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fix: 将日志级别从trace更改为debug

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晴猫
2025-06-11 22:49:25 +09:00
parent 4747c151d5
commit fc7b9b61d9
9 changed files with 22 additions and 22 deletions
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2
src/chat/focus_chat/heartflow_message_processor.py
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@@ -75,7 +75,7 @@ async def _calculate_interest(message: MessageRecv) -> Tuple[float, bool]:
message.processed_plain_text,
fast_retrieval=True,
)
logger.trace(f"记忆激活率: {interested_rate:.2f}")
logger.debug(f"记忆激活率: {interested_rate:.2f}")
text_len = len(message.processed_plain_text)
# 根据文本长度调整兴趣度，长度越大兴趣度越高，但增长率递减，最低0.01，最高0.05

2
src/chat/heart_flow/observation/chatting_observation.py
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@@ -287,7 +287,7 @@ class ChattingObservation(Observation):
# print(f"构建中：self.person_list: {self.person_list}")
logger.trace(
logger.debug(
f"Chat {self.chat_id} - 压缩早期记忆：{self.mid_memory_info}\n现在聊天内容：{self.talking_message_str}"
)

12
src/chat/memory_system/Hippocampus.py
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@@ -409,7 +409,7 @@ class Hippocampus:
activation_values[neighbor] = new_activation
visited_nodes.add(neighbor)
nodes_to_process.append((neighbor, new_activation, current_depth + 1))
logger.trace(
logger.debug(
f"节点 '{neighbor}' 被激活，激活值: {new_activation:.2f} (通过 '{current_node}' 连接，强度: {strength}, 深度: {current_depth + 1})"
) # noqa: E501
@@ -580,7 +580,7 @@ class Hippocampus:
activation_values[neighbor] = new_activation
visited_nodes.add(neighbor)
nodes_to_process.append((neighbor, new_activation, current_depth + 1))
logger.trace(
logger.debug(
f"节点 '{neighbor}' 被激活，激活值: {new_activation:.2f} (通过 '{current_node}' 连接，强度: {strength}, 深度: {current_depth + 1})"
) # noqa: E501
@@ -733,7 +733,7 @@ class Hippocampus:
# 对每个关键词进行扩散式检索
for keyword in valid_keywords:
logger.trace(f"开始以关键词 '{keyword}' 为中心进行扩散检索 (最大深度: {max_depth}):")
logger.debug(f"开始以关键词 '{keyword}' 为中心进行扩散检索 (最大深度: {max_depth}):")
# 初始化激活值
activation_values = {keyword: 1.0}
# 记录已访问的节点
@@ -784,7 +784,7 @@ class Hippocampus:
# 计算激活节点数与总节点数的比值
total_activation = sum(activate_map.values())
logger.trace(f"总激活值: {total_activation:.2f}")
logger.debug(f"总激活值: {total_activation:.2f}")
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
@@ -1605,8 +1605,8 @@ class ParahippocampalGyrus:
if similarity >= similarity_threshold:
logger.debug(f"[整合] 节点 '{node}' 中发现相似项 (相似度: {similarity:.2f}):")
logger.trace(f" - '{item1}'")
logger.trace(f" - '{item2}'")
logger.debug(f" - '{item1}'")
logger.debug(f" - '{item2}'")
# 比较信息量
info1 = calculate_information_content(item1)

14
src/chat/message_receive/bot.py
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@@ -33,7 +33,7 @@ class ChatBot:
async def _ensure_started(self):
"""确保所有任务已启动"""
if not self._started:
logger.trace("确保ChatBot所有任务已启动")
logger.debug("确保ChatBot所有任务已启动")
self._started = True
@@ -166,23 +166,23 @@ class ChatBot:
template_group_name = None
async def preprocess():
logger.trace("开始预处理消息...")
logger.debug("开始预处理消息...")
# 如果在私聊中
if group_info is None:
logger.trace("检测到私聊消息")
logger.debug("检测到私聊消息")
if global_config.experimental.pfc_chatting:
logger.trace("进入PFC私聊处理流程")
logger.debug("进入PFC私聊处理流程")
# 创建聊天流
logger.trace(f"为{user_info.user_id}创建/获取聊天流")
logger.debug(f"为{user_info.user_id}创建/获取聊天流")
await self.only_process_chat.process_message(message)
await self._create_pfc_chat(message)
# 禁止PFC，进入普通的心流消息处理逻辑
else:
logger.trace("进入普通心流私聊处理")
logger.debug("进入普通心流私聊处理")
await self.heartflow_message_receiver.process_message(message_data)
# 群聊默认进入心流消息处理逻辑
else:
logger.trace(f"检测到群聊消息，群ID: {group_info.group_id}")
logger.debug(f"检测到群聊消息，群ID: {group_info.group_id}")
await self.heartflow_message_receiver.process_message(message_data)
if template_group_name:

4
src/chat/message_receive/message_sender.py
View File

@@ -41,9 +41,9 @@ async def send_message(
thinking_start_time=message.thinking_start_time,
is_emoji=message.is_emoji,
)
# logger.trace(f"{message.processed_plain_text},{typing_time},计算输入时间结束") # 减少日志
# logger.debug(f"{message.processed_plain_text},{typing_time},计算输入时间结束") # 减少日志
await asyncio.sleep(typing_time)
# logger.trace(f"{message.processed_plain_text},{typing_time},等待输入时间结束") # 减少日志
# logger.debug(f"{message.processed_plain_text},{typing_time},等待输入时间结束") # 减少日志
# --- 结束打字延迟 ---
message_preview = truncate_message(message.processed_plain_text)

2
src/chat/utils/utils.py
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@@ -328,7 +328,7 @@ def process_llm_response(text: str) -> list[str]:
# 先保护颜文字
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}")
logger.debug(f"保护颜文字后的文本: {protected_text}")
else:
protected_text = text
kaomoji_mapping = {}

4
src/chat/utils/utils_image.py
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@@ -228,7 +228,7 @@ class ImageManager:
description=description,
timestamp=current_timestamp,
)
logger.trace(f"保存图片元数据: {file_path}")
logger.debug(f"保存图片元数据: {file_path}")
except Exception as e:
logger.error(f"保存图片文件或元数据失败: {str(e)}")
@@ -288,7 +288,7 @@ class ImageManager:
# 计算和上一张选中帧的差异（均方误差 MSE）
if last_selected_frame_np is not None:
mse = np.mean((current_frame_np - last_selected_frame_np) ** 2)
# logger.trace(f"帧 {i} 与上一选中帧的 MSE: {mse}") # 可以取消注释来看差异值
# logger.debug(f"帧 {i} 与上一选中帧的 MSE: {mse}") # 可以取消注释来看差异值
# 如果差异够大，就选它！
if mse > similarity_threshold:

2
src/llm_models/utils_model.py
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@@ -183,7 +183,7 @@ class LLMRequest:
status="success",
timestamp=datetime.now(), # Peewee 会处理 DateTimeField
)
logger.trace(
logger.debug(
f"Token使用情况 - 模型: {self.model_name}, "
f"用户: {user_id}, 类型: {request_type}, "
f"提示词: {prompt_tokens}, 完成: {completion_tokens}, "

2
src/person_info/person_info.py
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@@ -459,7 +459,7 @@ class PersonInfoManager:
if field_name not in PersonInfo._meta.fields:
if field_name in person_info_default:
result[field_name] = copy.deepcopy(person_info_default[field_name])
logger.trace(f"字段'{field_name}'不在Peewee模型中，使用默认配置值。")
logger.debug(f"字段'{field_name}'不在Peewee模型中，使用默认配置值。")
else:
logger.debug(f"get_values查询失败：字段'{field_name}'未在Peewee模型和默认配置中定义。")
result[field_name] = None