This commit is contained in:
SengokuCola
2025-04-30 17:50:47 +08:00
parent 7d19a6728f
commit 5963214d95
11 changed files with 108 additions and 94 deletions

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@@ -170,7 +170,6 @@ class BotConfig:
SCHEDULE_TEMPERATURE: float = 0.5 # 日程表温度建议0.5-1.0
TIME_ZONE: str = "Asia/Shanghai" # 时区
# chat
allow_focus_mode: bool = True # 是否允许专注聊天状态
@@ -181,7 +180,6 @@ class BotConfig:
message_buffer: bool = True # 消息缓冲器
ban_words = set()
ban_msgs_regex = set()
@@ -190,11 +188,9 @@ class BotConfig:
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
@@ -434,7 +430,6 @@ class BotConfig:
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
@@ -457,9 +452,7 @@ class BotConfig:
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.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
)
@@ -470,7 +463,6 @@ class BotConfig:
"consecutive_no_reply_threshold", config.consecutive_no_reply_threshold
)
def model(parent: dict):
# 加载模型配置
model_config: dict = parent["model"]
@@ -634,7 +626,9 @@ class BotConfig:
"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)
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"]

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@@ -24,6 +24,7 @@ CLEANUP_INTERVAL_SECONDS = 1200
STATE_UPDATE_INTERVAL_SECONDS = 60
LOG_INTERVAL_SECONDS = 3
class BackgroundTaskManager:
"""管理 Heartflow 的后台周期性任务。"""
@@ -32,14 +33,13 @@ class BackgroundTaskManager:
mai_state_info: MaiStateInfo, # Needs current state info
mai_state_manager: MaiStateManager,
subheartflow_manager: SubHeartflowManager,
interest_logger: InterestLogger
interest_logger: InterestLogger,
):
self.mai_state_info = mai_state_info
self.mai_state_manager = mai_state_manager
self.subheartflow_manager = subheartflow_manager
self.interest_logger = interest_logger
# Task references
self._state_update_task: Optional[asyncio.Task] = None
self._cleanup_task: Optional[asyncio.Task] = None
@@ -100,7 +100,7 @@ class BackgroundTaskManager:
]
# 统一启动所有任务
for task_func,log_level, log_msg, task_attr_name in task_configs:
for task_func, log_level, log_msg, task_attr_name in task_configs:
# 检查任务变量是否存在且未完成
current_task_var = getattr(self, task_attr_name)
if current_task_var is None or current_task_var.done():

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@@ -14,6 +14,7 @@ from src.heart_flow.background_tasks import BackgroundTaskManager # Import Back
logger = get_logger("heartflow")
class Heartflow:
"""主心流协调器,负责初始化并协调各个子系统:
- 状态管理 (MaiState)

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@@ -5,6 +5,7 @@ from typing import List, Tuple, Optional
from src.common.logger_manager import get_logger
from src.plugins.moods.moods import MoodManager
from src.config.config import global_config
logger = get_logger("mai_state")
@@ -19,13 +20,12 @@ 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_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
# 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_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

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@@ -5,7 +5,6 @@ import time
from typing import Optional, List, Dict, Tuple, Callable, Coroutine
import traceback
from src.common.logger_manager import get_logger
import random
from src.plugins.chat.message import MessageRecv
from src.plugins.chat.chat_stream import chat_manager
import math
@@ -153,8 +152,6 @@ class InterestChatting:
"above_threshold": self.above_threshold,
}
# --- 新增后台更新任务相关方法 ---
async def _run_update_loop(self, update_interval: float = 1.0):
"""后台循环,定期更新兴趣和回复概率。"""

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@@ -31,6 +31,7 @@ logger = get_logger("subheartflow_manager")
INACTIVE_THRESHOLD_SECONDS = 3600 # 子心流不活跃超时时间(秒)
NORMAL_CHAT_TIMEOUT_SECONDS = 30 * 60 # 30分钟
class SubHeartflowManager:
"""管理所有活跃的 SubHeartflow 实例。"""
@@ -341,8 +342,7 @@ class SubHeartflowManager:
async with self._lock:
# 1. 筛选出所有 ABSENT 状态的子心流
absent_subflows = [
hf for hf in self.subheartflows.values()
if hf.chat_state.chat_status == ChatState.ABSENT
hf for hf in self.subheartflows.values() if hf.chat_state.chat_status == ChatState.ABSENT
]
if not absent_subflows:
@@ -358,7 +358,9 @@ class SubHeartflowManager:
# 3. 检查 CHAT 上限
current_chat_count = self.count_subflows_by_state_nolock(ChatState.CHAT)
if current_chat_count >= chat_limit:
logger.debug(f"{log_prefix} 想看看能不能聊,但是聊天太多了, ({current_chat_count}/{chat_limit}) 满了。")
logger.debug(
f"{log_prefix} 想看看能不能聊,但是聊天太多了, ({current_chat_count}/{chat_limit}) 满了。"
)
return # 满了,这次就算了
# --- 获取 FOCUSED 计数 ---
@@ -384,15 +386,19 @@ class SubHeartflowManager:
mai_state_description = f"你当前状态: {current_mai_state.value}"
individuality = Individuality.get_instance()
personality_prompt = individuality.get_prompt(x_person=2, level = 2)
personality_prompt = individuality.get_prompt(x_person=2, level=2)
prompt_personality = f"你正在扮演名为{individuality.name}的人类,{personality_prompt}"
# --- 修改:在 prompt 中加入当前聊天计数和群名信息 (条件显示) ---
chat_status_lines = []
if chatting_group_names:
chat_status_lines.append(f"正在闲聊 ({current_chat_count}/{chat_limit}): {', '.join(chatting_group_names)}")
chat_status_lines.append(
f"正在闲聊 ({current_chat_count}/{chat_limit}): {', '.join(chatting_group_names)}"
)
if focused_group_names:
chat_status_lines.append(f"正在专注 ({current_focused_count}/{focused_limit}): {', '.join(focused_group_names)}")
chat_status_lines.append(
f"正在专注 ({current_focused_count}/{focused_limit}): {', '.join(focused_group_names)}"
)
chat_status_prompt = "当前没有在任何群聊中。" # 默认消息喵~
if chat_status_lines:
@@ -406,8 +412,8 @@ class SubHeartflowManager:
f"{_observation_summary}\\n---\\n"
f"基于以上信息,你想不想开始在这个群闲聊?\\n"
f"请说明理由,并以 JSON 格式回答,包含 'decision' (布尔值) 和 'reason' (字符串)。\\n"
f'例如:{{\"decision\": true, \"reason\": \"看起来挺热闹的,插个话\"}}\\n'
f'例如:{{\"decision\": false, \"reason\": \"已经聊了好多,休息一下\"}}\\n'
f'例如:{{"decision": true, "reason": "看起来挺热闹的,插个话"}}\\n'
f'例如:{{"decision": false, "reason": "已经聊了好多,休息一下"}}\\n'
f"请只输出有效的 JSON 对象。"
)
# --- 结束修改 ---
@@ -435,7 +441,9 @@ class SubHeartflowManager:
if sub_hf_to_evaluate.chat_state.chat_status == ChatState.CHAT:
logger.debug(f"{log_prefix} 成功进入聊天状态!本次评估圆满结束。")
else:
logger.warning(f"{log_prefix} 奇怪,尝试进入聊天状态失败了。当前状态: {sub_hf_to_evaluate.chat_state.chat_status.value}")
logger.warning(
f"{log_prefix} 奇怪,尝试进入聊天状态失败了。当前状态: {sub_hf_to_evaluate.chat_state.chat_status.value}"
)
else:
logger.warning(
f"{log_prefix} AI说想聊但是刚问完就没空位了 ({current_chat_count_before_change}/{chat_limit})。真不巧,下次再说吧。"
@@ -483,7 +491,9 @@ class SubHeartflowManager:
if time_since_last_bb > NORMAL_CHAT_TIMEOUT_SECONDS:
should_deactivate = True
reason = f"超过 {NORMAL_CHAT_TIMEOUT_SECONDS / 60:.0f} 分钟没 BB"
logger.info(f"{log_prefix} 检测到超时 ({reason}),准备转为 ABSENT。上次活动时间: {last_bot_dong_zuo_time:.0f}")
logger.info(
f"{log_prefix} 检测到超时 ({reason}),准备转为 ABSENT。上次活动时间: {last_bot_dong_zuo_time:.0f}"
)
# else:
# logger.debug(f"{log_prefix} Bot活动时间未超时 ({time_since_last_bb:.0f}s < {NORMAL_CHAT_TIMEOUT_SECONDS}s),保持 CHAT 状态。")
# else:
@@ -491,7 +501,9 @@ class SubHeartflowManager:
# logger.debug(f"{log_prefix} 未找到有效的 Bot 最后活动时间记录,不执行超时检查。")
except AttributeError:
logger.error(f"{log_prefix} 无法获取 Bot 最后 BB 时间,请确保 SubHeartflow 相关实现正确。跳过超时检查。")
logger.error(
f"{log_prefix} 无法获取 Bot 最后 BB 时间,请确保 SubHeartflow 相关实现正确。跳过超时检查。"
)
except Exception as e:
logger.error(f"{log_prefix} 检查 Bot 超时状态时出错: {e}", exc_info=True)
@@ -507,9 +519,12 @@ class SubHeartflowManager:
logger.warning(f"{log_prefix} 尝试因超时转换为 ABSENT 失败。")
if transitioned_to_absent > 0:
logger.info(f"{log_prefix_task} 完成,共检查 {checked_count} 个子心流,{transitioned_to_absent} 个因超时转为 ABSENT。")
logger.info(
f"{log_prefix_task} 完成,共检查 {checked_count} 个子心流,{transitioned_to_absent} 个因超时转为 ABSENT。"
)
# else:
# logger.debug(f"{log_prefix_task} 完成,共检查 {checked_count} 个子心流,无超时转换。")
# --- 结束新增 ---
async def _llm_evaluate_state_transition(self, prompt: str) -> Optional[bool]:
@@ -671,14 +686,20 @@ class SubHeartflowManager:
if current_chat_count < chat_limit:
target_state = ChatState.CHAT
log_reason = f"随机选择 CHAT (当前 {current_chat_count}/{chat_limit})"
logger.debug(f"[状态转换请求] {stream_name} ({current_state.value}) 随机决定进入 CHAT未达上限 ({current_chat_count}/{chat_limit})")
logger.debug(
f"[状态转换请求] {stream_name} ({current_state.value}) 随机决定进入 CHAT未达上限 ({current_chat_count}/{chat_limit})"
)
else:
target_state = ChatState.ABSENT
log_reason = f"随机选择 CHAT 但已达上限 ({current_chat_count}/{chat_limit}),转为 ABSENT"
logger.debug(f"[状态转换请求] {stream_name} ({current_state.value}) 随机决定进入 CHAT但已达上限 ({current_chat_count}/{chat_limit}),改为进入 ABSENT")
logger.debug(
f"[状态转换请求] {stream_name} ({current_state.value}) 随机决定进入 CHAT但已达上限 ({current_chat_count}/{chat_limit}),改为进入 ABSENT"
)
#开始转换
logger.info(f"[状态转换请求] 接收到请求,将 {stream_name} (当前: {current_state.value}) 尝试转换为 {target_state.value} ({log_reason})")
# 开始转换
logger.info(
f"[状态转换请求] 接收到请求,将 {stream_name} (当前: {current_state.value}) 尝试转换为 {target_state.value} ({log_reason})"
)
try:
await subflow.change_chat_state(target_state)
# 检查最终状态
@@ -686,9 +707,13 @@ class SubHeartflowManager:
if final_state == target_state:
logger.debug(f"[状态转换请求] {stream_name} 状态已成功转换为 {final_state.value}")
else:
logger.warning(f"[状态转换请求] 尝试将 {stream_name} 转换为 {target_state.value} 后,状态实际为 {final_state.value}")
logger.warning(
f"[状态转换请求] 尝试将 {stream_name} 转换为 {target_state.value} 后,状态实际为 {final_state.value}"
)
except Exception as e:
logger.error(f"[状态转换请求] 转换 {stream_name}{target_state.value} 时出错: {e}", exc_info=True)
logger.error(
f"[状态转换请求] 转换 {stream_name}{target_state.value} 时出错: {e}", exc_info=True
)
elif current_state == ChatState.ABSENT:
logger.debug(f"[状态转换请求] {stream_name} 已处于 ABSENT 状态,无需转换")
else:

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@@ -315,7 +315,6 @@ class ImageManager:
logger.warning(f"计算出的目标宽度为0 (原始尺寸 {frame_width}x{frame_height})调整为1")
target_width = 1
# 调整所有选中帧的大小
resized_frames = [
frame.resize((target_width, target_height), Image.Resampling.LANCZOS) for frame in selected_frames
@@ -332,7 +331,6 @@ class ImageManager:
logger.error("计算出的总宽度为0且无选中帧")
return None
combined_image = Image.new("RGB", (total_width, target_height))
# 水平拼接图像

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@@ -982,12 +982,13 @@ class HeartFChatting:
# --- 新增:概率性忽略文本回复附带的表情(正确的位置)---
if action == "text_reply" and emoji_query:
logger.debug(f"{self.log_prefix}[Planner] 大模型想让麦麦发文字时带表情: '{emoji_query}'")
# 掷骰子看看要不要听它的
if random.random() > EMOJI_SEND_PRO:
logger.info(f"{self.log_prefix}[Planner] 但是麦麦这次不想加表情 ({1-EMOJI_SEND_PRO:.0%}),忽略表情 '{emoji_query}'")
logger.info(
f"{self.log_prefix}[Planner] 但是麦麦这次不想加表情 ({1 - EMOJI_SEND_PRO:.0%}),忽略表情 '{emoji_query}'"
)
emoji_query = "" # 把表情请求清空,就不发了
else:
logger.info(f"{self.log_prefix}[Planner] 好吧,加上表情 '{emoji_query}'")

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@@ -44,7 +44,5 @@ class MemoryConfig:
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
llm_summary=getattr(global_config, "llm_summary", "default_summary_model"), # 添加默认模型名
)