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use structlog instead of loguru

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春河晴
2025-06-11 15:17:08 +09:00
parent 0cb595218e
commit 7b4e7b94f8
132 changed files with 283 additions and 1804 deletions
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src/chat/memory_system/Hippocampus.py
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@@ -12,7 +12,7 @@ import networkx as nx
import numpy as np
from collections import Counter
from ...llm_models.utils_model import LLMRequest
from src.common.logger_manager import get_logger
from src.common.logger import get_logger
from src.chat.memory_system.sample_distribution import MemoryBuildScheduler # 分布生成器
from ..utils.chat_message_builder import (
get_raw_msg_by_timestamp,
@@ -829,7 +829,7 @@ class EntorhinalCortex:
)
if messages:
time_diff = (datetime.datetime.now().timestamp() - timestamp) / 3600
logger.success(f"成功抽取 {time_diff:.1f} 小时前的消息样本，共{len(messages)}条")
logger.info(f"成功抽取 {time_diff:.1f} 小时前的消息样本，共{len(messages)}条")
chat_samples.append(messages)
else:
logger.debug(f"时间戳 {timestamp} 的消息无需记忆")
@@ -1046,8 +1046,8 @@ class EntorhinalCortex:
GraphEdges.delete().where((GraphEdges.source == source) & (GraphEdges.target == target)).execute()
end_time = time.time()
logger.success(f"[同步] 总耗时: {end_time - start_time:.2f}秒")
logger.success(f"[同步] 同步了 {len(memory_nodes)} 个节点和 {len(memory_edges)} 条边")
logger.info(f"[同步] 总耗时: {end_time - start_time:.2f}秒")
logger.info(f"[同步] 同步了 {len(memory_nodes)} 个节点和 {len(memory_edges)} 条边")
async def resync_memory_to_db(self):
"""清空数据库并重新同步所有记忆数据"""
@@ -1133,8 +1133,8 @@ class EntorhinalCortex:
logger.info(f"[数据库] 写入 {len(edges_data)} 条边耗时: {edge_end - edge_start:.2f}秒")
end_time = time.time()
logger.success(f"[数据库] 重新同步完成，总耗时: {end_time - start_time:.2f}秒")
logger.success(f"[数据库] 同步了 {len(nodes_data)} 个节点和 {len(edges_data)} 条边")
logger.info(f"[数据库] 重新同步完成，总耗时: {end_time - start_time:.2f}秒")
logger.info(f"[数据库] 同步了 {len(nodes_data)} 个节点和 {len(edges_data)} 条边")
def sync_memory_from_db(self):
"""从数据库同步数据到内存中的图结构"""
@@ -1209,7 +1209,7 @@ class EntorhinalCortex:
)
if need_update:
logger.success("[数据库] 已为缺失的时间字段进行补充")
logger.info("[数据库] 已为缺失的时间字段进行补充")
# 负责整合，遗忘，合并记忆
@@ -1387,7 +1387,7 @@ class ParahippocampalGyrus:
logger.debug(f"进度: [{bar}] {progress:.1f}% ({i}/{len(memory_samples)})")
if all_added_nodes:
logger.success(f"更新记忆: {', '.join(all_added_nodes)}")
logger.info(f"更新记忆: {', '.join(all_added_nodes)}")
if all_added_edges:
logger.debug(f"强化连接: {', '.join(all_added_edges)}")
if all_connected_nodes:
@@ -1396,7 +1396,7 @@ class ParahippocampalGyrus:
await self.hippocampus.entorhinal_cortex.sync_memory_to_db()
end_time = time.time()
logger.success(f"---------------------记忆构建耗时: {end_time - start_time:.2f} 秒---------------------")
logger.info(f"---------------------记忆构建耗时: {end_time - start_time:.2f} 秒---------------------")
async def operation_forget_topic(self, percentage=0.005):
start_time = time.time()
@@ -1686,7 +1686,7 @@ class HippocampusManager:
node_count = len(memory_graph.nodes())
edge_count = len(memory_graph.edges())
logger.success(f"""--------------------------------
logger.info(f"""--------------------------------
记忆系统参数配置:
构建间隔: {global_config.memory.memory_build_interval}秒|样本数: {global_config.memory.memory_build_sample_num},长度: {global_config.memory.memory_build_sample_length}|压缩率: {global_config.memory.memory_compress_rate}
记忆构建分布: {global_config.memory.memory_build_distribution}