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添加有关时区的设置，可以在bot_config里设置时区，来改变机器人作息，以及一些llm logger的小tweak

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lmst2
2025-03-31 21:10:51 +01:00
parent bc4472dfa1
commit 220219c9ba
5 changed files with 45 additions and 35 deletions
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4
.gitignore vendored
View File

@@ -6,6 +6,10 @@ log/
logs/ logs/
/test /test
/src/test /src/test
nonebot-maibot-adapter/
*.zip
run.bat
run.py
message_queue_content.txt message_queue_content.txt
message_queue_content.bat message_queue_content.bat
message_queue_window.bat message_queue_window.bat

2
src/plugins/config/config.py
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@@ -149,6 +149,7 @@ class BotConfig:
PROMPT_SCHEDULE_GEN = "无日程" PROMPT_SCHEDULE_GEN = "无日程"
SCHEDULE_DOING_UPDATE_INTERVAL: int = 300 # 日程表更新间隔 单位秒 SCHEDULE_DOING_UPDATE_INTERVAL: int = 300 # 日程表更新间隔 单位秒
SCHEDULE_TEMPERATURE: float = 0.5 # 日程表温度，建议0.5-1.0 SCHEDULE_TEMPERATURE: float = 0.5 # 日程表温度，建议0.5-1.0
TIME_ZONE: str = "Asia/Shanghai" # 时区
# message # message
MAX_CONTEXT_SIZE: int = 15 # 上下文最大消息数 MAX_CONTEXT_SIZE: int = 15 # 上下文最大消息数
@@ -349,6 +350,7 @@ class BotConfig:
) )
if config.INNER_VERSION in SpecifierSet(">=1.0.2"): if config.INNER_VERSION in SpecifierSet(">=1.0.2"):
config.SCHEDULE_TEMPERATURE = schedule_config.get("schedule_temperature", config.SCHEDULE_TEMPERATURE) config.SCHEDULE_TEMPERATURE = schedule_config.get("schedule_temperature", config.SCHEDULE_TEMPERATURE)
config.TIME_ZONE = schedule_config.get("time_zone", config.TIME_ZONE)
def emoji(parent: dict): def emoji(parent: dict):
emoji_config = parent["emoji"] emoji_config = parent["emoji"]

1
src/plugins/memory_system/Hippocampus.py
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@@ -14,7 +14,6 @@ from src.common.logger import get_module_logger, LogConfig, MEMORY_STYLE_CONFIG
from src.plugins.memory_system.sample_distribution import MemoryBuildScheduler # 分布生成器 from src.plugins.memory_system.sample_distribution import MemoryBuildScheduler # 分布生成器
from .memory_config import MemoryConfig from .memory_config import MemoryConfig
def get_closest_chat_from_db(length: int, timestamp: str): def get_closest_chat_from_db(length: int, timestamp: str):
# print(f"获取最接近指定时间戳的聊天记录，长度: {length}, 时间戳: {timestamp}") # print(f"获取最接近指定时间戳的聊天记录，长度: {length}, 时间戳: {timestamp}")
# print(f"当前时间: {timestamp},转换后时间: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(timestamp))}") # print(f"当前时间: {timestamp},转换后时间: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(timestamp))}")

56
src/plugins/models/utils_model.py
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@@ -179,9 +179,6 @@ class LLM_request:
# logger.debug(f"{logger_msg}发送请求到URL: {api_url}") # logger.debug(f"{logger_msg}发送请求到URL: {api_url}")
# logger.info(f"使用模型: {self.model_name}") # logger.info(f"使用模型: {self.model_name}")
# 流式输出标志
if stream_mode:
payload["stream"] = stream_mode
# 构建请求体 # 构建请求体
if image_base64: if image_base64:
@@ -189,6 +186,11 @@ class LLM_request:
elif payload is None: elif payload is None:
payload = await self._build_payload(prompt) payload = await self._build_payload(prompt)
# 流式输出标志
# 先构建payload，再添加流式输出标志
if stream_mode:
payload["stream"] = stream_mode
for retry in range(policy["max_retries"]): for retry in range(policy["max_retries"]):
try: try:
# 使用上下文管理器处理会话 # 使用上下文管理器处理会话
@@ -202,13 +204,13 @@ class LLM_request:
# 处理需要重试的状态码 # 处理需要重试的状态码
if response.status in policy["retry_codes"]: if response.status in policy["retry_codes"]:
wait_time = policy["base_wait"] * (2**retry) wait_time = policy["base_wait"] * (2**retry)
logger.warning(f"错误码: {response.status}, 等待 {wait_time}秒后重试") logger.warning(f"模型 {self.model_name} 错误码: {response.status}, 等待 {wait_time}秒后重试")
if response.status == 413: if response.status == 413:
logger.warning("请求体过大，尝试压缩...") logger.warning("请求体过大，尝试压缩...")
image_base64 = compress_base64_image_by_scale(image_base64) image_base64 = compress_base64_image_by_scale(image_base64)
payload = await self._build_payload(prompt, image_base64, image_format) payload = await self._build_payload(prompt, image_base64, image_format)
elif response.status in [500, 503]: elif response.status in [500, 503]:
logger.error(f"错误码: {response.status} - {error_code_mapping.get(response.status)}") logger.error(f"模型 {self.model_name} 错误码: {response.status} - {error_code_mapping.get(response.status)}")
raise RuntimeError("服务器负载过高，模型恢复失败QAQ") raise RuntimeError("服务器负载过高，模型恢复失败QAQ")
else: else:
logger.warning(f"请求限制(429)，等待{wait_time}秒后重试...") logger.warning(f"请求限制(429)，等待{wait_time}秒后重试...")
@@ -216,7 +218,7 @@ class LLM_request:
await asyncio.sleep(wait_time) await asyncio.sleep(wait_time)
continue continue
elif response.status in policy["abort_codes"]: elif response.status in policy["abort_codes"]:
logger.error(f"错误码: {response.status} - {error_code_mapping.get(response.status)}") logger.error(f"模型 {self.model_name} 错误码: {response.status} - {error_code_mapping.get(response.status)}")
# 尝试获取并记录服务器返回的详细错误信息 # 尝试获取并记录服务器返回的详细错误信息
try: try:
error_json = await response.json() error_json = await response.json()
@@ -228,7 +230,7 @@ class LLM_request:
error_message = error_obj.get("message") error_message = error_obj.get("message")
error_status = error_obj.get("status") error_status = error_obj.get("status")
logger.error( logger.error(
f"服务器错误详情: 代码={error_code}, 状态={error_status}, " f"模型 {self.model_name} 服务器错误详情: 代码={error_code}, 状态={error_status}, "
f"消息={error_message}" f"消息={error_message}"
) )
elif isinstance(error_json, dict) and "error" in error_json: elif isinstance(error_json, dict) and "error" in error_json:
@@ -238,13 +240,13 @@ class LLM_request:
error_message = error_obj.get("message") error_message = error_obj.get("message")
error_status = error_obj.get("status") error_status = error_obj.get("status")
logger.error( logger.error(
f"服务器错误详情: 代码={error_code}, 状态={error_status}, 消息={error_message}" f"模型 {self.model_name} 服务器错误详情: 代码={error_code}, 状态={error_status}, 消息={error_message}"
) )
else: else:
# 记录原始错误响应内容 # 记录原始错误响应内容
logger.error(f"服务器错误响应: {error_json}") logger.error(f"模型 {self.model_name} 服务器错误响应: {error_json}")
except Exception as e: except Exception as e:
logger.warning(f"无法解析服务器错误响应: {str(e)}") logger.warning(f"模型 {self.model_name} 无法解析服务器错误响应: {str(e)}")
if response.status == 403: if response.status == 403:
# 只针对硅基流动的V3和R1进行降级处理 # 只针对硅基流动的V3和R1进行降级处理
@@ -273,7 +275,7 @@ class LLM_request:
retry -= 1 # 不计入重试次数 retry -= 1 # 不计入重试次数
continue continue
raise RuntimeError(f"请求被拒绝: {error_code_mapping.get(response.status)}") raise RuntimeError(f"模型 {self.model_name} 请求被拒绝: {error_code_mapping.get(response.status)}")
response.raise_for_status() response.raise_for_status()
reasoning_content = "" reasoning_content = ""
@@ -318,12 +320,12 @@ class LLM_request:
flag_delta_content_finished = True flag_delta_content_finished = True
except Exception as e: except Exception as e:
logger.exception(f"解析流式输出错误: {str(e)}") logger.exception(f"模型 {self.model_name} 解析流式输出错误: {str(e)}")
except GeneratorExit: except GeneratorExit:
logger.warning("流式输出被中断") logger.warning(f"模型 {self.model_name} 流式输出被中断")
break break
except Exception as e: except Exception as e:
logger.error(f"处理流式输出时发生错误: {str(e)}") logger.error(f"模型 {self.model_name} 处理流式输出时发生错误: {str(e)}")
break break
content = accumulated_content content = accumulated_content
think_match = re.search(r"<think>(.*?)</think>", content, re.DOTALL) think_match = re.search(r"<think>(.*?)</think>", content, re.DOTALL)
@@ -353,7 +355,7 @@ class LLM_request:
# 处理aiohttp抛出的响应错误 # 处理aiohttp抛出的响应错误
if retry < policy["max_retries"] - 1: if retry < policy["max_retries"] - 1:
wait_time = policy["base_wait"] * (2**retry) wait_time = policy["base_wait"] * (2**retry)
logger.error(f"HTTP响应错误，等待{wait_time}秒后重试... 状态码: {e.status}, 错误: {e.message}") logger.error(f"模型 {self.model_name} HTTP响应错误，等待{wait_time}秒后重试... 状态码: {e.status}, 错误: {e.message}")
try: try:
if hasattr(e, "response") and e.response and hasattr(e.response, "text"): if hasattr(e, "response") and e.response and hasattr(e.response, "text"):
error_text = await e.response.text() error_text = await e.response.text()
@@ -364,27 +366,27 @@ class LLM_request:
if "error" in error_item and isinstance(error_item["error"], dict): if "error" in error_item and isinstance(error_item["error"], dict):
error_obj = error_item["error"] error_obj = error_item["error"]
logger.error( logger.error(
f"服务器错误详情: 代码={error_obj.get('code')}, " f"模型 {self.model_name} 服务器错误详情: 代码={error_obj.get('code')}, "
f"状态={error_obj.get('status')}, " f"状态={error_obj.get('status')}, "
f"消息={error_obj.get('message')}" f"消息={error_obj.get('message')}"
) )
elif isinstance(error_json, dict) and "error" in error_json: elif isinstance(error_json, dict) and "error" in error_json:
error_obj = error_json.get("error", {}) error_obj = error_json.get("error", {})
logger.error( logger.error(
f"服务器错误详情: 代码={error_obj.get('code')}, " f"模型 {self.model_name} 服务器错误详情: 代码={error_obj.get('code')}, "
f"状态={error_obj.get('status')}, " f"状态={error_obj.get('status')}, "
f"消息={error_obj.get('message')}" f"消息={error_obj.get('message')}"
) )
else: else:
logger.error(f"服务器错误响应: {error_json}") logger.error(f"模型 {self.model_name} 服务器错误响应: {error_json}")
except (json.JSONDecodeError, TypeError) as json_err: except (json.JSONDecodeError, TypeError) as json_err:
logger.warning(f"响应不是有效的JSON: {str(json_err)}, 原始内容: {error_text[:200]}") logger.warning(f"模型 {self.model_name} 响应不是有效的JSON: {str(json_err)}, 原始内容: {error_text[:200]}")
except (AttributeError, TypeError, ValueError) as parse_err: except (AttributeError, TypeError, ValueError) as parse_err:
logger.warning(f"无法解析响应错误内容: {str(parse_err)}") logger.warning(f"模型 {self.model_name} 无法解析响应错误内容: {str(parse_err)}")
await asyncio.sleep(wait_time) await asyncio.sleep(wait_time)
else: else:
logger.critical(f"HTTP响应错误达到最大重试次数: 状态码: {e.status}, 错误: {e.message}") logger.critical(f"模型 {self.model_name} HTTP响应错误达到最大重试次数: 状态码: {e.status}, 错误: {e.message}")
# 安全地检查和记录请求详情 # 安全地检查和记录请求详情
if ( if (
image_base64 image_base64
@@ -401,14 +403,14 @@ class LLM_request:
f"{image_base64[:10]}...{image_base64[-10:]}" f"{image_base64[:10]}...{image_base64[-10:]}"
) )
logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {payload}") logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {payload}")
raise RuntimeError(f"API请求失败: 状态码 {e.status}, {e.message}") from e raise RuntimeError(f"模型 {self.model_name} API请求失败: 状态码 {e.status}, {e.message}") from e
except Exception as e: except Exception as e:
if retry < policy["max_retries"] - 1: if retry < policy["max_retries"] - 1:
wait_time = policy["base_wait"] * (2**retry) wait_time = policy["base_wait"] * (2**retry)
logger.error(f"请求失败，等待{wait_time}秒后重试... 错误: {str(e)}") logger.error(f"模型 {self.model_name} 请求失败，等待{wait_time}秒后重试... 错误: {str(e)}")
await asyncio.sleep(wait_time) await asyncio.sleep(wait_time)
else: else:
logger.critical(f"请求失败: {str(e)}") logger.critical(f"模型 {self.model_name} 请求失败: {str(e)}")
# 安全地检查和记录请求详情 # 安全地检查和记录请求详情
if ( if (
image_base64 image_base64
@@ -425,10 +427,10 @@ class LLM_request:
f"{image_base64[:10]}...{image_base64[-10:]}" f"{image_base64[:10]}...{image_base64[-10:]}"
) )
logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {payload}") logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {payload}")
raise RuntimeError(f"API请求失败: {str(e)}") from e raise RuntimeError(f"模型 {self.model_name} API请求失败: {str(e)}") from e
logger.error("达到最大重试次数，请求仍然失败") logger.error(f"模型 {self.model_name} 达到最大重试次数，请求仍然失败")
raise RuntimeError("达到最大重试次数，API请求仍然失败") raise RuntimeError(f"模型 {self.model_name} 达到最大重试次数，API请求仍然失败")
async def _transform_parameters(self, params: dict) -> dict: async def _transform_parameters(self, params: dict) -> dict:
""" """

17
src/plugins/schedule/schedule_generator.py
View File

@@ -3,6 +3,7 @@ import os
import sys import sys
from typing import Dict from typing import Dict
import asyncio import asyncio
from dateutil import tz
# 添加项目根目录到 Python 路径 # 添加项目根目录到 Python 路径
root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../..")) root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
@@ -13,6 +14,8 @@ from src.common.logger import get_module_logger, SCHEDULE_STYLE_CONFIG, LogConfi
from src.plugins.models.utils_model import LLM_request # noqa: E402 from src.plugins.models.utils_model import LLM_request # noqa: E402
from src.plugins.config.config import global_config # noqa: E402 from src.plugins.config.config import global_config # noqa: E402
TIME_ZONE = tz.gettz(global_config.TIME_ZONE) # 设置时区
schedule_config = LogConfig( schedule_config = LogConfig(
# 使用海马体专用样式 # 使用海马体专用样式
@@ -44,7 +47,7 @@ class ScheduleGenerator:
self.personality = "" self.personality = ""
self.behavior = "" self.behavior = ""
self.start_time = datetime.datetime.now() self.start_time = datetime.datetime.now(TIME_ZONE)
self.schedule_doing_update_interval = 300 # 最好大于60 self.schedule_doing_update_interval = 300 # 最好大于60
@@ -74,7 +77,7 @@ class ScheduleGenerator:
while True: while True:
# print(self.get_current_num_task(1, True)) # print(self.get_current_num_task(1, True))
current_time = datetime.datetime.now() current_time = datetime.datetime.now(TIME_ZONE)
# 检查是否需要重新生成日程（日期变化） # 检查是否需要重新生成日程（日期变化）
if current_time.date() != self.start_time.date(): if current_time.date() != self.start_time.date():
@@ -100,7 +103,7 @@ class ScheduleGenerator:
Returns: Returns:
tuple: (today_schedule_text, today_schedule) 今天的日程文本和解析后的日程字典 tuple: (today_schedule_text, today_schedule) 今天的日程文本和解析后的日程字典
""" """
today = datetime.datetime.now() today = datetime.datetime.now(TIME_ZONE)
yesterday = today - datetime.timedelta(days=1) yesterday = today - datetime.timedelta(days=1)
# 先检查昨天的日程 # 先检查昨天的日程
@@ -156,7 +159,7 @@ class ScheduleGenerator:
"""打印完整的日程安排""" """打印完整的日程安排"""
if not self.today_schedule_text: if not self.today_schedule_text:
logger.warning("今日日程有误，将在下次运行时重新生成") logger.warning("今日日程有误，将在下次运行时重新生成")
db.schedule.delete_one({"date": datetime.datetime.now().strftime("%Y-%m-%d")}) db.schedule.delete_one({"date": datetime.datetime.now(TIME_ZONE).strftime("%Y-%m-%d")})
else: else:
logger.info("=== 今日日程安排 ===") logger.info("=== 今日日程安排 ===")
logger.info(self.today_schedule_text) logger.info(self.today_schedule_text)
@@ -165,7 +168,7 @@ class ScheduleGenerator:
async def update_today_done_list(self): async def update_today_done_list(self):
# 更新数据库中的 today_done_list # 更新数据库中的 today_done_list
today_str = datetime.datetime.now().strftime("%Y-%m-%d") today_str = datetime.datetime.now(TIME_ZONE).strftime("%Y-%m-%d")
existing_schedule = db.schedule.find_one({"date": today_str}) existing_schedule = db.schedule.find_one({"date": today_str})
if existing_schedule: if existing_schedule:
@@ -177,7 +180,7 @@ class ScheduleGenerator:
async def move_doing(self, mind_thinking: str = ""): async def move_doing(self, mind_thinking: str = ""):
try: try:
current_time = datetime.datetime.now() current_time = datetime.datetime.now(TIME_ZONE)
if mind_thinking: if mind_thinking:
doing_prompt = self.construct_doing_prompt(current_time, mind_thinking) doing_prompt = self.construct_doing_prompt(current_time, mind_thinking)
else: else:
@@ -246,7 +249,7 @@ class ScheduleGenerator:
def save_today_schedule_to_db(self): def save_today_schedule_to_db(self):
"""保存日程到数据库，同时初始化 today_done_list""" """保存日程到数据库，同时初始化 today_done_list"""
date_str = datetime.datetime.now().strftime("%Y-%m-%d") date_str = datetime.datetime.now(TIME_ZONE).strftime("%Y-%m-%d")
schedule_data = { schedule_data = {
"date": date_str, "date": date_str,
"schedule": self.today_schedule_text, "schedule": self.today_schedule_text,