gardel/Mofox-Core
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat(chat): 实现动态消息分发系统和消息打断机制

Browse Source 
添加基于focus_energy的动态消息分发周期调整功能，根据聊天流兴趣度智能调整检查间隔
实现消息打断系统，允许高优先级消息打断正在处理的任务
重构ChatStream类，引入动态兴趣度计算系统，包括消息兴趣度统计和用户关系评分
扩展数据库模型和配置系统以支持新功能，增加相关配置项
更新版本号至0.11.0-alpha-1以反映重大功能更新
This commit is contained in:
Windpicker-owo
2025-09-25 17:14:01 +08:00
parent 4cbd86aa96
commit a2baec088e
15 changed files with 703 additions and 73 deletions
Download Patch File Download Diff File Expand all files Collapse all files

188
src/chat/message_receive/chat_stream.py
View File

@@ -83,10 +83,18 @@ class ChatStream:
self.sleep_pressure = data.get("sleep_pressure", 0.0) if data else 0.0
self.saved = False
self.context: ChatMessageContext = None # type: ignore # 用于存储该聊天的上下文信息
# 从配置文件中读取focus_value，如果没有则使用默认值1.0
self.focus_energy = (
data.get("focus_energy", global_config.chat.focus_value) if data else global_config.chat.focus_value
)
# 动态兴趣度系统 - 重构后的focus_energy
self.base_interest_energy = data.get("base_interest_energy", 0.5) if data else 0.5
self.message_interest_total = data.get("message_interest_total", 0.0) if data else 0.0
self.message_count = data.get("message_count", 0) if data else 0
self.action_count = data.get("action_count", 0) if data else 0
self.reply_count = data.get("reply_count", 0) if data else 0
self.last_interaction_time = data.get("last_interaction_time", time.time()) if data else time.time()
self.consecutive_no_reply = data.get("consecutive_no_reply", 0) if data else 0
# 计算动态focus_energy
self.focus_energy = self._calculate_dynamic_focus_energy()
self.no_reply_consecutive = 0
self.breaking_accumulated_interest = 0.0
@@ -103,6 +111,14 @@ class ChatStream:
"sleep_pressure": self.sleep_pressure,
"focus_energy": self.focus_energy,
"breaking_accumulated_interest": self.breaking_accumulated_interest,
# 新增动态兴趣度系统字段
"base_interest_energy": self.base_interest_energy,
"message_interest_total": self.message_interest_total,
"message_count": self.message_count,
"action_count": self.action_count,
"reply_count": self.reply_count,
"last_interaction_time": self.last_interaction_time,
"consecutive_no_reply": self.consecutive_no_reply,
}
@classmethod
@@ -128,6 +144,148 @@ class ChatStream:
"""设置聊天消息上下文"""
self.context = ChatMessageContext(message)
def _calculate_dynamic_focus_energy(self) -> float:
"""动态计算聊天流的总体兴趣度"""
try:
# 基础分：平均消息兴趣度
avg_message_interest = self.message_interest_total / max(self.message_count, 1)
# 动作参与度：动作执行率
action_rate = self.action_count / max(self.message_count, 1)
# 回复活跃度：回复率
reply_rate = self.reply_count / max(self.message_count, 1)
# 获取用户关系分（对于私聊，群聊无效）
relationship_factor = self._get_user_relationship_score()
# 时间衰减因子：最近活跃度
current_time = time.time()
if not self.last_interaction_time:
self.last_interaction_time = current_time
time_since_interaction = current_time - self.last_interaction_time
time_decay = max(0.3, 1.0 - min(time_since_interaction / (7 * 24 * 3600), 0.7)) # 7天衰减
# 连续无回复惩罚
no_reply_penalty = max(0.1, 1.0 - self.consecutive_no_reply * 0.1)
# 获取AFC系统阈值，添加None值检查
reply_threshold = getattr(global_config.affinity_flow, 'reply_action_interest_threshold', 0.4)
non_reply_threshold = getattr(global_config.affinity_flow, 'non_reply_action_interest_threshold', 0.2)
high_match_threshold = getattr(global_config.affinity_flow, 'high_match_interest_threshold', 0.8)
# 计算与不同阈值的差距比例
reply_gap_ratio = max(0, (avg_message_interest - reply_threshold) / max(0.1, (1.0 - reply_threshold)))
non_reply_gap_ratio = max(0, (avg_message_interest - non_reply_threshold) / max(0.1, (1.0 - non_reply_threshold)))
high_match_gap_ratio = max(0, (avg_message_interest - high_match_threshold) / max(0.1, (1.0 - high_match_threshold)))
# 基于阈值差距比例的基础分计算
threshold_based_score = (
reply_gap_ratio * 0.6 + # 回复阈值差距权重60%
non_reply_gap_ratio * 0.2 + # 非回复阈值差距权重20%
high_match_gap_ratio * 0.2 # 高匹配阈值差距权重20%
)
# 动态权重调整：根据平均兴趣度水平调整权重分配
if avg_message_interest >= high_match_threshold:
# 高兴趣度：更注重阈值差距
threshold_weight = 0.7
activity_weight = 0.2
relationship_weight = 0.1
elif avg_message_interest >= reply_threshold:
# 中等兴趣度：平衡权重
threshold_weight = 0.5
activity_weight = 0.3
relationship_weight = 0.2
else:
# 低兴趣度：更注重活跃度提升
threshold_weight = 0.3
activity_weight = 0.5
relationship_weight = 0.2
# 计算活跃度得分
activity_score = (action_rate * 0.6 + reply_rate * 0.4)
# 综合计算：基于阈值的动态加权
focus_energy = (
threshold_based_score * threshold_weight + # 阈值差距基础分
activity_score * activity_weight + # 活跃度得分
relationship_factor * relationship_weight + # 关系得分
self.base_interest_energy * 0.05 # 基础兴趣微调
) * time_decay * no_reply_penalty
# 确保在合理范围内
focus_energy = max(0.1, min(1.0, focus_energy))
# 应用非线性变换增强区分度
if focus_energy >= 0.7:
# 高兴趣度区域：指数增强，更敏感
focus_energy = 0.7 + (focus_energy - 0.7) ** 0.8
elif focus_energy >= 0.4:
# 中等兴趣度区域：线性保持
pass
else:
# 低兴趣度区域：对数压缩，减少区分度
focus_energy = 0.4 * (focus_energy / 0.4) ** 1.2
return max(0.1, min(1.0, focus_energy))
except Exception as e:
logger.error(f"计算动态focus_energy失败: {e}")
return self.base_interest_energy
def _get_user_relationship_score(self) -> float:
"""从外部系统获取用户关系分"""
try:
# 尝试从兴趣评分系统获取用户关系分
from src.plugins.built_in.affinity_flow_chatter.interest_scoring import (
chatter_interest_scoring_system,
)
if self.user_info and hasattr(self.user_info, 'user_id'):
return chatter_interest_scoring_system.get_user_relationship(str(self.user_info.user_id))
except Exception:
pass
# 默认基础分
return 0.3
def add_message_interest(self, interest_score: float):
"""添加消息兴趣值并更新focus_energy"""
self.message_interest_total += interest_score
self.message_count += 1
self.last_interaction_time = time.time()
self.focus_energy = self._calculate_dynamic_focus_energy()
def record_action(self, is_reply: bool = False):
"""记录动作执行"""
self.action_count += 1
if is_reply:
self.reply_count += 1
self.consecutive_no_reply = max(0, self.consecutive_no_reply - 1)
self.last_interaction_time = time.time()
self.focus_energy = self._calculate_dynamic_focus_energy()
def record_no_reply(self):
"""记录无回复动作"""
self.consecutive_no_reply += 1
self.last_interaction_time = time.time()
self.focus_energy = self._calculate_dynamic_focus_energy()
def get_adjusted_focus_energy(self) -> float:
"""获取应用了afc调整的focus_energy"""
try:
from src.chat.message_manager.message_manager import message_manager
if self.stream_id in message_manager.stream_contexts:
context = message_manager.stream_contexts[self.stream_id]
afc_adjustment = context.get_afc_threshold_adjustment()
# 对动态计算的focus_energy应用AFC调整
adjusted_energy = max(0.0, self.focus_energy - afc_adjustment)
return adjusted_energy
except Exception:
pass
return self.focus_energy
class ChatManager:
"""聊天管理器，管理所有聊天流"""
@@ -364,7 +522,16 @@ class ChatManager:
"group_name": group_info_d["group_name"] if group_info_d else "",
"energy_value": s_data_dict.get("energy_value", 5.0),
"sleep_pressure": s_data_dict.get("sleep_pressure", 0.0),
"focus_energy": s_data_dict.get("focus_energy", global_config.chat.focus_value),
"focus_energy": s_data_dict.get("focus_energy", 0.5),
# 新增动态兴趣度系统字段
"base_interest_energy": s_data_dict.get("base_interest_energy", 0.5),
"message_interest_total": s_data_dict.get("message_interest_total", 0.0),
"message_count": s_data_dict.get("message_count", 0),
"action_count": s_data_dict.get("action_count", 0),
"reply_count": s_data_dict.get("reply_count", 0),
"last_interaction_time": s_data_dict.get("last_interaction_time", time.time()),
"relationship_score": s_data_dict.get("relationship_score", 0.3),
"consecutive_no_reply": s_data_dict.get("consecutive_no_reply", 0),
}
# 根据数据库类型选择插入语句
@@ -426,7 +593,16 @@ class ChatManager:
"last_active_time": model_instance.last_active_time,
"energy_value": model_instance.energy_value,
"sleep_pressure": model_instance.sleep_pressure,
"focus_energy": getattr(model_instance, "focus_energy", global_config.chat.focus_value),
"focus_energy": getattr(model_instance, "focus_energy", 0.5),
# 新增动态兴趣度系统字段 - 使用getattr提供默认值
"base_interest_energy": getattr(model_instance, "base_interest_energy", 0.5),
"message_interest_total": getattr(model_instance, "message_interest_total", 0.0),
"message_count": getattr(model_instance, "message_count", 0),
"action_count": getattr(model_instance, "action_count", 0),
"reply_count": getattr(model_instance, "reply_count", 0),
"last_interaction_time": getattr(model_instance, "last_interaction_time", time.time()),
"relationship_score": getattr(model_instance, "relationship_score", 0.3),
"consecutive_no_reply": getattr(model_instance, "consecutive_no_reply", 0),
}
loaded_streams_data.append(data_for_from_dict)
session.commit()