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Merge branch 'dev' of https://github.com/MoFox-Studio/MoFox_Bot into dev

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This commit is contained in:
Windpicker-owo
2025-11-01 19:35:05 +08:00
parent e0063fb281 724fdd6827
commit a83fe72717
4 changed files with 32 additions and 31 deletions
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3
src/chat/replyer/default_generator.py
View File

@@ -1468,7 +1468,6 @@ class DefaultReplyer:
if now < start_time:
now += timedelta(days=1)
if start_time <= now < end_time:
duration_minutes = (now - start_time).total_seconds() / 60
remaining_minutes = (end_time - now).total_seconds() / 60
schedule_block = (
@@ -1478,8 +1477,6 @@ class DefaultReplyer:
f"预计还有{remaining_minutes:.0f}分钟结束。"
"（此为你的当前状态，仅供参考。除非被直接询问，否则不要在对话中主动提及。）"
)
else:
schedule_block = f"你当前正在进行“{activity}”。(此为你的当前状态，仅供参考。除非被直接询问，否则不要在对话中主动提及。)"
except (ValueError, AttributeError):
schedule_block = f"你当前正在进行“{activity}”。(此为你的当前状态，仅供参考。除非被直接询问，否则不要在对话中主动提及。)"

4
src/llm_models/model_client/openai_client.py
View File

@@ -350,10 +350,10 @@ def _default_normal_response_parser(
api_response.tool_calls = []
for call in message_part.tool_calls:
try:
arguments = orjson.loads(repair_json(call.function.arguments))
arguments = orjson.loads(repair_json(call.function.arguments)) # type: ignore
if not isinstance(arguments, dict):
raise RespParseException(resp, "响应解析失败，工具调用参数无法解析为字典类型")
api_response.tool_calls.append(ToolCall(call.id, call.function.name, arguments))
api_response.tool_calls.append(ToolCall(call.id, call.function.name, arguments)) # type: ignore
except orjson.JSONDecodeError as e:
raise RespParseException(resp, "响应解析失败，无法解析工具调用参数") from e

20
src/main.py
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@@ -218,14 +218,6 @@ class MainSystem:
cleanup_tasks = []
# 停止数据库服务
try:
from src.common.database.core import close_engine as stop_database
cleanup_tasks.append(("数据库服务", stop_database()))
except Exception as e:
logger.error(f"准备停止数据库服务时出错: {e}")
# 停止消息批处理器
try:
from src.chat.message_receive.storage import get_message_storage_batcher, get_message_update_batcher
@@ -329,6 +321,18 @@ class MainSystem:
else:
logger.warning("没有需要清理的任务")
# 停止数据库服务 (在所有其他任务完成后最后停止)
try:
from src.common.database.core import close_engine as stop_database
logger.info("正在停止数据库服务...")
await asyncio.wait_for(stop_database(), timeout=15.0)
logger.info("🛑 数据库服务已停止")
except asyncio.TimeoutError:
logger.error("停止数据库服务超时")
except Exception as e:
logger.error(f"停止数据库服务时出错: {e}")
def _cleanup(self) -> None:
"""同步清理资源（向后兼容）"""
try:

30
template/model_config_template.toml
View File

@@ -1,5 +1,5 @@
[inner]
version = "1.3.6"
version = "1.3.7"
# 配置文件版本号迭代规则同bot_config.toml
@@ -53,8 +53,8 @@ price_out = 8.0 # 输出价格（用于API调用统计，单
#use_anti_truncation = true # [可选] 启用反截断功能。当模型输出不完整时，系统会自动重试。建议只为有需要的模型（如Gemini）开启。
[[models]]
model_identifier = "deepseek-ai/DeepSeek-V3.1-Terminus"
name = "siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"
model_identifier = "deepseek-ai/DeepSeek-V3.2-Exp"
name = "siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"
api_provider = "SiliconFlow"
price_in = 2.0
price_out = 8.0
@@ -122,7 +122,7 @@ price_in = 4.0
price_out = 16.0
[model_task_config.utils] # 在麦麦的一些组件中使用的模型，例如表情包模块，取名模块，关系模块，是麦麦必须的模型
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"] # 使用的模型列表，每个子项对应上面的模型名称(name)
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"] # 使用的模型列表，每个子项对应上面的模型名称(name)
temperature = 0.2 # 模型温度，新V3建议0.1-0.3
max_tokens = 800 # 最大输出token数
#concurrency_count = 2 # 并发请求数量，默认为1（不并发），设置为2或更高启用并发
@@ -133,28 +133,28 @@ temperature = 0.7
max_tokens = 800
[model_task_config.replyer] # 首要回复模型，还用于表达器和表达方式学习
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.2 # 模型温度，新V3建议0.1-0.3
max_tokens = 800
[model_task_config.planner] #决策：负责决定麦麦该做什么的模型
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.3
max_tokens = 800
[model_task_config.emotion] #负责麦麦的情绪变化
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.3
max_tokens = 800
[model_task_config.mood] #负责麦麦的心情变化
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.3
max_tokens = 800
[model_task_config.maizone] # maizone模型
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.7
max_tokens = 800
@@ -181,22 +181,22 @@ temperature = 0.7
max_tokens = 800
[model_task_config.schedule_generator]#日程表生成模型
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.7
max_tokens = 1000
[model_task_config.anti_injection] # 反注入检测专用模型
model_list = ["moonshotai-Kimi-K2-Instruct"] # 使用快速的小模型进行检测
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"] # 使用快速的小模型进行检测
temperature = 0.1 # 低温度确保检测结果稳定
max_tokens = 200 # 检测结果不需要太长的输出
[model_task_config.monthly_plan_generator] # 月层计划生成模型
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.7
max_tokens = 1000
[model_task_config.relationship_tracker] # 用户关系追踪模型
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.7
max_tokens = 1000
@@ -210,12 +210,12 @@ embedding_dimension = 1024
#------------LPMM知识库模型------------
[model_task_config.lpmm_entity_extract] # 实体提取模型
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.2
max_tokens = 800
[model_task_config.lpmm_rdf_build] # RDF构建模型
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.1-Terminus"]
model_list = ["siliconflow-deepseek-ai/DeepSeek-V3.2-Exp"]
temperature = 0.2
max_tokens = 800