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Merge pull request #240 from SengokuCola/debug

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记忆和遗忘的可自定义
This commit is contained in:
SengokuCola
2025-03-12 01:33:15 +08:00
committed by GitHub
parent c20ad28e8b 7274573736
commit 1ac5c225af
4 changed files with 25 additions and 10 deletions
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2
src/plugins/chat/__init__.py
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@@ -127,7 +127,7 @@ async def build_memory_task():
async def forget_memory_task(): async def forget_memory_task():
"""每30秒执行一次记忆构建""" """每30秒执行一次记忆构建"""
print("\033[1;32m[记忆遗忘]\033[0m 开始遗忘记忆...") print("\033[1;32m[记忆遗忘]\033[0m 开始遗忘记忆...")
await hippocampus.operation_forget_topic(percentage=0.1) await hippocampus.operation_forget_topic(percentage=global_config.memory_forget_percentage)
print("\033[1;32m[记忆遗忘]\033[0m 记忆遗忘完成") print("\033[1;32m[记忆遗忘]\033[0m 记忆遗忘完成")

14
src/plugins/chat/config.py
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@@ -37,8 +37,7 @@ class BotConfig:
ban_user_id = set() ban_user_id = set()
build_memory_interval: int = 30 # 记忆构建间隔（秒）
forget_memory_interval: int = 300 # 记忆遗忘间隔（秒）
EMOJI_CHECK_INTERVAL: int = 120 # 表情包检查间隔（分钟） EMOJI_CHECK_INTERVAL: int = 120 # 表情包检查间隔（分钟）
EMOJI_REGISTER_INTERVAL: int = 10 # 表情包注册间隔（分钟） EMOJI_REGISTER_INTERVAL: int = 10 # 表情包注册间隔（分钟）
EMOJI_SAVE: bool = True # 偷表情包 EMOJI_SAVE: bool = True # 偷表情包
@@ -96,6 +95,12 @@ class BotConfig:
PERSONALITY_2: float = 0.3 # 第二种人格概率 PERSONALITY_2: float = 0.3 # 第二种人格概率
PERSONALITY_3: float = 0.1 # 第三种人格概率 PERSONALITY_3: float = 0.1 # 第三种人格概率
build_memory_interval: int = 600 # 记忆构建间隔（秒）
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
memory_compress_rate: float = 0.1 # 记忆压缩率
memory_ban_words: list = field( memory_ban_words: list = field(
default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"] default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"]
) # 添加新的配置项默认值 ) # 添加新的配置项默认值
@@ -295,6 +300,11 @@ class BotConfig:
if config.INNER_VERSION in SpecifierSet(">=0.0.4"): if config.INNER_VERSION in SpecifierSet(">=0.0.4"):
config.memory_ban_words = set(memory_config.get("memory_ban_words", [])) config.memory_ban_words = set(memory_config.get("memory_ban_words", []))
if config.INNER_VERSION in SpecifierSet(">=0.0.7"):
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)
def mood(parent: dict): def mood(parent: dict):
mood_config = parent["mood"] mood_config = parent["mood"]
config.mood_update_interval = mood_config.get("mood_update_interval", config.mood_update_interval) config.mood_update_interval = mood_config.get("mood_update_interval", config.mood_update_interval)

6
src/plugins/memory_system/memory.py
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@@ -303,7 +303,7 @@ class Hippocampus:
return topic_num return topic_num
async def operation_build_memory(self, chat_size=20): async def operation_build_memory(self, chat_size=20):
time_frequency = {'near': 3, 'mid': 8, 'far': 5} time_frequency = {'near': 1, 'mid': 4, 'far': 4}
memory_samples = self.get_memory_sample(chat_size, time_frequency) memory_samples = self.get_memory_sample(chat_size, time_frequency)
for i, messages in enumerate(memory_samples, 1): for i, messages in enumerate(memory_samples, 1):
@@ -315,7 +315,7 @@ class Hippocampus:
bar = '█' * filled_length + '-' * (bar_length - filled_length) bar = '█' * filled_length + '-' * (bar_length - filled_length)
logger.debug(f"进度: [{bar}] {progress:.1f}% ({i}/{len(memory_samples)})") logger.debug(f"进度: [{bar}] {progress:.1f}% ({i}/{len(memory_samples)})")
compress_rate = 0.1 compress_rate = global_config.memory_compress_rate
compressed_memory, similar_topics_dict = await self.memory_compress(messages, compress_rate) compressed_memory, similar_topics_dict = await self.memory_compress(messages, compress_rate)
logger.info(f"压缩后记忆数量: {len(compressed_memory)}，似曾相识的话题: {len(similar_topics_dict)}") logger.info(f"压缩后记忆数量: {len(compressed_memory)}，似曾相识的话题: {len(similar_topics_dict)}")
@@ -551,7 +551,7 @@ class Hippocampus:
# print(f"float(last_modified):{float(last_modified)}" ) # print(f"float(last_modified):{float(last_modified)}" )
# print(f"current_time:{current_time}") # print(f"current_time:{current_time}")
# print(f"current_time - last_modified:{current_time - last_modified}") # print(f"current_time - last_modified:{current_time - last_modified}")
if current_time - last_modified > 3600*24: # test if current_time - last_modified > 3600*global_config.memory_forget_time: # test
current_strength = edge_data.get('strength', 1) current_strength = edge_data.get('strength', 1)
new_strength = current_strength - 1 new_strength = current_strength - 1

11
template/bot_config_template.toml
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@@ -1,5 +1,5 @@
[inner] [inner]
version = "0.0.7" version = "0.0.8"
#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 #如果新增项目，请在BotConfig类下新增相应的变量
@@ -65,8 +65,13 @@ model_r1_distill_probability = 0.1 # 麦麦回答时选择次要回复模型3
max_response_length = 1024 # 麦麦回答的最大token数 max_response_length = 1024 # 麦麦回答的最大token数
[memory] [memory]
build_memory_interval = 300 # 记忆构建间隔 单位秒 build_memory_interval = 600 # 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
forget_memory_interval = 300 # 记忆遗忘间隔 单位秒 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 = 600 # 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
memory_forget_time = 24 #多长时间后的记忆会被遗忘 单位小时
memory_forget_percentage = 0.01 # 记忆遗忘比例 控制记忆遗忘程度 越大遗忘越多 建议保持默认
memory_ban_words = [ #不希望记忆的词 memory_ban_words = [ #不希望记忆的词
# "403","张三" # "403","张三"