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fix ruff

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This commit is contained in:
SengokuCola
2025-03-27 00:23:13 +08:00
parent 5886b1c849
commit 8da4729c17
5 changed files with 49 additions and 24 deletions
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6
src/plugins/chat/__init__.py
View File

@@ -84,7 +84,11 @@ async def start_background_tasks():
@driver.on_startup
async def init_schedule():
"""在 NoneBot2 启动时初始化日程系统"""
bot_schedule.initialize(name=global_config.BOT_NICKNAME, personality=global_config.PROMPT_PERSONALITY, behavior=global_config.PROMPT_SCHEDULE_GEN, interval=global_config.SCHEDULE_DOING_UPDATE_INTERVAL)
bot_schedule.initialize(
name=global_config.BOT_NICKNAME,
personality=global_config.PROMPT_PERSONALITY,
behavior=global_config.PROMPT_SCHEDULE_GEN,
interval=global_config.SCHEDULE_DOING_UPDATE_INTERVAL)
asyncio.create_task(bot_schedule.mai_schedule_start())
@driver.on_startup

2
src/plugins/chat/prompt_builder.py
View File

@@ -57,7 +57,7 @@ class PromptBuilder:
mood_prompt = mood_manager.get_prompt()
# 日程构建
schedule_prompt = f'''你现在正在做的事情是：{bot_schedule.get_current_num_task(num = 1,time_info = False)}'''
# schedule_prompt = f'''你现在正在做的事情是：{bot_schedule.get_current_num_task(num = 1,time_info = False)}'''
# 获取聊天上下文
chat_in_group = True

3
src/plugins/schedule/offline_llm.py
View File

@@ -1,10 +1,7 @@
import asyncio
import os
import time
from typing import Tuple, Union
import aiohttp
import requests
from src.common.logger import get_module_logger
logger = get_module_logger("offline_llm")

18
src/plugins/schedule/schedule_generator.py
View File

@@ -24,7 +24,7 @@ logger = get_module_logger("scheduler", config=schedule_config)
class ScheduleGenerator:
# enable_output: bool = True
def __init__(self, ):
def __init__(self):
# 使用离线LLM模型
self.llm_scheduler_all = LLM_request(
model= global_config.llm_reasoning, temperature=0.9, max_tokens=7000,request_type="schedule")
@@ -45,7 +45,11 @@ class ScheduleGenerator:
self.schedule_doing_update_interval = 300 #最好大于60
def initialize(self,name: str = "bot_name", personality: str = "你是一个爱国爱党的新时代青年", behavior: str = "你非常外向，喜欢尝试新事物和人交流",interval: int = 60):
def initialize(
self,name: str = "bot_name",
personality: str = "你是一个爱国爱党的新时代青年",
behavior: str = "你非常外向，喜欢尝试新事物和人交流",
interval: int = 60):
"""初始化日程系统"""
self.name = name
self.behavior = behavior
@@ -117,7 +121,7 @@ class ScheduleGenerator:
prompt = f"你是{self.name}，{self.personality}，{self.behavior}"
prompt += f"你昨天的日程是：{self.yesterday_schedule_text}\n"
prompt += f"请为你生成{date_str}（{weekday}）的日程安排，结合你的个人特点和行为习惯\n"
prompt += "推测你的日程安排，包括你一天都在做什么，从起床到睡眠，有什么发现和思考，具体一些，详细一些，需要1500字以上，精确到每半个小时，记得写明时间\n"
prompt += "推测你的日程安排，包括你一天都在做什么，从起床到睡眠，有什么发现和思考，具体一些，详细一些，需要1500字以上，精确到每半个小时，记得写明时间\n" #noqa: E501
prompt += "直接返回你的日程，从起床到睡觉，不要输出其他内容："
return prompt
@@ -132,7 +136,7 @@ class ScheduleGenerator:
prompt = f"你是{self.name}，{self.personality}，{self.behavior}"
prompt += f"你今天的日程是：{self.today_schedule_text}\n"
prompt += f"你之前做了的事情是：{previous_doings}，从之前到现在已经过去了{self.schedule_doing_update_interval/60}分钟了\n"
prompt += f"你之前做了的事情是：{previous_doings}，从之前到现在已经过去了{self.schedule_doing_update_interval/60}分钟了\n" #noqa: E501
if mind_thinking:
prompt += f"你脑子里在想：{mind_thinking}\n"
prompt += f"现在是{now_time}，结合你的个人特点和行为习惯,"
@@ -284,7 +288,11 @@ class ScheduleGenerator:
async def main():
# 使用示例
scheduler = ScheduleGenerator()
scheduler.initialize(name="麦麦", personality="你叫麦麦，你19岁，是一个大二的女大学生，你有一头黑色短发，你会刷贴吧，你现在在学习心理学", behavior="你比较内向，一般熬夜比较晚，然后第二天早上10点起床吃早午饭",interval=60)
scheduler.initialize(
name="麦麦",
personality="你叫麦麦，你19岁，是一个大二的女大学生，你有一头黑色短发，你会刷贴吧，你现在在学习心理学",
behavior="你比较内向，一般熬夜比较晚，然后第二天早上10点起床吃早午饭",
interval=60)
await scheduler.mai_schedule_start()

44
配置文件错误排查.py
View File

@@ -1,8 +1,7 @@
import tomli
import sys
import re
from pathlib import Path
from typing import Dict, Any, List, Set, Tuple
from typing import Dict, Any, List, Tuple
def load_toml_file(file_path: str) -> Dict[str, Any]:
"""加载TOML文件"""
@@ -184,10 +183,15 @@ def check_model_configurations(config: Dict[str, Any], env_vars: Dict[str, str])
provider = model_config["provider"].upper()
# 检查拼写错误
for known_provider, correct_provider in reverse_mapping.items():
for known_provider, _correct_provider in reverse_mapping.items():
# 使用模糊匹配检测拼写错误
if provider != known_provider and _similar_strings(provider, known_provider) and provider not in reverse_mapping:
errors.append(f"[model.{model_name}]的provider '{model_config['provider']}' 可能拼写错误，应为 '{known_provider}'")
if (provider != known_provider and
_similar_strings(provider, known_provider) and
provider not in reverse_mapping):
errors.append(
f"[model.{model_name}]的provider '{model_config['provider']}' "
f"可能拼写错误，应为 '{known_provider}'"
)
break
return errors
@@ -223,7 +227,7 @@ def check_api_providers(config: Dict[str, Any], env_vars: Dict[str, str]) -> Lis
# 检查配置文件中使用的所有提供商
used_providers = set()
for model_category, model_config in config["model"].items():
for _model_category, model_config in config["model"].items():
if "provider" in model_config:
provider = model_config["provider"]
used_providers.add(provider)
@@ -247,7 +251,7 @@ def check_api_providers(config: Dict[str, Any], env_vars: Dict[str, str]) -> Lis
# 特别检查常见的拼写错误
for provider in used_providers:
if provider.upper() == "SILICONFOLW":
errors.append(f"提供商 'SILICONFOLW' 存在拼写错误，应为 'SILICONFLOW'")
errors.append("提供商 'SILICONFOLW' 存在拼写错误，应为 'SILICONFLOW'")
return errors
@@ -272,7 +276,7 @@ def check_groups_configuration(config: Dict[str, Any]) -> List[str]:
"main": "groups.talk_allowed中存在默认示例值'123'，请修改为真实的群号",
"details": [
f" 当前值: {groups['talk_allowed']}",
f" '123'为示例值，需要替换为真实群号"
" '123'为示例值，需要替换为真实群号"
]
})
@@ -371,7 +375,8 @@ def check_memory_config(config: Dict[str, Any]) -> List[str]:
if "memory_compress_rate" in memory and (memory["memory_compress_rate"] <= 0 or memory["memory_compress_rate"] > 1):
errors.append(f"memory.memory_compress_rate值无效: {memory['memory_compress_rate']}, 应在0-1之间")
if "memory_forget_percentage" in memory and (memory["memory_forget_percentage"] <= 0 or memory["memory_forget_percentage"] > 1):
if ("memory_forget_percentage" in memory
and (memory["memory_forget_percentage"] <= 0 or memory["memory_forget_percentage"] > 1)):
errors.append(f"memory.memory_forget_percentage值无效: {memory['memory_forget_percentage']}, 应在0-1之间")
return errors
@@ -393,7 +398,10 @@ def check_personality_config(config: Dict[str, Any]) -> List[str]:
else:
# 检查数组长度
if len(personality["prompt_personality"]) < 1:
errors.append(f"personality.prompt_personality数组长度不足，当前长度: {len(personality['prompt_personality'])}, 需要至少1项")
errors.append(
f"personality.prompt_personality至少需要1项，"
f"当前长度: {len(personality['prompt_personality'])}"
)
else:
# 模板默认值
template_values = [
@@ -452,10 +460,13 @@ def check_bot_config(config: Dict[str, Any]) -> List[str]:
def format_results(all_errors):
"""格式化检查结果"""
sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_results = all_errors
sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_results = all_errors # noqa: E501, F821
bot_errors, bot_infos = bot_results
if not any([sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_errors]):
if not any([
sections_errors, prob_sum_errors,
prob_range_errors, model_errors, api_errors, groups_errors,
kr_errors, willing_errors, memory_errors, personality_errors, bot_errors]):
result = "✅ 配置文件检查通过，未发现问题。"
# 添加机器人信息
@@ -574,7 +585,10 @@ def main():
bot_results = check_bot_config(config)
# 格式化并打印结果
all_errors = (sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_results)
all_errors = (
sections_errors, prob_sum_errors,
prob_range_errors, model_errors, api_errors, groups_errors,
kr_errors, willing_errors, memory_errors, personality_errors, bot_results)
result = format_results(all_errors)
print("📋 机器人配置检查结果:")
print(result)
@@ -586,7 +600,9 @@ def main():
bot_errors, _ = bot_results
# 计算普通错误列表的长度
for errors in [sections_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, bot_errors]:
for errors in [
sections_errors, model_errors, api_errors,
groups_errors, kr_errors, willing_errors, memory_errors, bot_errors]:
total_errors += len(errors)
# 计算元组列表的长度（概率相关错误）