_reply_willing[chat_id] = min(1, current_willing + 0.4)
+ self.chat_reply_willing[chat_id] = min(1.0, current_willing + 0.4)
async def bombing_buffer_message_handle(self, message_id):
return await super().bombing_buffer_message_handle(message_id)
diff --git a/src/chat/normal_chat/willing/mode_mxp.py b/src/chat/normal_chat/willing/mode_mxp.py
index 78120ac53..1e7d5856d 100644
--- a/src/chat/normal_chat/willing/mode_mxp.py
+++ b/src/chat/normal_chat/willing/mode_mxp.py
@@ -19,6 +19,7 @@ Mxp 模式：梦溪畔独家赞助
下下策是询问一个菜鸟（@梦溪畔）
"""
+from src.config.config import global_config
from .willing_manager import BaseWillingManager
from typing import Dict
import asyncio
@@ -50,8 +51,6 @@ class MxpWillingManager(BaseWillingManager):
self.mention_willing_gain = 0.6 # 提及意愿增益
self.interest_willing_gain = 0.3 # 兴趣意愿增益
- self.emoji_response_penalty = self.global_config.emoji_response_penalty # 表情包回复惩罚
- self.down_frequency_rate = self.global_config.down_frequency_rate # 降低回复频率的群组惩罚系数
self.single_chat_gain = 0.12 # 单聊增益
self.fatigue_messages_triggered_num = self.expected_replies_per_min # 疲劳消息触发数量(int)
@@ -179,10 +178,10 @@ class MxpWillingManager(BaseWillingManager):
probability = self._willing_to_probability(current_willing)
if w_info.is_emoji:
- probability *= self.emoji_response_penalty
+ probability *= global_config.normal_chat.emoji_response_penalty
- if w_info.group_info and w_info.group_info.group_id in self.global_config.talk_frequency_down_groups:
- probability /= self.down_frequency_rate
+ if w_info.group_info and w_info.group_info.group_id in global_config.chat_target.talk_frequency_down_groups:
+ probability /= global_config.normal_chat.down_frequency_rate
self.temporary_willing = current_willing
diff --git a/src/chat/normal_chat/willing/willing_manager.py b/src/chat/normal_chat/willing/willing_manager.py
index 37e623d11..bbc5dcc0a 100644
--- a/src/chat/normal_chat/willing/willing_manager.py
+++ b/src/chat/normal_chat/willing/willing_manager.py
@@ -1,6 +1,6 @@
from src.common.logger import LogConfig, WILLING_STYLE_CONFIG, LoguruLogger, get_module_logger
from dataclasses import dataclass
-from src.config.config import global_config, BotConfig
+from src.config.config import global_config
from src.chat.message_receive.chat_stream import ChatStream, GroupInfo
from src.chat.message_receive.message import MessageRecv
from src.chat.person_info.person_info import person_info_manager, PersonInfoManager
@@ -93,7 +93,6 @@ class BaseWillingManager(ABC):
self.chat_reply_willing: Dict[str, float] = {} # 存储每个聊天流的回复意愿(chat_id)
self.ongoing_messages: Dict[str, WillingInfo] = {} # 当前正在进行的消息(message_id)
self.lock = asyncio.Lock()
- self.global_config: BotConfig = global_config
self.logger: LoguruLogger = logger
def setup(self, message: MessageRecv, chat: ChatStream, is_mentioned_bot: bool, interested_rate: float):
@@ -173,7 +172,7 @@ def init_willing_manager() -> BaseWillingManager:
Returns:
对应mode的WillingManager实例
"""
- mode = global_config.willing_mode.lower()
+ mode = global_config.normal_chat.willing_mode.lower()
return BaseWillingManager.create(mode)
diff --git a/src/chat/person_info/person_info.py b/src/chat/person_info/person_info.py
index 9d0841c0e..c31f483fb 100644
--- a/src/chat/person_info/person_info.py
+++ b/src/chat/person_info/person_info.py
@@ -56,8 +56,9 @@ person_info_default = {
class PersonInfoManager:
def __init__(self):
self.person_name_list = {}
+ # TODO: API-Adapter修改标记
self.qv_name_llm = LLMRequest(
- model=global_config.llm_normal,
+ model=global_config.model.normal,
max_tokens=256,
request_type="qv_name",
)
diff --git a/src/chat/utils/chat_message_builder.py b/src/chat/utils/chat_message_builder.py
index 42fed2f80..4dbcf499a 100644
--- a/src/chat/utils/chat_message_builder.py
+++ b/src/chat/utils/chat_message_builder.py
@@ -190,8 +190,8 @@ async def _build_readable_messages_internal(
person_id = person_info_manager.get_person_id(platform, user_id)
# 根据 replace_bot_name 参数决定是否替换机器人名称
- if replace_bot_name and user_id == global_config.BOT_QQ:
- person_name = f"{global_config.BOT_NICKNAME}(你)"
+ if replace_bot_name and user_id == global_config.bot.qq_account:
+ person_name = f"{global_config.bot.nickname}(你)"
else:
person_name = await person_info_manager.get_value(person_id, "person_name")
@@ -427,7 +427,7 @@ async def build_anonymous_messages(messages: List[Dict[str, Any]]) -> str:
output_lines = []
def get_anon_name(platform, user_id):
- if user_id == global_config.BOT_QQ:
+ if user_id == global_config.bot.qq_account:
return "SELF"
person_id = person_info_manager.get_person_id(platform, user_id)
if person_id not in person_map:
@@ -501,7 +501,7 @@ async def get_person_id_list(messages: List[Dict[str, Any]]) -> List[str]:
user_id = user_info.get("user_id")
# 检查必要信息是否存在 且 不是机器人自己
- if not all([platform, user_id]) or user_id == global_config.BOT_QQ:
+ if not all([platform, user_id]) or user_id == global_config.bot.qq_account:
continue
person_id = person_info_manager.get_person_id(platform, user_id)
diff --git a/src/chat/utils/info_catcher.py b/src/chat/utils/info_catcher.py
index 07caa06c0..93cda5113 100644
--- a/src/chat/utils/info_catcher.py
+++ b/src/chat/utils/info_catcher.py
@@ -10,7 +10,6 @@ import json
class InfoCatcher:
def __init__(self):
self.chat_history = [] # 聊天历史，长度为三倍使用的上下文喵~
- self.context_length = global_config.observation_context_size
self.chat_history_in_thinking = [] # 思考期间的聊天内容喵~
self.chat_history_after_response = [] # 回复后的聊天内容，长度为一倍上下文喵~
@@ -128,7 +127,7 @@ class InfoCatcher:
Messages.select()
.where((Messages.chat_id == chat_id_val) & (Messages.message_id < message_id_val))
.order_by(Messages.time.desc())
- .limit(self.context_length * 3)
+ .limit(global_config.chat.observation_context_size * 3)
)
return list(messages_before_query)
diff --git a/src/chat/utils/utils.py b/src/chat/utils/utils.py
index f78a0c114..c400a9948 100644
--- a/src/chat/utils/utils.py
+++ b/src/chat/utils/utils.py
@@ -43,8 +43,8 @@ def db_message_to_str(message_dict: dict) -> str:
def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
"""检查消息是否提到了机器人"""
- keywords = [global_config.BOT_NICKNAME]
- nicknames = global_config.BOT_ALIAS_NAMES
+ keywords = [global_config.bot.nickname]
+ nicknames = global_config.bot.alias_names
reply_probability = 0.0
is_at = False
is_mentioned = False
@@ -64,18 +64,18 @@ def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
)
# 判断是否被@
- if re.search(f"@[\s\S]*?（id:{global_config.BOT_QQ}）", message.processed_plain_text):
+ if re.search(f"@[\s\S]*?（id:{global_config.bot.qq_account}）", message.processed_plain_text):
is_at = True
is_mentioned = True
- if is_at and global_config.at_bot_inevitable_reply:
+ if is_at and global_config.normal_chat.at_bot_inevitable_reply:
reply_probability = 1.0
logger.info("被@，回复概率设置为100%")
else:
if not is_mentioned:
# 判断是否被回复
if re.match(
- f"\[回复 [\s\S]*?\({str(global_config.BOT_QQ)}\)：[\s\S]*?]，说：", message.processed_plain_text
+ f"\[回复 [\s\S]*?\({str(global_config.bot.qq_account)}\)：[\s\S]*?]，说：", message.processed_plain_text
):
is_mentioned = True
else:
@@ -88,7 +88,7 @@ def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
for nickname in nicknames:
if nickname in message_content:
is_mentioned = True
- if is_mentioned and global_config.mentioned_bot_inevitable_reply:
+ if is_mentioned and global_config.normal_chat.mentioned_bot_inevitable_reply:
reply_probability = 1.0
logger.info("被提及，回复概率设置为100%")
return is_mentioned, reply_probability
@@ -96,7 +96,8 @@ def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
async def get_embedding(text, request_type="embedding"):
"""获取文本的embedding向量"""
- llm = LLMRequest(model=global_config.embedding, request_type=request_type)
+ # TODO: API-Adapter修改标记
+ llm = LLMRequest(model=global_config.model.embedding, request_type=request_type)
# return llm.get_embedding_sync(text)
try:
embedding = await llm.get_embedding(text)
@@ -163,7 +164,7 @@ def get_recent_group_speaker(chat_stream_id: int, sender, limit: int = 12) -> li
user_info = UserInfo.from_dict(msg_db_data["user_info"])
if (
(user_info.platform, user_info.user_id) != sender
- and user_info.user_id != global_config.BOT_QQ
+ and user_info.user_id != global_config.bot.qq_account
and (user_info.platform, user_info.user_id, user_info.user_nickname) not in who_chat_in_group
and len(who_chat_in_group) < 5
): # 排除重复，排除消息发送者，排除bot，限制加载的关系数目
@@ -321,7 +322,7 @@ def random_remove_punctuation(text: str) -> str:
def process_llm_response(text: str) -> list[str]:
# 先保护颜文字
- if global_config.enable_kaomoji_protection:
+ if global_config.response_splitter.enable_kaomoji_protection:
protected_text, kaomoji_mapping = protect_kaomoji(text)
logger.trace(f"保护颜文字后的文本: {protected_text}")
else:
@@ -340,8 +341,8 @@ def process_llm_response(text: str) -> list[str]:
logger.debug(f"{text}去除括号处理后的文本: {cleaned_text}")
# 对清理后的文本进行进一步处理
- max_length = global_config.response_max_length * 2
- max_sentence_num = global_config.response_max_sentence_num
+ max_length = global_config.response_splitter.max_length * 2
+ max_sentence_num = global_config.response_splitter.max_sentence_num
# 如果基本上是中文，则进行长度过滤
if get_western_ratio(cleaned_text) < 0.1:
if len(cleaned_text) > max_length:
@@ -349,20 +350,20 @@ def process_llm_response(text: str) -> list[str]:
return ["懒得说"]
typo_generator = ChineseTypoGenerator(
- error_rate=global_config.chinese_typo_error_rate,
- min_freq=global_config.chinese_typo_min_freq,
- tone_error_rate=global_config.chinese_typo_tone_error_rate,
- word_replace_rate=global_config.chinese_typo_word_replace_rate,
+ error_rate=global_config.chinese_typo.error_rate,
+ min_freq=global_config.chinese_typo.min_freq,
+ tone_error_rate=global_config.chinese_typo.tone_error_rate,
+ word_replace_rate=global_config.chinese_typo.word_replace_rate,
)
- if global_config.enable_response_splitter:
+ if global_config.response_splitter.enable:
split_sentences = split_into_sentences_w_remove_punctuation(cleaned_text)
else:
split_sentences = [cleaned_text]
sentences = []
for sentence in split_sentences:
- if global_config.chinese_typo_enable:
+ if global_config.chinese_typo.enable:
typoed_text, typo_corrections = typo_generator.create_typo_sentence(sentence)
sentences.append(typoed_text)
if typo_corrections:
@@ -372,7 +373,7 @@ def process_llm_response(text: str) -> list[str]:
if len(sentences) > max_sentence_num:
logger.warning(f"分割后消息数量过多 ({len(sentences)} 条)，返回默认回复")
- return [f"{global_config.BOT_NICKNAME}不知道哦"]
+ return [f"{global_config.bot.nickname}不知道哦"]
# if extracted_contents:
# for content in extracted_contents:
diff --git a/src/chat/utils/utils_image.py b/src/chat/utils/utils_image.py
index 14cb24922..c317fbbd6 100644
--- a/src/chat/utils/utils_image.py
+++ b/src/chat/utils/utils_image.py
@@ -34,7 +34,9 @@ class ImageManager:
def __init__(self):
if not self._initialized:
self._ensure_image_dir()
- self._llm = LLMRequest(model=global_config.vlm, temperature=0.4, max_tokens=300, request_type="image")
+
+ self._initialized = True
+ self._llm = LLMRequest(model=global_config.model.vlm, temperature=0.4, max_tokens=300, request_type="image")
try:
db.connect(reuse_if_open=True)
@@ -126,7 +128,7 @@ class ImageManager:
return f"[表情包，含义看起来是：{cached_description}]"
# 根据配置决定是否保存图片
- if global_config.save_emoji:
+ if global_config.emoji.save_emoji:
# 生成文件名和路径
current_timestamp = time.time()
filename = f"{int(current_timestamp)}_{image_hash[:8]}.{image_format}"
@@ -199,7 +201,7 @@ class ImageManager:
logger.debug(f"描述是{description}")
# 根据配置决定是否保存图片
- if global_config.save_pic:
+ if global_config.emoji.save_pic:
# 生成文件名和路径
current_timestamp = time.time()
filename = f"{int(current_timestamp)}_{image_hash[:8]}.{image_format}"
diff --git a/src/common/remote.py b/src/common/remote.py
index 1d26df01b..b1108be9c 100644
--- a/src/common/remote.py
+++ b/src/common/remote.py
@@ -35,7 +35,7 @@ class TelemetryHeartBeatTask(AsyncTask):
info_dict = {
"os_type": "Unknown",
"py_version": platform.python_version(),
- "mmc_version": global_config.MAI_VERSION,
+ "mmc_version": global_config.MMC_VERSION,
}
match platform.system():
@@ -133,10 +133,9 @@ class TelemetryHeartBeatTask(AsyncTask):
async def run(self):
# 发送心跳
- if global_config.remote_enable:
- if self.client_uuid is None:
- if not await self._req_uuid():
- logger.error("获取UUID失败，跳过此次心跳")
- return
+ if global_config.telemetry.enable:
+ if self.client_uuid is None and not await self._req_uuid():
+ logger.error("获取UUID失败，跳过此次心跳")
+ return
await self._send_heartbeat()
diff --git a/src/config/config.py b/src/config/config.py
index b186f3b83..e6b7c5326 100644
--- a/src/config/config.py
+++ b/src/config/config.py
@@ -1,64 +1,68 @@
import os
-import re
-from dataclasses import dataclass, field
-from typing import Dict, List, Optional
+from dataclasses import field, dataclass
-import tomli
import tomlkit
import shutil
from datetime import datetime
-from pathlib import Path
-from packaging import version
-from packaging.version import Version, InvalidVersion
-from packaging.specifiers import SpecifierSet, InvalidSpecifier
+
+from tomlkit import TOMLDocument
+from tomlkit.items import Table
from src.common.logger_manager import get_logger
from rich.traceback import install
+from src.config.config_base import ConfigBase
+from src.config.official_configs import (
+ BotConfig,
+ ChatTargetConfig,
+ PersonalityConfig,
+ IdentityConfig,
+ PlatformsConfig,
+ ChatConfig,
+ NormalChatConfig,
+ FocusChatConfig,
+ EmojiConfig,
+ MemoryConfig,
+ MoodConfig,
+ KeywordReactionConfig,
+ ChineseTypoConfig,
+ ResponseSplitterConfig,
+ TelemetryConfig,
+ ExperimentalConfig,
+ ModelConfig,
+)
+
install(extra_lines=3)
# 配置主程序日志格式
logger = get_logger("config")
-# 考虑到，实际上配置文件中的mai_version是不会自动更新的,所以采用硬编码
-is_test = True
-mai_version_main = "0.6.4"
-mai_version_fix = "snapshot-1"
+CONFIG_DIR = "config"
+TEMPLATE_DIR = "template"
-if mai_version_fix:
- if is_test:
- mai_version = f"test-{mai_version_main}-{mai_version_fix}"
- else:
- mai_version = f"{mai_version_main}-{mai_version_fix}"
-else:
- if is_test:
- mai_version = f"test-{mai_version_main}"
- else:
- mai_version = mai_version_main
+# 考虑到，实际上配置文件中的mai_version是不会自动更新的,所以采用硬编码
+# 对该字段的更新，请严格参照语义化版本规范：https://semver.org/lang/zh-CN/
+MMC_VERSION = "0.7.0-snapshot.1"
def update_config():
# 获取根目录路径
- root_dir = Path(__file__).parent.parent.parent
- template_dir = root_dir / "template"
- config_dir = root_dir / "config"
- old_config_dir = config_dir / "old"
+ old_config_dir = f"{CONFIG_DIR}/old"
# 定义文件路径
- template_path = template_dir / "bot_config_template.toml"
- old_config_path = config_dir / "bot_config.toml"
- new_config_path = config_dir / "bot_config.toml"
+ template_path = f"{TEMPLATE_DIR}/bot_config_template.toml"
+ old_config_path = f"{CONFIG_DIR}/bot_config.toml"
+ new_config_path = f"{CONFIG_DIR}/bot_config.toml"
# 检查配置文件是否存在
- if not old_config_path.exists():
+ if not os.path.exists(old_config_path):
logger.info("配置文件不存在，从模板创建新配置")
- # 创建文件夹
- old_config_dir.mkdir(parents=True, exist_ok=True)
- shutil.copy2(template_path, old_config_path)
+ os.makedirs(CONFIG_DIR, exist_ok=True) # 创建文件夹
+ shutil.copy2(template_path, old_config_path) # 复制模板文件
logger.info(f"已创建新配置文件，请填写后重新运行: {old_config_path}")
# 如果是新创建的配置文件,直接返回
- return quit()
+ quit()
# 读取旧配置文件和模板文件
with open(old_config_path, "r", encoding="utf-8") as f:
@@ -75,13 +79,15 @@ def update_config():
return
else:
logger.info(f"检测到版本号不同: 旧版本 v{old_version} -> 新版本 v{new_version}")
+ else:
+ logger.info("已有配置文件未检测到版本号，可能是旧版本。将进行更新")
# 创建old目录（如果不存在）
- old_config_dir.mkdir(exist_ok=True)
+ os.makedirs(old_config_dir, exist_ok=True)
# 生成带时间戳的新文件名
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
- old_backup_path = old_config_dir / f"bot_config_{timestamp}.toml"
+ old_backup_path = f"{old_config_dir}/bot_config_{timestamp}.toml"
# 移动旧配置文件到old目录
shutil.move(old_config_path, old_backup_path)
@@ -91,24 +97,23 @@ def update_config():
shutil.copy2(template_path, new_config_path)
logger.info(f"已创建新配置文件: {new_config_path}")
- # 递归更新配置
- def update_dict(target, source):
+ def update_dict(target: TOMLDocument | dict, source: TOMLDocument | dict):
+ """
+ 将source字典的值更新到target字典中（如果target中存在相同的键）
+ """
for key, value in source.items():
# 跳过version字段的更新
if key == "version":
continue
if key in target:
- if isinstance(value, dict) and isinstance(target[key], (dict, tomlkit.items.Table)):
+ if isinstance(value, dict) and isinstance(target[key], (dict, Table)):
update_dict(target[key], value)
else:
try:
# 对数组类型进行特殊处理
if isinstance(value, list):
# 如果是空数组，确保它保持为空数组
- if not value:
- target[key] = tomlkit.array()
- else:
- target[key] = tomlkit.array(value)
+ target[key] = tomlkit.array(str(value)) if value else tomlkit.array()
else:
# 其他类型使用item方法创建新值
target[key] = tomlkit.item(value)
@@ -123,619 +128,57 @@ def update_config():
# 保存更新后的配置（保留注释和格式）
with open(new_config_path, "w", encoding="utf-8") as f:
f.write(tomlkit.dumps(new_config))
- logger.info("配置文件更新完成")
+ logger.info("配置文件更新完成，建议检查新配置文件中的内容，以免丢失重要信息")
+ quit()
@dataclass
-class BotConfig:
- """机器人配置类"""
-
- INNER_VERSION: Version = None
- MAI_VERSION: str = mai_version # 硬编码的版本信息
-
- # bot
- BOT_QQ: Optional[str] = "114514"
- BOT_NICKNAME: Optional[str] = None
- BOT_ALIAS_NAMES: List[str] = field(default_factory=list) # 别名，可以通过这个叫它
-
- # group
- talk_allowed_groups = set()
- talk_frequency_down_groups = set()
- ban_user_id = set()
-
- # personality
- personality_core = "用一句话或几句话描述人格的核心特点" # 建议20字以内，谁再写3000字小作文敲谁脑袋
- personality_sides: List[str] = field(
- default_factory=lambda: [
- "用一句话或几句话描述人格的一些侧面",
- "用一句话或几句话描述人格的一些侧面",
- "用一句话或几句话描述人格的一些侧面",
- ]
- )
- expression_style = "描述麦麦说话的表达风格，表达习惯"
- # identity
- identity_detail: List[str] = field(
- default_factory=lambda: [
- "身份特点",
- "身份特点",
- ]
- )
- height: int = 170 # 身高 单位厘米
- weight: int = 50 # 体重 单位千克
- age: int = 20 # 年龄 单位岁
- gender: str = "男" # 性别
- appearance: str = "用几句话描述外貌特征" # 外貌特征
-
- # chat
- allow_focus_mode: bool = True # 是否允许专注聊天状态
-
- base_normal_chat_num: int = 3 # 最多允许多少个群进行普通聊天
- base_focused_chat_num: int = 2 # 最多允许多少个群进行专注聊天
-
- observation_context_size: int = 12 # 心流观察到的最长上下文大小，超过这个值的上下文会被压缩
-
- message_buffer: bool = True # 消息缓冲器
-
- ban_words = set()
- ban_msgs_regex = set()
-
- # focus_chat
- reply_trigger_threshold: float = 3.0 # 心流聊天触发阈值，越低越容易触发
- default_decay_rate_per_second: float = 0.98 # 默认衰减率，越大衰减越慢
- consecutive_no_reply_threshold = 3
-
- compressed_length: int = 5 # 不能大于observation_context_size,心流上下文压缩的最短压缩长度，超过心流观察到的上下文长度，会压缩，最短压缩长度为5
- compress_length_limit: int = 5 # 最多压缩份数，超过该数值的压缩上下文会被删除
-
- # normal_chat
- model_reasoning_probability: float = 0.7 # 麦麦回答时选择推理模型(主要)模型概率
- model_normal_probability: float = 0.3 # 麦麦回答时选择一般模型(次要)模型概率
-
- emoji_chance: float = 0.2 # 发送表情包的基础概率
- thinking_timeout: int = 120 # 思考时间
-
- willing_mode: str = "classical" # 意愿模式
- response_willing_amplifier: float = 1.0 # 回复意愿放大系数
- response_interested_rate_amplifier: float = 1.0 # 回复兴趣度放大系数
- down_frequency_rate: float = 3 # 降低回复频率的群组回复意愿降低系数
- emoji_response_penalty: float = 0.0 # 表情包回复惩罚
- mentioned_bot_inevitable_reply: bool = False # 提及 bot 必然回复
- at_bot_inevitable_reply: bool = False # @bot 必然回复
-
- # emoji
- max_emoji_num: int = 200 # 表情包最大数量
- max_reach_deletion: bool = True # 开启则在达到最大数量时删除表情包，关闭则不会继续收集表情包
- EMOJI_CHECK_INTERVAL: int = 120 # 表情包检查间隔（分钟）
-
- save_pic: bool = False # 是否保存图片
- save_emoji: bool = False # 是否保存表情包
- steal_emoji: bool = True # 是否偷取表情包，让麦麦可以发送她保存的这些表情包
-
- EMOJI_CHECK: bool = False # 是否开启过滤
- EMOJI_CHECK_PROMPT: str = "符合公序良俗" # 表情包过滤要求
-
- # memory
- build_memory_interval: int = 600 # 记忆构建间隔（秒）
- memory_build_distribution: list = field(
- default_factory=lambda: [4, 2, 0.6, 24, 8, 0.4]
- ) # 记忆构建分布，参数：分布1均值，标准差，权重，分布2均值，标准差，权重
- build_memory_sample_num: int = 10 # 记忆构建采样数量
- build_memory_sample_length: int = 20 # 记忆构建采样长度
- memory_compress_rate: float = 0.1 # 记忆压缩率
-
- forget_memory_interval: int = 600 # 记忆遗忘间隔（秒）
- memory_forget_time: int = 24 # 记忆遗忘时间（小时）
- memory_forget_percentage: float = 0.01 # 记忆遗忘比例
-
- consolidate_memory_interval: int = 1000 # 记忆整合间隔（秒）
- consolidation_similarity_threshold: float = 0.7 # 相似度阈值
- consolidate_memory_percentage: float = 0.01 # 检查节点比例
-
- memory_ban_words: list = field(
- default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"]
- ) # 添加新的配置项默认值
-
- # mood
- mood_update_interval: float = 1.0 # 情绪更新间隔 单位秒
- mood_decay_rate: float = 0.95 # 情绪衰减率
- mood_intensity_factor: float = 0.7 # 情绪强度因子
-
- # keywords
- keywords_reaction_rules = [] # 关键词回复规则
-
- # chinese_typo
- chinese_typo_enable = True # 是否启用中文错别字生成器
- chinese_typo_error_rate = 0.03 # 单字替换概率
- chinese_typo_min_freq = 7 # 最小字频阈值
- chinese_typo_tone_error_rate = 0.2 # 声调错误概率
- chinese_typo_word_replace_rate = 0.02 # 整词替换概率
-
- # response_splitter
- enable_kaomoji_protection = False # 是否启用颜文字保护
- enable_response_splitter = True # 是否启用回复分割器
- response_max_length = 100 # 回复允许的最大长度
- response_max_sentence_num = 3 # 回复允许的最大句子数
-
- model_max_output_length: int = 800 # 最大回复长度
-
- # remote
- remote_enable: bool = True # 是否启用远程控制
-
- # experimental
- enable_friend_chat: bool = False # 是否启用好友聊天
- # enable_think_flow: bool = False # 是否启用思考流程
- talk_allowed_private = set()
- enable_pfc_chatting: bool = False # 是否启用PFC聊天
-
- # 模型配置
- llm_reasoning: dict[str, str] = field(default_factory=lambda: {})
- # llm_reasoning_minor: dict[str, str] = field(default_factory=lambda: {})
- llm_normal: Dict[str, str] = field(default_factory=lambda: {})
- llm_topic_judge: Dict[str, str] = field(default_factory=lambda: {})
- llm_summary: Dict[str, str] = field(default_factory=lambda: {})
- embedding: Dict[str, str] = field(default_factory=lambda: {})
- vlm: Dict[str, str] = field(default_factory=lambda: {})
- moderation: Dict[str, str] = field(default_factory=lambda: {})
-
- llm_observation: Dict[str, str] = field(default_factory=lambda: {})
- llm_sub_heartflow: Dict[str, str] = field(default_factory=lambda: {})
- llm_heartflow: Dict[str, str] = field(default_factory=lambda: {})
- llm_tool_use: Dict[str, str] = field(default_factory=lambda: {})
- llm_plan: Dict[str, str] = field(default_factory=lambda: {})
-
- api_urls: Dict[str, str] = field(default_factory=lambda: {})
-
- @staticmethod
- def get_config_dir() -> str:
- """获取配置文件目录"""
- current_dir = os.path.dirname(os.path.abspath(__file__))
- root_dir = os.path.abspath(os.path.join(current_dir, "..", ".."))
- config_dir = os.path.join(root_dir, "config")
- if not os.path.exists(config_dir):
- os.makedirs(config_dir)
- return config_dir
-
- @classmethod
- def convert_to_specifierset(cls, value: str) -> SpecifierSet:
- """将 字符串 版本表达式转换成 SpecifierSet
- Args:
- value[str]: 版本表达式(字符串)
- Returns:
- SpecifierSet
- """
-
- try:
- converted = SpecifierSet(value)
- except InvalidSpecifier:
- logger.error(f"{value} 分类使用了错误的版本约束表达式\n", "请阅读 https://semver.org/lang/zh-CN/ 修改代码")
- exit(1)
-
- return converted
-
- @classmethod
- def get_config_version(cls, toml: dict) -> Version:
- """提取配置文件的 SpecifierSet 版本数据
- Args:
- toml[dict]: 输入的配置文件字典
- Returns:
- Version
- """
-
- if "inner" in toml:
- try:
- config_version: str = toml["inner"]["version"]
- except KeyError as e:
- logger.error("配置文件中 inner 段 不存在, 这是错误的配置文件")
- raise KeyError(f"配置文件中 inner 段 不存在 {e}, 这是错误的配置文件") from e
- else:
- toml["inner"] = {"version": "0.0.0"}
- config_version = toml["inner"]["version"]
-
- try:
- ver = version.parse(config_version)
- except InvalidVersion as e:
- logger.error(
- "配置文件中 inner段 的 version 键是错误的版本描述\n"
- "请阅读 https://semver.org/lang/zh-CN/ 修改配置，并参考本项目指定的模板进行修改\n"
- "本项目在不同的版本下有不同的模板，请注意识别"
- )
- raise InvalidVersion("配置文件中 inner段 的 version 键是错误的版本描述\n") from e
-
- return ver
-
- @classmethod
- def load_config(cls, config_path: str = None) -> "BotConfig":
- """从TOML配置文件加载配置"""
- config = cls()
-
- def personality(parent: dict):
- personality_config = parent["personality"]
- if config.INNER_VERSION in SpecifierSet(">=1.2.4"):
- config.personality_core = personality_config.get("personality_core", config.personality_core)
- config.personality_sides = personality_config.get("personality_sides", config.personality_sides)
- if config.INNER_VERSION in SpecifierSet(">=1.7.0"):
- config.expression_style = personality_config.get("expression_style", config.expression_style)
-
- def identity(parent: dict):
- identity_config = parent["identity"]
- if config.INNER_VERSION in SpecifierSet(">=1.2.4"):
- config.identity_detail = identity_config.get("identity_detail", config.identity_detail)
- config.height = identity_config.get("height", config.height)
- config.weight = identity_config.get("weight", config.weight)
- config.age = identity_config.get("age", config.age)
- config.gender = identity_config.get("gender", config.gender)
- config.appearance = identity_config.get("appearance", config.appearance)
-
- def emoji(parent: dict):
- emoji_config = parent["emoji"]
- config.EMOJI_CHECK_INTERVAL = emoji_config.get("check_interval", config.EMOJI_CHECK_INTERVAL)
- config.EMOJI_CHECK_PROMPT = emoji_config.get("check_prompt", config.EMOJI_CHECK_PROMPT)
- config.EMOJI_CHECK = emoji_config.get("enable_check", config.EMOJI_CHECK)
- if config.INNER_VERSION in SpecifierSet(">=1.1.1"):
- config.max_emoji_num = emoji_config.get("max_emoji_num", config.max_emoji_num)
- config.max_reach_deletion = emoji_config.get("max_reach_deletion", config.max_reach_deletion)
- if config.INNER_VERSION in SpecifierSet(">=1.4.2"):
- config.save_pic = emoji_config.get("save_pic", config.save_pic)
- config.save_emoji = emoji_config.get("save_emoji", config.save_emoji)
- config.steal_emoji = emoji_config.get("steal_emoji", config.steal_emoji)
-
- def bot(parent: dict):
- # 机器人基础配置
- bot_config = parent["bot"]
- bot_qq = bot_config.get("qq")
- config.BOT_QQ = str(bot_qq)
- config.BOT_NICKNAME = bot_config.get("nickname", config.BOT_NICKNAME)
- config.BOT_ALIAS_NAMES = bot_config.get("alias_names", config.BOT_ALIAS_NAMES)
-
- def chat(parent: dict):
- chat_config = parent["chat"]
- config.allow_focus_mode = chat_config.get("allow_focus_mode", config.allow_focus_mode)
- config.base_normal_chat_num = chat_config.get("base_normal_chat_num", config.base_normal_chat_num)
- config.base_focused_chat_num = chat_config.get("base_focused_chat_num", config.base_focused_chat_num)
- config.observation_context_size = chat_config.get(
- "observation_context_size", config.observation_context_size
- )
- config.message_buffer = chat_config.get("message_buffer", config.message_buffer)
- config.ban_words = chat_config.get("ban_words", config.ban_words)
- for r in chat_config.get("ban_msgs_regex", config.ban_msgs_regex):
- config.ban_msgs_regex.add(re.compile(r))
-
- def normal_chat(parent: dict):
- normal_chat_config = parent["normal_chat"]
- config.model_reasoning_probability = normal_chat_config.get(
- "model_reasoning_probability", config.model_reasoning_probability
- )
- config.model_normal_probability = normal_chat_config.get(
- "model_normal_probability", config.model_normal_probability
- )
- config.emoji_chance = normal_chat_config.get("emoji_chance", config.emoji_chance)
- config.thinking_timeout = normal_chat_config.get("thinking_timeout", config.thinking_timeout)
-
- config.willing_mode = normal_chat_config.get("willing_mode", config.willing_mode)
- config.response_willing_amplifier = normal_chat_config.get(
- "response_willing_amplifier", config.response_willing_amplifier
- )
- config.response_interested_rate_amplifier = normal_chat_config.get(
- "response_interested_rate_amplifier", config.response_interested_rate_amplifier
- )
- config.down_frequency_rate = normal_chat_config.get("down_frequency_rate", config.down_frequency_rate)
- config.emoji_response_penalty = normal_chat_config.get(
- "emoji_response_penalty", config.emoji_response_penalty
- )
-
- config.mentioned_bot_inevitable_reply = normal_chat_config.get(
- "mentioned_bot_inevitable_reply", config.mentioned_bot_inevitable_reply
- )
- config.at_bot_inevitable_reply = normal_chat_config.get(
- "at_bot_inevitable_reply", config.at_bot_inevitable_reply
- )
-
- def focus_chat(parent: dict):
- focus_chat_config = parent["focus_chat"]
- config.compressed_length = focus_chat_config.get("compressed_length", config.compressed_length)
- config.compress_length_limit = focus_chat_config.get("compress_length_limit", config.compress_length_limit)
- config.reply_trigger_threshold = focus_chat_config.get(
- "reply_trigger_threshold", config.reply_trigger_threshold
- )
- config.default_decay_rate_per_second = focus_chat_config.get(
- "default_decay_rate_per_second", config.default_decay_rate_per_second
- )
- config.consecutive_no_reply_threshold = focus_chat_config.get(
- "consecutive_no_reply_threshold", config.consecutive_no_reply_threshold
- )
-
- def model(parent: dict):
- # 加载模型配置
- model_config: dict = parent["model"]
-
- config_list = [
- "llm_reasoning",
- # "llm_reasoning_minor",
- "llm_normal",
- "llm_topic_judge",
- "llm_summary",
- "vlm",
- "embedding",
- "llm_tool_use",
- "llm_observation",
- "llm_sub_heartflow",
- "llm_plan",
- "llm_heartflow",
- "llm_PFC_action_planner",
- "llm_PFC_chat",
- "llm_PFC_reply_checker",
- ]
-
- for item in config_list:
- if item in model_config:
- cfg_item: dict = model_config[item]
-
- # base_url 的例子： SILICONFLOW_BASE_URL
- # key 的例子： SILICONFLOW_KEY
- cfg_target = {
- "name": "",
- "base_url": "",
- "key": "",
- "stream": False,
- "pri_in": 0,
- "pri_out": 0,
- "temp": 0.7,
- }
-
- if config.INNER_VERSION in SpecifierSet("<=0.0.0"):
- cfg_target = cfg_item
-
- elif config.INNER_VERSION in SpecifierSet(">=0.0.1"):
- stable_item = ["name", "pri_in", "pri_out"]
-
- stream_item = ["stream"]
- if config.INNER_VERSION in SpecifierSet(">=1.0.1"):
- stable_item.append("stream")
-
- pricing_item = ["pri_in", "pri_out"]
-
- # 从配置中原始拷贝稳定字段
- for i in stable_item:
- # 如果 字段 属于计费项 且获取不到，那默认值是 0
- if i in pricing_item and i not in cfg_item:
- cfg_target[i] = 0
-
- if i in stream_item and i not in cfg_item:
- cfg_target[i] = False
-
- else:
- # 没有特殊情况则原样复制
- try:
- cfg_target[i] = cfg_item[i]
- except KeyError as e:
- logger.error(f"{item} 中的必要字段不存在，请检查")
- raise KeyError(f"{item} 中的必要字段 {e} 不存在，请检查") from e
-
- # 如果配置中有temp参数，就使用配置中的值
- if "temp" in cfg_item:
- cfg_target["temp"] = cfg_item["temp"]
- else:
- # 如果没有temp参数，就删除默认值
- cfg_target.pop("temp", None)
-
- provider = cfg_item.get("provider")
- if provider is None:
- logger.error(f"provider 字段在模型配置 {item} 中不存在，请检查")
- raise KeyError(f"provider 字段在模型配置 {item} 中不存在，请检查")
-
- cfg_target["base_url"] = f"{provider}_BASE_URL"
- cfg_target["key"] = f"{provider}_KEY"
-
- # 如果 列表中的项目在 model_config 中，利用反射来设置对应项目
- setattr(config, item, cfg_target)
- else:
- logger.error(f"模型 {item} 在config中不存在，请检查，或尝试更新配置文件")
- raise KeyError(f"模型 {item} 在config中不存在，请检查，或尝试更新配置文件")
-
- def memory(parent: dict):
- memory_config = parent["memory"]
- config.build_memory_interval = memory_config.get("build_memory_interval", config.build_memory_interval)
- config.forget_memory_interval = memory_config.get("forget_memory_interval", config.forget_memory_interval)
- config.memory_ban_words = set(memory_config.get("memory_ban_words", []))
- config.memory_forget_time = memory_config.get("memory_forget_time", config.memory_forget_time)
- config.memory_forget_percentage = memory_config.get(
- "memory_forget_percentage", config.memory_forget_percentage
- )
- config.memory_compress_rate = memory_config.get("memory_compress_rate", config.memory_compress_rate)
- if config.INNER_VERSION in SpecifierSet(">=0.0.11"):
- config.memory_build_distribution = memory_config.get(
- "memory_build_distribution", config.memory_build_distribution
- )
- config.build_memory_sample_num = memory_config.get(
- "build_memory_sample_num", config.build_memory_sample_num
- )
- config.build_memory_sample_length = memory_config.get(
- "build_memory_sample_length", config.build_memory_sample_length
- )
- if config.INNER_VERSION in SpecifierSet(">=1.5.1"):
- config.consolidate_memory_interval = memory_config.get(
- "consolidate_memory_interval", config.consolidate_memory_interval
- )
- config.consolidation_similarity_threshold = memory_config.get(
- "consolidation_similarity_threshold", config.consolidation_similarity_threshold
- )
- config.consolidate_memory_percentage = memory_config.get(
- "consolidate_memory_percentage", config.consolidate_memory_percentage
- )
-
- def remote(parent: dict):
- remote_config = parent["remote"]
- config.remote_enable = remote_config.get("enable", config.remote_enable)
-
- def mood(parent: dict):
- mood_config = parent["mood"]
- config.mood_update_interval = mood_config.get("mood_update_interval", config.mood_update_interval)
- config.mood_decay_rate = mood_config.get("mood_decay_rate", config.mood_decay_rate)
- config.mood_intensity_factor = mood_config.get("mood_intensity_factor", config.mood_intensity_factor)
-
- def keywords_reaction(parent: dict):
- keywords_reaction_config = parent["keywords_reaction"]
- if keywords_reaction_config.get("enable", False):
- config.keywords_reaction_rules = keywords_reaction_config.get("rules", config.keywords_reaction_rules)
- for rule in config.keywords_reaction_rules:
- if rule.get("enable", False) and "regex" in rule:
- rule["regex"] = [re.compile(r) for r in rule.get("regex", [])]
-
- def chinese_typo(parent: dict):
- chinese_typo_config = parent["chinese_typo"]
- config.chinese_typo_enable = chinese_typo_config.get("enable", config.chinese_typo_enable)
- config.chinese_typo_error_rate = chinese_typo_config.get("error_rate", config.chinese_typo_error_rate)
- config.chinese_typo_min_freq = chinese_typo_config.get("min_freq", config.chinese_typo_min_freq)
- config.chinese_typo_tone_error_rate = chinese_typo_config.get(
- "tone_error_rate", config.chinese_typo_tone_error_rate
- )
- config.chinese_typo_word_replace_rate = chinese_typo_config.get(
- "word_replace_rate", config.chinese_typo_word_replace_rate
- )
-
- def response_splitter(parent: dict):
- response_splitter_config = parent["response_splitter"]
- config.enable_response_splitter = response_splitter_config.get(
- "enable_response_splitter", config.enable_response_splitter
- )
- config.response_max_length = response_splitter_config.get("response_max_length", config.response_max_length)
- config.response_max_sentence_num = response_splitter_config.get(
- "response_max_sentence_num", config.response_max_sentence_num
- )
- if config.INNER_VERSION in SpecifierSet(">=1.4.2"):
- config.enable_kaomoji_protection = response_splitter_config.get(
- "enable_kaomoji_protection", config.enable_kaomoji_protection
- )
- if config.INNER_VERSION in SpecifierSet(">=1.6.0"):
- config.model_max_output_length = response_splitter_config.get(
- "model_max_output_length", config.model_max_output_length
- )
-
- def groups(parent: dict):
- groups_config = parent["groups"]
- # config.talk_allowed_groups = set(groups_config.get("talk_allowed", []))
- config.talk_allowed_groups = set(str(group) for group in groups_config.get("talk_allowed", []))
- # config.talk_frequency_down_groups = set(groups_config.get("talk_frequency_down", []))
- config.talk_frequency_down_groups = set(
- str(group) for group in groups_config.get("talk_frequency_down", [])
- )
- # config.ban_user_id = set(groups_config.get("ban_user_id", []))
- config.ban_user_id = set(str(user) for user in groups_config.get("ban_user_id", []))
-
- def experimental(parent: dict):
- experimental_config = parent["experimental"]
- config.enable_friend_chat = experimental_config.get("enable_friend_chat", config.enable_friend_chat)
- # config.enable_think_flow = experimental_config.get("enable_think_flow", config.enable_think_flow)
- config.talk_allowed_private = set(str(user) for user in experimental_config.get("talk_allowed_private", []))
- if config.INNER_VERSION in SpecifierSet(">=1.1.0"):
- config.enable_pfc_chatting = experimental_config.get("pfc_chatting", config.enable_pfc_chatting)
-
- # 版本表达式：>=1.0.0,<2.0.0
- # 允许字段：func: method, support: str, notice: str, necessary: bool
- # 如果使用 notice 字段，在该组配置加载时，会展示该字段对用户的警示
- # 例如："notice": "personality 将在 1.3.2 后被移除"，那么在有效版本中的用户就会虽然可以
- # 正常执行程序，但是会看到这条自定义提示
-
- # 版本格式：主版本号.次版本号.修订号，版本号递增规则如下：
- # 主版本号：当你做了不兼容的 API 修改，
- # 次版本号：当你做了向下兼容的功能性新增，
- # 修订号：当你做了向下兼容的问题修正。
- # 先行版本号及版本编译信息可以加到"主版本号.次版本号.修订号"的后面，作为延伸。
-
- # 如果你做了break的修改，就应该改动主版本号
- # 如果做了一个兼容修改，就不应该要求这个选项是必须的！
- include_configs = {
- "bot": {"func": bot, "support": ">=0.0.0"},
- "groups": {"func": groups, "support": ">=0.0.0"},
- "personality": {"func": personality, "support": ">=0.0.0"},
- "identity": {"func": identity, "support": ">=1.2.4"},
- "emoji": {"func": emoji, "support": ">=0.0.0"},
- "model": {"func": model, "support": ">=0.0.0"},
- "memory": {"func": memory, "support": ">=0.0.0", "necessary": False},
- "mood": {"func": mood, "support": ">=0.0.0"},
- "remote": {"func": remote, "support": ">=0.0.10", "necessary": False},
- "keywords_reaction": {"func": keywords_reaction, "support": ">=0.0.2", "necessary": False},
- "chinese_typo": {"func": chinese_typo, "support": ">=0.0.3", "necessary": False},
- "response_splitter": {"func": response_splitter, "support": ">=0.0.11", "necessary": False},
- "experimental": {"func": experimental, "support": ">=0.0.11", "necessary": False},
- "chat": {"func": chat, "support": ">=1.6.0", "necessary": False},
- "normal_chat": {"func": normal_chat, "support": ">=1.6.0", "necessary": False},
- "focus_chat": {"func": focus_chat, "support": ">=1.6.0", "necessary": False},
- }
-
- # 原地修改，将 字符串版本表达式 转换成 版本对象
- for key in include_configs:
- item_support = include_configs[key]["support"]
- include_configs[key]["support"] = cls.convert_to_specifierset(item_support)
-
- if os.path.exists(config_path):
- with open(config_path, "rb") as f:
- try:
- toml_dict = tomli.load(f)
- except tomli.TOMLDecodeError as e:
- logger.critical(f"配置文件bot_config.toml填写有误，请检查第{e.lineno}行第{e.colno}处：{e.msg}")
- exit(1)
-
- # 获取配置文件版本
- config.INNER_VERSION = cls.get_config_version(toml_dict)
-
- # 如果在配置中找到了需要的项，调用对应项的闭包函数处理
- for key in include_configs:
- if key in toml_dict:
- group_specifierset: SpecifierSet = include_configs[key]["support"]
-
- # 检查配置文件版本是否在支持范围内
- if config.INNER_VERSION in group_specifierset:
- # 如果版本在支持范围内，检查是否存在通知
- if "notice" in include_configs[key]:
- logger.warning(include_configs[key]["notice"])
-
- include_configs[key]["func"](toml_dict)
-
- else:
- # 如果版本不在支持范围内，崩溃并提示用户
- logger.error(
- f"配置文件中的 '{key}' 字段的版本 ({config.INNER_VERSION}) 不在支持范围内。\n"
- f"当前程序仅支持以下版本范围: {group_specifierset}"
- )
- raise InvalidVersion(f"当前程序仅支持以下版本范围: {group_specifierset}")
-
- # 如果 necessary 项目存在，而且显式声明是 False，进入特殊处理
- elif "necessary" in include_configs[key] and include_configs[key].get("necessary") is False:
- # 通过 pass 处理的项虽然直接忽略也是可以的，但是为了不增加理解困难，依然需要在这里显式处理
- if key == "keywords_reaction":
- pass
-
- else:
- # 如果用户根本没有需要的配置项，提示缺少配置
- logger.error(f"配置文件中缺少必需的字段: '{key}'")
- raise KeyError(f"配置文件中缺少必需的字段: '{key}'")
-
- # identity_detail字段非空检查
- if not config.identity_detail:
- logger.error("配置文件错误：[identity] 部分的 identity_detail 不能为空字符串")
- raise ValueError("配置文件错误：[identity] 部分的 identity_detail 不能为空字符串")
-
- logger.success(f"成功加载配置文件: {config_path}")
-
- return config
+class Config(ConfigBase):
+ """总配置类"""
+
+ MMC_VERSION: str = field(default=MMC_VERSION, repr=False, init=False) # 硬编码的版本信息
+
+ bot: BotConfig
+ chat_target: ChatTargetConfig
+ personality: PersonalityConfig
+ identity: IdentityConfig
+ platforms: PlatformsConfig
+ chat: ChatConfig
+ normal_chat: NormalChatConfig
+ focus_chat: FocusChatConfig
+ emoji: EmojiConfig
+ memory: MemoryConfig
+ mood: MoodConfig
+ keyword_reaction: KeywordReactionConfig
+ chinese_typo: ChineseTypoConfig
+ response_splitter: ResponseSplitterConfig
+ telemetry: TelemetryConfig
+ experimental: ExperimentalConfig
+ model: ModelConfig
+
+
+def load_config(config_path: str) -> Config:
+ """
+ 加载配置文件
+ :param config_path: 配置文件路径
+ :return: Config对象
+ """
+ # 读取配置文件
+ with open(config_path, "r", encoding="utf-8") as f:
+ config_data = tomlkit.load(f)
+
+ # 创建Config对象
+ try:
+ return Config.from_dict(config_data)
+ except Exception as e:
+ logger.critical("配置文件解析失败")
+ raise e
# 获取配置文件路径
-logger.info(f"MaiCore当前版本: {mai_version}")
+logger.info(f"MaiCore当前版本: {MMC_VERSION}")
update_config()
-bot_config_floder_path = BotConfig.get_config_dir()
-logger.info(f"正在品鉴配置文件目录: {bot_config_floder_path}")
-
-bot_config_path = os.path.join(bot_config_floder_path, "bot_config.toml")
-
-if os.path.exists(bot_config_path):
- # 如果开发环境配置文件不存在，则使用默认配置文件
- logger.info(f"异常的新鲜，异常的美味: {bot_config_path}")
-else:
- # 配置文件不存在
- logger.error("配置文件不存在，请检查路径: {bot_config_path}")
- raise FileNotFoundError(f"配置文件不存在: {bot_config_path}")
-
-global_config = BotConfig.load_config(config_path=bot_config_path)
+logger.info("正在品鉴配置文件...")
+global_config = load_config(config_path=f"{CONFIG_DIR}/bot_config.toml")
+logger.info("非常的新鲜，非常的美味！")
diff --git a/src/config/config_base.py b/src/config/config_base.py
new file mode 100644
index 000000000..92f6cf9d4
--- /dev/null
+++ b/src/config/config_base.py
@@ -0,0 +1,116 @@
+from dataclasses import dataclass, fields, MISSING
+from typing import TypeVar, Type, Any, get_origin, get_args
+
+T = TypeVar("T", bound="ConfigBase")
+
+TOML_DICT_TYPE = {
+ int,
+ float,
+ str,
+ bool,
+ list,
+ dict,
+}
+
+
+@dataclass
+class ConfigBase:
+ """配置类的基类"""
+
+ @classmethod
+ def from_dict(cls: Type[T], data: dict[str, Any]) -> T:
+ """从字典加载配置字段"""
+ if not isinstance(data, dict):
+ raise TypeError(f"Expected a dictionary, got {type(data).__name__}")
+
+ init_args: dict[str, Any] = {}
+
+ for f in fields(cls):
+ field_name = f.name
+
+ if field_name.startswith("_"):
+ # 跳过以 _ 开头的字段
+ continue
+
+ if field_name not in data:
+ if f.default is not MISSING or f.default_factory is not MISSING:
+ # 跳过未提供且有默认值/默认构造方法的字段
+ continue
+ else:
+ raise ValueError(f"Missing required field: '{field_name}'")
+
+ value = data[field_name]
+ field_type = f.type
+
+ try:
+ init_args[field_name] = cls._convert_field(value, field_type)
+ except TypeError as e:
+ raise TypeError(f"Field '{field_name}' has a type error: {e}") from e
+ except Exception as e:
+ raise RuntimeError(f"Failed to convert field '{field_name}' to target type: {e}") from e
+
+ return cls(**init_args)
+
+ @classmethod
+ def _convert_field(cls, value: Any, field_type: Type[Any]) -> Any:
+ """
+ 转换字段值为指定类型
+
+ 1. 对于嵌套的 dataclass，递归调用相应的 from_dict 方法
+ 2. 对于泛型集合类型（list, set, tuple），递归转换每个元素
+ 3. 对于基础类型（int, str, float, bool），直接转换
+ 4. 对于其他类型，尝试直接转换，如果失败则抛出异常
+ """
+
+ # 如果是嵌套的 dataclass，递归调用 from_dict 方法
+ if isinstance(field_type, type) and issubclass(field_type, ConfigBase):
+ if not isinstance(value, dict):
+ raise TypeError(f"Expected a dictionary for {field_type.__name__}, got {type(value).__name__}")
+ return field_type.from_dict(value)
+
+ # 处理泛型集合类型（list, set, tuple）
+ field_origin_type = get_origin(field_type)
+ field_type_args = get_args(field_type)
+
+ if field_origin_type in {list, set, tuple}:
+ # 检查提供的value是否为list
+ if not isinstance(value, list):
+ raise TypeError(f"Expected an list for {field_type.__name__}, got {type(value).__name__}")
+
+ if field_origin_type is list:
+ return [cls._convert_field(item, field_type_args[0]) for item in value]
+ elif field_origin_type is set:
+ return {cls._convert_field(item, field_type_args[0]) for item in value}
+ elif field_origin_type is tuple:
+ # 检查提供的value长度是否与类型参数一致
+ if len(value) != len(field_type_args):
+ raise TypeError(
+ f"Expected {len(field_type_args)} items for {field_type.__name__}, got {len(value)}"
+ )
+ return tuple(cls._convert_field(item, arg) for item, arg in zip(value, field_type_args))
+
+ if field_origin_type is dict:
+ # 检查提供的value是否为dict
+ if not isinstance(value, dict):
+ raise TypeError(f"Expected a dictionary for {field_type.__name__}, got {type(value).__name__}")
+
+ # 检查字典的键值类型
+ if len(field_type_args) != 2:
+ raise TypeError(f"Expected a dictionary with two type arguments for {field_type.__name__}")
+ key_type, value_type = field_type_args
+
+ return {cls._convert_field(k, key_type): cls._convert_field(v, value_type) for k, v in value.items()}
+
+ # 处理基础类型，例如 int, str 等
+ if field_type is Any or isinstance(value, field_type):
+ return value
+
+ # 其他类型，尝试直接转换
+ try:
+ return field_type(value)
+ except (ValueError, TypeError) as e:
+ raise TypeError(f"Cannot convert {type(value).__name__} to {field_type.__name__}") from e
+
+ def __str__(self):
+ """返回配置类的字符串表示"""
+ return f"{self.__class__.__name__}({', '.join(f'{f.name}={getattr(self, f.name)}' for f in fields(self))})"
diff --git a/src/config/official_configs.py b/src/config/official_configs.py
new file mode 100644
index 000000000..d92d925d6
--- /dev/null
+++ b/src/config/official_configs.py
@@ -0,0 +1,399 @@
+from dataclasses import dataclass, field
+from typing import Any
+
+from src.config.config_base import ConfigBase
+
+"""
+须知：
+1. 本文件中记录了所有的配置项
+2. 所有新增的class都需要继承自ConfigBase
+3. 所有新增的class都应在config.py中的Config类中添加字段
+4. 对于新增的字段，若为可选项，则应在其后添加field()并设置default_factory或default
+"""
+
+
+@dataclass
+class BotConfig(ConfigBase):
+ """QQ机器人配置类"""
+
+ qq_account: str
+ """QQ账号"""
+
+ nickname: str
+ """昵称"""
+
+ alias_names: list[str] = field(default_factory=lambda: [])
+ """别名列表"""
+
+
+@dataclass
+class ChatTargetConfig(ConfigBase):
+ """
+ 聊天目标配置类
+ 此类中有聊天的群组和用户配置
+ """
+
+ talk_allowed_groups: set[str] = field(default_factory=lambda: set())
+ """允许聊天的群组列表"""
+
+ talk_frequency_down_groups: set[str] = field(default_factory=lambda: set())
+ """降低聊天频率的群组列表"""
+
+ ban_user_id: set[str] = field(default_factory=lambda: set())
+ """禁止聊天的用户列表"""
+
+
+@dataclass
+class PersonalityConfig(ConfigBase):
+ """人格配置类"""
+
+ personality_core: str
+ """核心人格"""
+
+ expression_style: str
+ """表达风格"""
+
+ personality_sides: list[str] = field(default_factory=lambda: [])
+ """人格侧写"""
+
+
+@dataclass
+class IdentityConfig(ConfigBase):
+ """个体特征配置类"""
+
+ height: int = 170
+ """身高（单位：厘米）"""
+
+ weight: float = 50
+ """体重（单位：千克）"""
+
+ age: int = 18
+ """年龄（单位：岁）"""
+
+ gender: str = "女"
+ """性别（男/女）"""
+
+ appearance: str = "可爱"
+ """外貌描述"""
+
+ identity_detail: list[str] = field(default_factory=lambda: [])
+ """身份特征"""
+
+
+@dataclass
+class PlatformsConfig(ConfigBase):
+ """平台配置类"""
+
+ qq: str
+ """QQ适配器连接URL配置"""
+
+
+@dataclass
+class ChatConfig(ConfigBase):
+ """聊天配置类"""
+
+ allow_focus_mode: bool = True
+ """是否允许专注聊天状态"""
+
+ base_normal_chat_num: int = 3
+ """最多允许多少个群进行普通聊天"""
+
+ base_focused_chat_num: int = 2
+ """最多允许多少个群进行专注聊天"""
+
+ observation_context_size: int = 12
+ """可观察到的最长上下文大小，超过这个值的上下文会被压缩"""
+
+ message_buffer: bool = True
+ """消息缓冲器"""
+
+ ban_words: set[str] = field(default_factory=lambda: set())
+ """过滤词列表"""
+
+ ban_msgs_regex: set[str] = field(default_factory=lambda: set())
+ """过滤正则表达式列表"""
+
+
+@dataclass
+class NormalChatConfig(ConfigBase):
+ """普通聊天配置类"""
+
+ reasoning_model_probability: float = 0.3
+ """
+ 发言时选择推理模型的概率（0-1之间）
+ 选择普通模型的概率为 1 - reasoning_normal_model_probability
+ """
+
+ emoji_chance: float = 0.2
+ """发送表情包的基础概率"""
+
+ thinking_timeout: int = 120
+ """最长思考时间"""
+
+ willing_mode: str = "classical"
+ """意愿模式"""
+
+ response_willing_amplifier: float = 1.0
+ """回复意愿放大系数"""
+
+ response_interested_rate_amplifier: float = 1.0
+ """回复兴趣度放大系数"""
+
+ down_frequency_rate: float = 3.0
+ """降低回复频率的群组回复意愿降低系数"""
+
+ emoji_response_penalty: float = 0.0
+ """表情包回复惩罚系数"""
+
+ mentioned_bot_inevitable_reply: bool = False
+ """提及 bot 必然回复"""
+
+ at_bot_inevitable_reply: bool = False
+ """@bot 必然回复"""
+
+
+@dataclass
+class FocusChatConfig(ConfigBase):
+ """专注聊天配置类"""
+
+ reply_trigger_threshold: float = 3.0
+ """心流聊天触发阈值，越低越容易触发"""
+
+ default_decay_rate_per_second: float = 0.98
+ """默认衰减率，越大衰减越快"""
+
+ consecutive_no_reply_threshold: int = 3
+ """连续不回复的次数阈值"""
+
+ compressed_length: int = 5
+ """心流上下文压缩的最短压缩长度，超过心流观察到的上下文长度，会压缩，最短压缩长度为5"""
+
+ compress_length_limit: int = 5
+ """最多压缩份数，超过该数值的压缩上下文会被删除"""
+
+
+@dataclass
+class EmojiConfig(ConfigBase):
+ """表情包配置类"""
+
+ max_reg_num: int = 200
+ """表情包最大注册数量"""
+
+ do_replace: bool = True
+ """达到最大注册数量时替换旧表情包"""
+
+ check_interval: int = 120
+ """表情包检查间隔（分钟）"""
+
+ save_pic: bool = False
+ """是否保存图片"""
+
+ cache_emoji: bool = True
+ """是否缓存表情包"""
+
+ steal_emoji: bool = True
+ """是否偷取表情包，让麦麦可以发送她保存的这些表情包"""
+
+ content_filtration: bool = False
+ """是否开启表情包过滤"""
+
+ filtration_prompt: str = "符合公序良俗"
+ """表情包过滤要求"""
+
+
+@dataclass
+class MemoryConfig(ConfigBase):
+ """记忆配置类"""
+
+ memory_build_interval: int = 600
+ """记忆构建间隔（秒）"""
+
+ memory_build_distribution: tuple[
+ float,
+ float,
+ float,
+ float,
+ float,
+ float,
+ ] = field(default_factory=lambda: (6.0, 3.0, 0.6, 32.0, 12.0, 0.4))
+ """记忆构建分布，参数：分布1均值，标准差，权重，分布2均值，标准差，权重"""
+
+ memory_build_sample_num: int = 8
+ """记忆构建采样数量"""
+
+ memory_build_sample_length: int = 40
+ """记忆构建采样长度"""
+
+ memory_compress_rate: float = 0.1
+ """记忆压缩率"""
+
+ forget_memory_interval: int = 1000
+ """记忆遗忘间隔（秒）"""
+
+ memory_forget_time: int = 24
+ """记忆遗忘时间（小时）"""
+
+ memory_forget_percentage: float = 0.01
+ """记忆遗忘比例"""
+
+ consolidate_memory_interval: int = 1000
+ """记忆整合间隔（秒）"""
+
+ consolidation_similarity_threshold: float = 0.7
+ """整合相似度阈值"""
+
+ consolidate_memory_percentage: float = 0.01
+ """整合检查节点比例"""
+
+ memory_ban_words: list[str] = field(default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"])
+ """不允许记忆的词列表"""
+
+
+@dataclass
+class MoodConfig(ConfigBase):
+ """情绪配置类"""
+
+ mood_update_interval: int = 1
+ """情绪更新间隔（秒）"""
+
+ mood_decay_rate: float = 0.95
+ """情绪衰减率"""
+
+ mood_intensity_factor: float = 0.7
+ """情绪强度因子"""
+
+
+@dataclass
+class KeywordRuleConfig(ConfigBase):
+ """关键词规则配置类"""
+
+ enable: bool = True
+ """是否启用关键词规则"""
+
+ keywords: list[str] = field(default_factory=lambda: [])
+ """关键词列表"""
+
+ regex: list[str] = field(default_factory=lambda: [])
+ """正则表达式列表"""
+
+ reaction: str = ""
+ """关键词触发的反应"""
+
+
+@dataclass
+class KeywordReactionConfig(ConfigBase):
+ """关键词配置类"""
+
+ enable: bool = True
+ """是否启用关键词反应"""
+
+ rules: list[KeywordRuleConfig] = field(default_factory=lambda: [])
+ """关键词反应规则列表"""
+
+
+@dataclass
+class ChineseTypoConfig(ConfigBase):
+ """中文错别字配置类"""
+
+ enable: bool = True
+ """是否启用中文错别字生成器"""
+
+ error_rate: float = 0.01
+ """单字替换概率"""
+
+ min_freq: int = 9
+ """最小字频阈值"""
+
+ tone_error_rate: float = 0.1
+ """声调错误概率"""
+
+ word_replace_rate: float = 0.006
+ """整词替换概率"""
+
+
+@dataclass
+class ResponseSplitterConfig(ConfigBase):
+ """回复分割器配置类"""
+
+ enable: bool = True
+ """是否启用回复分割器"""
+
+ max_length: int = 256
+ """回复允许的最大长度"""
+
+ max_sentence_num: int = 3
+ """回复允许的最大句子数"""
+
+ enable_kaomoji_protection: bool = False
+ """是否启用颜文字保护"""
+
+
+@dataclass
+class TelemetryConfig(ConfigBase):
+ """遥测配置类"""
+
+ enable: bool = True
+ """是否启用遥测"""
+
+
+@dataclass
+class ExperimentalConfig(ConfigBase):
+ """实验功能配置类"""
+
+ enable_friend_chat: bool = False
+ """是否启用好友聊天"""
+
+ talk_allowed_private: set[str] = field(default_factory=lambda: set())
+ """允许聊天的私聊列表"""
+
+ pfc_chatting: bool = False
+ """是否启用PFC"""
+
+
+@dataclass
+class ModelConfig(ConfigBase):
+ """模型配置类"""
+
+ model_max_output_length: int = 800 # 最大回复长度
+
+ reasoning: dict[str, Any] = field(default_factory=lambda: {})
+ """推理模型配置"""
+
+ normal: dict[str, Any] = field(default_factory=lambda: {})
+ """普通模型配置"""
+
+ topic_judge: dict[str, Any] = field(default_factory=lambda: {})
+ """主题判断模型配置"""
+
+ summary: dict[str, Any] = field(default_factory=lambda: {})
+ """摘要模型配置"""
+
+ vlm: dict[str, Any] = field(default_factory=lambda: {})
+ """视觉语言模型配置"""
+
+ heartflow: dict[str, Any] = field(default_factory=lambda: {})
+ """心流模型配置"""
+
+ observation: dict[str, Any] = field(default_factory=lambda: {})
+ """观察模型配置"""
+
+ sub_heartflow: dict[str, Any] = field(default_factory=lambda: {})
+ """子心流模型配置"""
+
+ plan: dict[str, Any] = field(default_factory=lambda: {})
+ """计划模型配置"""
+
+ embedding: dict[str, Any] = field(default_factory=lambda: {})
+ """嵌入模型配置"""
+
+ pfc_action_planner: dict[str, Any] = field(default_factory=lambda: {})
+ """PFC动作规划模型配置"""
+
+ pfc_chat: dict[str, Any] = field(default_factory=lambda: {})
+ """PFC聊天模型配置"""
+
+ pfc_reply_checker: dict[str, Any] = field(default_factory=lambda: {})
+ """PFC回复检查模型配置"""
+
+ tool_use: dict[str, Any] = field(default_factory=lambda: {})
+ """工具使用模型配置"""
diff --git a/src/experimental/PFC/action_planner.py b/src/experimental/PFC/action_planner.py
index b4182c9aa..c0bff5887 100644
--- a/src/experimental/PFC/action_planner.py
+++ b/src/experimental/PFC/action_planner.py
@@ -114,7 +114,7 @@ class ActionPlanner:
request_type="action_planning",
)
self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
- self.name = global_config.BOT_NICKNAME
+ self.name = global_config.bot.nickname
self.private_name = private_name
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
# self.action_planner_info = ActionPlannerInfo() # 移除未使用的变量
@@ -140,7 +140,7 @@ class ActionPlanner:
# (这部分逻辑不变)
time_since_last_bot_message_info = ""
try:
- bot_id = str(global_config.BOT_QQ)
+ bot_id = str(global_config.bot.qq_account)
if hasattr(observation_info, "chat_history") and observation_info.chat_history:
for i in range(len(observation_info.chat_history) - 1, -1, -1):
msg = observation_info.chat_history[i]
diff --git a/src/experimental/PFC/chat_observer.py b/src/experimental/PFC/chat_observer.py
index e9e64053f..55914d800 100644
--- a/src/experimental/PFC/chat_observer.py
+++ b/src/experimental/PFC/chat_observer.py
@@ -323,7 +323,7 @@ class ChatObserver:
for msg in messages:
try:
user_info = UserInfo.from_dict(msg.get("user_info", {}))
- if user_info.user_id == global_config.BOT_QQ:
+ if user_info.user_id == global_config.bot.qq_account:
self.update_bot_speak_time(msg["time"])
else:
self.update_user_speak_time(msg["time"])
diff --git a/src/experimental/PFC/message_sender.py b/src/experimental/PFC/message_sender.py
index 181bf171b..4b193a41d 100644
--- a/src/experimental/PFC/message_sender.py
+++ b/src/experimental/PFC/message_sender.py
@@ -42,8 +42,8 @@ class DirectMessageSender:
# 获取麦麦的信息
bot_user_info = UserInfo(
- user_id=global_config.BOT_QQ,
- user_nickname=global_config.BOT_NICKNAME,
+ user_id=global_config.bot.qq_account,
+ user_nickname=global_config.bot.nickname,
platform=chat_stream.platform,
)
diff --git a/src/experimental/PFC/pfc.py b/src/experimental/PFC/pfc.py
index 84fb9f8dc..686d4af49 100644
--- a/src/experimental/PFC/pfc.py
+++ b/src/experimental/PFC/pfc.py
@@ -42,13 +42,14 @@ class GoalAnalyzer:
"""对话目标分析器"""
def __init__(self, stream_id: str, private_name: str):
+ # TODO: API-Adapter修改标记
self.llm = LLMRequest(
- model=global_config.llm_normal, temperature=0.7, max_tokens=1000, request_type="conversation_goal"
+ model=global_config.model.normal, temperature=0.7, max_tokens=1000, request_type="conversation_goal"
)
self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
- self.name = global_config.BOT_NICKNAME
- self.nick_name = global_config.BOT_ALIAS_NAMES
+ self.name = global_config.bot.nickname
+ self.nick_name = global_config.bot.alias_names
self.private_name = private_name
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
diff --git a/src/experimental/PFC/pfc_KnowledgeFetcher.py b/src/experimental/PFC/pfc_KnowledgeFetcher.py
index 8ebc307e2..4c1d8c759 100644
--- a/src/experimental/PFC/pfc_KnowledgeFetcher.py
+++ b/src/experimental/PFC/pfc_KnowledgeFetcher.py
@@ -14,9 +14,10 @@ class KnowledgeFetcher:
"""知识调取器"""
def __init__(self, private_name: str):
+ # TODO: API-Adapter修改标记
self.llm = LLMRequest(
- model=global_config.llm_normal,
- temperature=global_config.llm_normal["temp"],
+ model=global_config.model.normal,
+ temperature=global_config.model.normal["temp"],
max_tokens=1000,
request_type="knowledge_fetch",
)
diff --git a/src/experimental/PFC/reply_checker.py b/src/experimental/PFC/reply_checker.py
index a76e8a0da..5bca9d601 100644
--- a/src/experimental/PFC/reply_checker.py
+++ b/src/experimental/PFC/reply_checker.py
@@ -16,7 +16,7 @@ class ReplyChecker:
self.llm = LLMRequest(
model=global_config.llm_PFC_reply_checker, temperature=0.50, max_tokens=1000, request_type="reply_check"
)
- self.name = global_config.BOT_NICKNAME
+ self.name = global_config.bot.nickname
self.private_name = private_name
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
self.max_retries = 3 # 最大重试次数
@@ -43,7 +43,7 @@ class ReplyChecker:
bot_messages = []
for msg in reversed(chat_history):
user_info = UserInfo.from_dict(msg.get("user_info", {}))
- if str(user_info.user_id) == str(global_config.BOT_QQ): # 确保比较的是字符串
+ if str(user_info.user_id) == str(global_config.bot.qq_account): # 确保比较的是字符串
bot_messages.append(msg.get("processed_plain_text", ""))
if len(bot_messages) >= 2: # 只和最近的两条比较
break
diff --git a/src/experimental/PFC/reply_generator.py b/src/experimental/PFC/reply_generator.py
index 6dcda69af..bac8a769f 100644
--- a/src/experimental/PFC/reply_generator.py
+++ b/src/experimental/PFC/reply_generator.py
@@ -93,7 +93,7 @@ class ReplyGenerator:
request_type="reply_generation",
)
self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
- self.name = global_config.BOT_NICKNAME
+ self.name = global_config.bot.nickname
self.private_name = private_name
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
self.reply_checker = ReplyChecker(stream_id, private_name)
diff --git a/src/experimental/PFC/waiter.py b/src/experimental/PFC/waiter.py
index af5cf7ad0..452446589 100644
--- a/src/experimental/PFC/waiter.py
+++ b/src/experimental/PFC/waiter.py
@@ -19,7 +19,7 @@ class Waiter:
def __init__(self, stream_id: str, private_name: str):
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
- self.name = global_config.BOT_NICKNAME
+ self.name = global_config.bot.nickname
self.private_name = private_name
# self.wait_accumulated_time = 0 # 不再需要累加计时
diff --git a/src/experimental/only_message_process.py b/src/experimental/only_message_process.py
index 3d1432703..62f73c700 100644
--- a/src/experimental/only_message_process.py
+++ b/src/experimental/only_message_process.py
@@ -16,7 +16,7 @@ class MessageProcessor:
@staticmethod
def _check_ban_words(text: str, chat, userinfo) -> bool:
"""检查消息中是否包含过滤词"""
- for word in global_config.ban_words:
+ for word in global_config.chat.ban_words:
if word in text:
logger.info(
f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{text}"
@@ -28,7 +28,7 @@ class MessageProcessor:
@staticmethod
def _check_ban_regex(text: str, chat, userinfo) -> bool:
"""检查消息是否匹配过滤正则表达式"""
- for pattern in global_config.ban_msgs_regex:
+ for pattern in global_config.chat.ban_msgs_regex:
if pattern.search(text):
logger.info(
f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{text}"
diff --git a/src/main.py b/src/main.py
index 34b7eda3d..4f8af28ef 100644
--- a/src/main.py
+++ b/src/main.py
@@ -40,7 +40,7 @@ class MainSystem:
async def initialize(self):
"""初始化系统组件"""
- logger.debug(f"正在唤醒{global_config.BOT_NICKNAME}......")
+ logger.debug(f"正在唤醒{global_config.bot.nickname}......")
# 其他初始化任务
await asyncio.gather(self._init_components())
@@ -84,7 +84,7 @@ class MainSystem:
asyncio.create_task(chat_manager._auto_save_task())
# 使用HippocampusManager初始化海马体
- self.hippocampus_manager.initialize(global_config=global_config)
+ self.hippocampus_manager.initialize()
# await asyncio.sleep(0.5) #防止logger输出飞了
# 将bot.py中的chat_bot.message_process消息处理函数注册到api.py的消息处理基类中
@@ -92,15 +92,15 @@ class MainSystem:
# 初始化个体特征
self.individuality.initialize(
- bot_nickname=global_config.BOT_NICKNAME,
- personality_core=global_config.personality_core,
- personality_sides=global_config.personality_sides,
- identity_detail=global_config.identity_detail,
- height=global_config.height,
- weight=global_config.weight,
- age=global_config.age,
- gender=global_config.gender,
- appearance=global_config.appearance,
+ bot_nickname=global_config.bot.nickname,
+ personality_core=global_config.personality.personality_core,
+ personality_sides=global_config.personality.personality_sides,
+ identity_detail=global_config.identity.identity_detail,
+ height=global_config.identity.height,
+ weight=global_config.identity.weight,
+ age=global_config.identity.age,
+ gender=global_config.identity.gender,
+ appearance=global_config.identity.appearance,
)
logger.success("个体特征初始化成功")
@@ -141,7 +141,7 @@ class MainSystem:
async def build_memory_task():
"""记忆构建任务"""
while True:
- await asyncio.sleep(global_config.build_memory_interval)
+ await asyncio.sleep(global_config.memory.memory_build_interval)
logger.info("正在进行记忆构建")
await HippocampusManager.get_instance().build_memory()
@@ -149,16 +149,18 @@ class MainSystem:
async def forget_memory_task():
"""记忆遗忘任务"""
while True:
- await asyncio.sleep(global_config.forget_memory_interval)
+ await asyncio.sleep(global_config.memory.forget_memory_interval)
print("\033[1;32m[记忆遗忘]\033[0m 开始遗忘记忆...")
- await HippocampusManager.get_instance().forget_memory(percentage=global_config.memory_forget_percentage)
+ await HippocampusManager.get_instance().forget_memory(
+ percentage=global_config.memory.memory_forget_percentage
+ )
print("\033[1;32m[记忆遗忘]\033[0m 记忆遗忘完成")
@staticmethod
async def consolidate_memory_task():
"""记忆整合任务"""
while True:
- await asyncio.sleep(global_config.consolidate_memory_interval)
+ await asyncio.sleep(global_config.memory.consolidate_memory_interval)
print("\033[1;32m[记忆整合]\033[0m 开始整合记忆...")
await HippocampusManager.get_instance().consolidate_memory()
print("\033[1;32m[记忆整合]\033[0m 记忆整合完成")
diff --git a/src/manager/mood_manager.py b/src/manager/mood_manager.py
index 42677d4e1..c83fbeb7c 100644
--- a/src/manager/mood_manager.py
+++ b/src/manager/mood_manager.py
@@ -34,14 +34,14 @@ class MoodUpdateTask(AsyncTask):
def __init__(self):
super().__init__(
task_name="Mood Update Task",
- wait_before_start=global_config.mood_update_interval,
- run_interval=global_config.mood_update_interval,
+ wait_before_start=global_config.mood.mood_update_interval,
+ run_interval=global_config.mood.mood_update_interval,
)
# 从配置文件获取衰减率
- self.decay_rate_valence: float = 1 - global_config.mood_decay_rate
+ self.decay_rate_valence: float = 1 - global_config.mood.mood_decay_rate
"""愉悦度衰减率"""
- self.decay_rate_arousal: float = 1 - global_config.mood_decay_rate
+ self.decay_rate_arousal: float = 1 - global_config.mood.mood_decay_rate
"""唤醒度衰减率"""
self.last_update = time.time()
diff --git a/src/tools/not_used/change_mood.py b/src/tools/not_used/change_mood.py
index c34bebb93..69fc3bb78 100644
--- a/src/tools/not_used/change_mood.py
+++ b/src/tools/not_used/change_mood.py
@@ -44,7 +44,7 @@ class ChangeMoodTool(BaseTool):
_ori_response = ",".join(response_set)
# _stance, emotion = await gpt._get_emotion_tags(ori_response, message_processed_plain_text)
emotion = "平静"
- mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor)
+ mood_manager.update_mood_from_emotion(emotion, global_config.mood.mood_intensity_factor)
return {"name": "change_mood", "content": f"你的心情刚刚变化了，现在的心情是: {emotion}"}
except Exception as e:
logger.error(f"心情改变工具执行失败: {str(e)}")
diff --git a/src/tools/tool_use.py b/src/tools/tool_use.py
index c55170b88..ff36085d6 100644
--- a/src/tools/tool_use.py
+++ b/src/tools/tool_use.py
@@ -15,7 +15,7 @@ logger = get_logger("tool_use")
class ToolUser:
def __init__(self):
self.llm_model_tool = LLMRequest(
- model=global_config.llm_tool_use, temperature=0.2, max_tokens=1000, request_type="tool_use"
+ model=global_config.model.tool_use, temperature=0.2, max_tokens=1000, request_type="tool_use"
)
@staticmethod
@@ -37,7 +37,7 @@ class ToolUser:
# print(f"intol111111111111111111111111111111111222222222222mid_memory_info：{mid_memory_info}")
# 这些信息应该从调用者传入，而不是从self获取
- bot_name = global_config.BOT_NICKNAME
+ bot_name = global_config.bot.nickname
prompt = ""
prompt += mid_memory_info
prompt += "你正在思考如何回复群里的消息。\n"
diff --git a/template/bot_config_meta.toml b/template/bot_config_meta.toml
deleted file mode 100644
index c3541baad..000000000
--- a/template/bot_config_meta.toml
+++ /dev/null
@@ -1,104 +0,0 @@
-[inner.version]
-describe = "版本号"
-important = true
-can_edit = false
-
-[bot.qq]
-describe = "机器人的QQ号"
-important = true
-can_edit = true
-
-[bot.nickname]
-describe = "机器人的昵称"
-important = true
-can_edit = true
-
-[bot.alias_names]
-describe = "机器人的别名列表，该选项还在调试中，暂时未生效"
-important = false
-can_edit = true
-
-[groups.talk_allowed]
-describe = "可以回复消息的群号码列表"
-important = true
-can_edit = true
-
-[groups.talk_frequency_down]
-describe = "降低回复频率的群号码列表"
-important = false
-can_edit = true
-
-[groups.ban_user_id]
-describe = "禁止回复和读取消息的QQ号列表"
-important = false
-can_edit = true
-
-[personality.personality_core]
-describe = "用一句话或几句话描述人格的核心特点，建议20字以内"
-important = true
-can_edit = true
-
-[personality.personality_sides]
-describe = "用一句话或几句话描述人格的一些细节，条数任意，不能为0，该选项还在调试中"
-important = false
-can_edit = true
-
-[identity.identity_detail]
-describe = "身份特点列表，条数任意，不能为0，该选项还在调试中"
-important = false
-can_edit = true
-
-[identity.age]
-describe = "年龄，单位岁"
-important = false
-can_edit = true
-
-[identity.gender]
-describe = "性别"
-important = false
-can_edit = true
-
-[identity.appearance]
-describe = "外貌特征描述，该选项还在调试中，暂时未生效"
-important = false
-can_edit = true
-
-[platforms.nonebot-qq]
-describe = "nonebot-qq适配器提供的链接"
-important = true
-can_edit = true
-
-[chat.allow_focus_mode]
-describe = "是否允许专注聊天状态"
-important = false
-can_edit = true
-
-[chat.base_normal_chat_num]
-describe = "最多允许多少个群进行普通聊天"
-important = false
-can_edit = true
-
-[chat.base_focused_chat_num]
-describe = "最多允许多少个群进行专注聊天"
-important = false
-can_edit = true
-
-[chat.observation_context_size]
-describe = "观察到的最长上下文大小，建议15，太短太长都会导致脑袋尖尖"
-important = false
-can_edit = true
-
-[chat.message_buffer]
-describe = "启用消息缓冲器，启用此项以解决消息的拆分问题，但会使麦麦的回复延迟"
-important = false
-can_edit = true
-
-[chat.ban_words]
-describe = "需要过滤的消息列表"
-important = false
-can_edit = true
-
-[chat.ban_msgs_regex]
-describe = "需要过滤的消息（原始消息）匹配的正则表达式，匹配到的消息将被过滤（支持CQ码）"
-important = false
-can_edit = true
\ No newline at end of file
diff --git a/template/bot_config_template.toml b/template/bot_config_template.toml
index 931afe2ed..64e51da77 100644
--- a/template/bot_config_template.toml
+++ b/template/bot_config_template.toml
@@ -1,18 +1,10 @@
[inner]
-version = "1.7.0"
+version = "2.0.0"
#----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
#如果你想要修改配置文件，请在修改后将version的值进行变更
-#如果新增项目，请在BotConfig类下新增相应的变量
-#1.如果你修改的是[]层级项目，例如你新增了 [memory],那么请在config.py的 load_config函数中的include_configs字典中新增"内容":{
-#"func":memory,
-#"support":">=0.0.0", #新的版本号
-#"necessary":False #是否必须
-#}
-#2.如果你修改的是[]下的项目，例如你新增了[memory]下的 memory_ban_words ,那么请在config.py的 load_config函数中的 memory函数下新增版本判断:
- # if config.INNER_VERSION in SpecifierSet(">=0.0.2"):
- # config.memory_ban_words = set(memory_config.get("memory_ban_words", []))
-
+#如果新增项目，请阅读src/config/official_configs.py中的说明
+#
# 版本格式：主版本号.次版本号.修订号，版本号递增规则如下：
# 主版本号：当你做了不兼容的 API 修改，
# 次版本号：当你做了向下兼容的功能性新增，
@@ -21,11 +13,11 @@ version = "1.7.0"
#----以上是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
[bot]
-qq = 1145141919810
+qq_account = 1145141919810
nickname = "麦麦"
alias_names = ["麦叠", "牢麦"] #该选项还在调试中，暂时未生效
-[groups]
+[chat_target]
talk_allowed = [
123,
123,
@@ -53,10 +45,13 @@ identity_detail = [
"身份特点",
"身份特点",
]# 条数任意，不能为0, 该选项还在调试中
+
#外貌特征
-age = 20 # 年龄 单位岁
-gender = "男" # 性别
-appearance = "用几句话描述外貌特征" # 外貌特征 该选项还在调试中，暂时未生效
+age = 18 # 年龄 单位岁
+gender = "女" # 性别
+height = "170" # 身高（单位cm）
+weight = "50" # 体重（单位kg）
+appearance = "用一句或几句话描述外貌特征" # 外貌特征 该选项还在调试中，暂时未生效
[platforms] # 必填项目，填写每个平台适配器提供的链接
qq="http://127.0.0.1:18002/api/message"
@@ -85,11 +80,10 @@ ban_msgs_regex = [
[normal_chat] #普通聊天
#一般回复参数
-model_reasoning_probability = 0.7 # 麦麦回答时选择推理模型 模型的概率
-model_normal_probability = 0.3 # 麦麦回答时选择一般模型 模型的概率
+reasoning_model_probability = 0.3 # 麦麦回答时选择推理模型的概率（与之相对的，普通模型的概率为1 - reasoning_model_probability）
emoji_chance = 0.2 # 麦麦一般回复时使用表情包的概率，设置为1让麦麦自己决定发不发
-thinking_timeout = 100 # 麦麦最长思考时间，超过这个时间的思考会放弃（往往是api反应太慢）
+thinking_timeout = 120 # 麦麦最长思考时间，超过这个时间的思考会放弃（往往是api反应太慢）
willing_mode = "classical" # 回复意愿模式 —— 经典模式：classical，mxp模式：mxp，自定义模式：custom（需要你自己实现）
response_willing_amplifier = 1 # 麦麦回复意愿放大系数，一般为1
@@ -100,8 +94,8 @@ mentioned_bot_inevitable_reply = false # 提及 bot 必然回复
at_bot_inevitable_reply = false # @bot 必然回复
[focus_chat] #专注聊天
-reply_trigger_threshold = 3.6 # 专注聊天触发阈值，越低越容易进入专注聊天
-default_decay_rate_per_second = 0.95 # 默认衰减率，越大衰减越快，越高越难进入专注聊天
+reply_trigger_threshold = 3.0 # 专注聊天触发阈值，越低越容易进入专注聊天
+default_decay_rate_per_second = 0.98 # 默认衰减率，越大衰减越快，越高越难进入专注聊天
consecutive_no_reply_threshold = 3 # 连续不回复的阈值，越低越容易结束专注聊天
# 以下选项暂时无效
@@ -110,20 +104,20 @@ compress_length_limit = 5 #最多压缩份数，超过该数值的压缩上下
[emoji]
-max_emoji_num = 40 # 表情包最大数量
-max_reach_deletion = true # 开启则在达到最大数量时删除表情包，关闭则达到最大数量时不删除，只是不会继续收集表情包
-check_interval = 10 # 检查表情包（注册，破损，删除）的时间间隔(分钟)
+max_reg_num = 40 # 表情包最大注册数量
+do_replace = true # 开启则在达到最大数量时删除（替换）表情包，关闭则达到最大数量时不会继续收集表情包
+check_interval = 120 # 检查表情包（注册，破损，删除）的时间间隔(分钟)
save_pic = false # 是否保存图片
-save_emoji = false # 是否保存表情包
+cache_emoji = true # 是否缓存表情包
steal_emoji = true # 是否偷取表情包，让麦麦可以发送她保存的这些表情包
-enable_check = false # 是否启用表情包过滤，只有符合该要求的表情包才会被保存
-check_prompt = "符合公序良俗" # 表情包过滤要求，只有符合该要求的表情包才会被保存
+content_filtration = false # 是否启用表情包过滤，只有符合该要求的表情包才会被保存
+filtration_prompt = "符合公序良俗" # 表情包过滤要求，只有符合该要求的表情包才会被保存
[memory]
-build_memory_interval = 2000 # 记忆构建间隔 单位秒 间隔越低，麦麦学习越多，但是冗余信息也会增多
-build_memory_distribution = [6.0,3.0,0.6,32.0,12.0,0.4] # 记忆构建分布，参数：分布1均值，标准差，权重，分布2均值，标准差，权重
-build_memory_sample_num = 8 # 采样数量，数值越高记忆采样次数越多
-build_memory_sample_length = 40 # 采样长度，数值越高一段记忆内容越丰富
+memory_build_interval = 2000 # 记忆构建间隔 单位秒 间隔越低，麦麦学习越多，但是冗余信息也会增多
+memory_build_distribution = [6.0, 3.0, 0.6, 32.0, 12.0, 0.4] # 记忆构建分布，参数：分布1均值，标准差，权重，分布2均值，标准差，权重
+memory_build_sample_num = 8 # 采样数量，数值越高记忆采样次数越多
+memory_build_sample_length = 40 # 采样长度，数值越高一段记忆内容越丰富
memory_compress_rate = 0.1 # 记忆压缩率 控制记忆精简程度 建议保持默认,调高可以获得更多信息，但是冗余信息也会增多
forget_memory_interval = 1000 # 记忆遗忘间隔 单位秒 间隔越低，麦麦遗忘越频繁，记忆更精简，但更难学习
@@ -135,49 +129,45 @@ consolidation_similarity_threshold = 0.7 # 相似度阈值
consolidation_check_percentage = 0.01 # 检查节点比例
#不希望记忆的词，已经记忆的不会受到影响
-memory_ban_words = [
- # "403","张三"
-]
+memory_ban_words = [ "表情包", "图片", "回复", "聊天记录" ]
[mood]
mood_update_interval = 1.0 # 情绪更新间隔 单位秒
mood_decay_rate = 0.95 # 情绪衰减率
mood_intensity_factor = 1.0 # 情绪强度因子
-[keywords_reaction] # 针对某个关键词作出反应
+[keyword_reaction] # 针对某个关键词作出反应
enable = true # 关键词反应功能的总开关
-[[keywords_reaction.rules]] # 如果想要新增多个关键词，直接复制本条，修改keywords和reaction即可
+[[keyword_reaction.rules]] # 如果想要新增多个关键词，直接复制本条，修改keywords和reaction即可
enable = true # 是否启用此条（为了人类在未来AI战争能更好地识别AI（bushi），默认开启）
keywords = ["人机", "bot", "机器", "入机", "robot", "机器人","ai","AI"] # 会触发反应的关键词
reaction = "有人说你是人机或者机器人，否定这一事实，攻击或反问他。注意，只有认为你是机器人才回复，否则不要否认" # 触发之后添加的提示词
-[[keywords_reaction.rules]] # 就像这样复制
+[[keyword_reaction.rules]] # 就像这样复制
enable = false # 仅作示例，不会触发
keywords = ["测试关键词回复","test",""]
reaction = "回答“测试成功”" # 修复错误的引号
-[[keywords_reaction.rules]] # 使用正则表达式匹配句式
+[[keyword_reaction.rules]] # 使用正则表达式匹配句式
enable = false # 仅作示例，不会触发
regex = ["^(?P