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迁移：69a855d（feat：保存关键词到message数据库）

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This commit is contained in:
Windpicker-owo
2025-09-01 15:24:43 +08:00
parent 9e64806d08
commit 366dadeb15
9 changed files with 76 additions and 55 deletions
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17
src/chat/chat_loop/cycle_processor.py
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@@ -159,19 +159,12 @@ class CycleProcessor:
self.context.last_action = action_type
# 处理no_reply相关的逻辑
if action_type != "no_reply" and action_type != "no_action":
# 导入NoReplyAction并重置计数器
from src.plugins.built_in.core_actions.no_reply import NoReplyAction
NoReplyAction.reset_consecutive_count()
if action_type != "no_reply":
self.context.no_reply_consecutive = 0
logger.info(f"{self.context.log_prefix} 执行了{action_type}动作，重置no_reply计数器")
elif action_type == "no_action":
# 当执行回复动作时，也重置no_reply计数
from src.plugins.built_in.core_actions.no_reply import NoReplyAction
NoReplyAction.reset_consecutive_count()
self.context.no_reply_consecutive = 0
logger.info(f"{self.context.log_prefix} 执行了回复动作，重置no_reply计数器")
if hasattr(self.context, 'chat_instance') and self.context.chat_instance:
self.context.chat_instance.recent_interest_records.clear()
logger.info(f"{self.context.log_prefix} 执行了{action_type}动作，重置no_reply计数器和兴趣度记录")
if action_type == "no_reply":
self.context.no_reply_consecutive += 1
# 调用HeartFChatting中的_determine_form_type方法

48
src/chat/chat_loop/heartFC_chat.py
View File

@@ -3,6 +3,7 @@ import time
import traceback
import random
from typing import Optional, List, Dict, Any, Tuple
from collections import deque
from src.common.logger import get_logger
from src.config.config import global_config
@@ -55,6 +56,9 @@ class HeartFChatting:
self.context.chat_instance = self
self._loop_task: Optional[asyncio.Task] = None
# 记录最近3次的兴趣度
self.recent_interest_records: deque = deque(maxlen=3)
self._initialize_chat_mode()
logger.info(f"{self.context.log_prefix} HeartFChatting 初始化完成")
@@ -242,23 +246,20 @@ class HeartFChatting:
logger.info(f"{self.context.log_prefix} 从睡眠中被唤醒，将处理积压的消息。")
# 根据聊天模式处理新消息
if self.context.loop_mode == ChatMode.FOCUS:
# 如果上一个动作是no_reply，则执行no_reply逻辑
if self.context.last_action == "no_reply":
if not await self._execute_no_reply(recent_messages):
self.context.energy_value -= 0.3 / global_config.chat.focus_value
logger.info(f"{self.context.log_prefix} 能量值减少，当前能量值：{self.context.energy_value:.1f}")
return has_new_messages
# 统一使用 _should_process_messages 判断是否应该处理
if not self._should_process_messages(recent_messages if has_new_messages else None):
return has_new_messages
if self.context.loop_mode == ChatMode.FOCUS:
# 处理新消息
for message in recent_messages:
await self.cycle_processor.observe(message)
# 如果成功观察，增加能量值
if has_new_messages:
self.context.energy_value += 1 / global_config.chat.focus_value
logger.info(f"{self.context.log_prefix} 能量值增加，当前能量值：{self.context.energy_value:.1f}")
self._check_focus_exit()
elif self.context.loop_mode == ChatMode.NORMAL:
self._check_focus_entry(len(recent_messages))
@@ -399,9 +400,8 @@ class HeartFChatting:
self.context.focus_energy = 1
else:
# 计算最近三次记录的兴趣度总和
from src.plugins.built_in.core_actions.no_reply import NoReplyAction
total_recent_interest = sum(NoReplyAction._recent_interest_records)
total_recent_interest = sum(self.recent_interest_records)
# 获取当前聊天频率和意愿系数
talk_frequency = global_config.chat.get_current_talk_frequency(self.context.stream_id)
@@ -417,6 +417,22 @@ class HeartFChatting:
else:
logger.info(f"{self.context.log_prefix} 兴趣度充足")
self.context.focus_energy = 1
def _should_process_messages(self, messages: List[Dict[str, Any]] = None) -> bool:
"""
统一判断是否应该处理消息的函数
根据当前循环模式和消息内容决定是否继续处理
"""
from src.chat.utils.utils_image import is_image_message
if self.context.loop_mode == ChatMode.FOCUS:
if self.context.last_action == "no_reply":
if messages:
return self._execute_no_reply(messages)
return False
return True
return True
async def _execute_no_reply(self, new_message: List[Dict[str, Any]]) -> bool:
"""执行breaking形式的no_reply（原有逻辑）"""
@@ -427,14 +443,13 @@ class HeartFChatting:
if new_message_count >= modified_exit_count_threshold:
# 记录兴趣度到列表
from src.plugins.built_in.core_actions.no_reply import NoReplyAction
total_interest = 0.0
for msg_dict in new_message:
interest_value = msg_dict.get("interest_value", 0.0)
if msg_dict.get("processed_plain_text", ""):
total_interest += interest_value
NoReplyAction._recent_interest_records.append(total_interest)
self.recent_interest_records.append(total_interest)
logger.info(
f"{self.context.log_prefix} 累计消息数量达到{new_message_count}条(>{modified_exit_count_threshold})，结束等待"
@@ -458,11 +473,10 @@ class HeartFChatting:
if accumulated_interest >= 3 / talk_frequency:
# 记录兴趣度到列表
from src.plugins.built_in.core_actions.no_reply import NoReplyAction
NoReplyAction._recent_interest_records.append(accumulated_interest)
self.recent_interest_records.append(accumulated_interest)
logger.info(
f"{self.context.log_prefix} 累计兴趣值达到{accumulated_interest:.2f}(>{5 / talk_frequency})，结束等待"
f"{self.context.log_prefix} 累计兴趣值达到{accumulated_interest:.2f}(>{3 / talk_frequency})，结束等待"
)
return True

4
src/chat/heart_flow/heartflow_message_processor.py
View File

@@ -57,9 +57,11 @@ async def _calculate_interest(message: MessageRecv) -> Tuple[float, bool, list[s
with Timer("记忆激活"):
interested_rate, keywords = await hippocampus_manager.get_activate_from_text(
message.processed_plain_text,
max_depth=5,
max_depth=4,
fast_retrieval=False,
)
message.key_words = keywords
message.key_words_lite = keywords
logger.debug(f"记忆激活率: {interested_rate:.2f}, 关键词: {keywords}")
text_len = len(message.processed_plain_text)

6
src/chat/memory_system/Hippocampus.py
View File

@@ -324,14 +324,14 @@ class Hippocampus:
# 使用LLM提取关键词 - 根据详细文本长度分布优化topic_num计算
text_length = len(text)
topic_num: int | list[int] = 0
if text_length <= 5:
if text_length <= 6:
words = jieba.cut(text)
keywords = [word for word in words if len(word) > 1]
keywords = list(set(keywords))[:3] # 限制最多3个关键词
if keywords:
logger.debug(f"提取关键词: {keywords}")
return keywords
elif text_length <= 10:
elif text_length <= 12:
topic_num = [1, 3] # 6-10字符: 1个关键词 (27.18%的文本)
elif text_length <= 20:
topic_num = [2, 4] # 11-20字符: 2个关键词 (22.76%的文本)
@@ -777,7 +777,7 @@ class Hippocampus:
total_nodes = len(self.memory_graph.G.nodes())
# activated_nodes = len(activate_map)
activation_ratio = total_activation / total_nodes if total_nodes > 0 else 0
activation_ratio = activation_ratio * 60
activation_ratio = activation_ratio * 50
logger.debug(f"总激活值: {total_activation:.2f}, 总节点数: {total_nodes}, 激活: {activation_ratio}")
return activation_ratio, keywords

3
src/chat/message_receive/message.py
View File

@@ -120,6 +120,9 @@ class MessageRecv(Message):
self.priority_mode = "interest"
self.priority_info = None
self.interest_value: float = 0.0
self.key_words = []
self.key_words_lite = []
def update_chat_stream(self, chat_stream: "ChatStream"):
self.chat_stream = chat_stream

24
src/chat/message_receive/storage.py
View File

@@ -14,6 +14,23 @@ logger = get_logger("message_storage")
class MessageStorage:
@staticmethod
def _serialize_keywords(keywords) -> str:
"""将关键词列表序列化为JSON字符串"""
if isinstance(keywords, list):
return orjson.dumps(keywords).decode("utf-8")
return "[]"
@staticmethod
def _deserialize_keywords(keywords_str: str) -> list:
"""将JSON字符串反序列化为关键词列表"""
if not keywords_str:
return []
try:
return orjson.loads(keywords_str)
except (orjson.JSONDecodeError, TypeError):
return []
@staticmethod
async def store_message(message: Union[MessageSending, MessageRecv], chat_stream: ChatStream) -> None:
"""存储消息到数据库"""
@@ -44,6 +61,8 @@ class MessageStorage:
is_picid = False
is_notify = False
is_command = False
key_words = ""
key_words_lite = ""
else:
filtered_display_message = ""
interest_value = message.interest_value
@@ -55,6 +74,9 @@ class MessageStorage:
is_picid = message.is_picid
is_notify = message.is_notify
is_command = message.is_command
# 序列化关键词列表为JSON字符串
key_words = MessageStorage._serialize_keywords(message.key_words)
key_words_lite = MessageStorage._serialize_keywords(message.key_words_lite)
chat_info_dict = chat_stream.to_dict()
user_info_dict = message.message_info.user_info.to_dict() # type: ignore
@@ -103,6 +125,8 @@ class MessageStorage:
is_picid=is_picid,
is_notify=is_notify,
is_command=is_command,
key_words=key_words,
key_words_lite=key_words_lite,
)
with get_db_session() as session:
session.add(new_message)