Merge branch 'new-storage' into plugin
This commit is contained in:
SengokuCola
@@ -1,5 +1,6 @@
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import os
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from pymongo import MongoClient
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from peewee import SqliteDatabase
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from pymongo.database import Database
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from rich.traceback import install
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@@ -57,4 +58,15 @@ class DBWrapper:
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# 全局数据库访问点
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db: Database = DBWrapper()
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memory_db: Database = DBWrapper()
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# 定义数据库文件路径
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ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
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_DB_DIR = os.path.join(ROOT_PATH, "data")
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_DB_FILE = os.path.join(_DB_DIR, "MaiBot.db")
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# 确保数据库目录存在
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os.makedirs(_DB_DIR, exist_ok=True)
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# 全局 Peewee SQLite 数据库访问点
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db = SqliteDatabase(_DB_FILE)
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358
src/common/database/database_model.py
Normal file
358
src/common/database/database_model.py
Normal file
@@ -0,0 +1,358 @@
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from peewee import Model, DoubleField, IntegerField, BooleanField, TextField, FloatField, DateTimeField
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from .database import db
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import datetime
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from ..logger_manager import get_logger
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logger = get_logger("database_model")
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# 请在此处定义您的数据库实例。
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# 您需要取消注释并配置适合您的数据库的部分。
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# 例如，对于 SQLite:
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# db = SqliteDatabase('MaiBot.db')
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#
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# 对于 PostgreSQL:
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# db = PostgresqlDatabase('your_db_name', user='your_user', password='your_password',
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# host='localhost', port=5432)
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#
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# 对于 MySQL:
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# db = MySQLDatabase('your_db_name', user='your_user', password='your_password',
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# host='localhost', port=3306)
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# 定义一个基础模型是一个好习惯，所有其他模型都应继承自它。
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# 这允许您在一个地方为所有模型指定数据库。
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class BaseModel(Model):
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class Meta:
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# 将下面的 'db' 替换为您实际的数据库实例变量名。
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database = db # 例如: database = my_actual_db_instance
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pass # 在用户定义数据库实例之前，此处为占位符
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class ChatStreams(BaseModel):
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"""
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用于存储流式记录数据的模型，类似于提供的 MongoDB 结构。
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"""
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# stream_id: "a544edeb1a9b73e3e1d77dff36e41264"
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# 假设 stream_id 是唯一的，并为其创建索引以提高查询性能。
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stream_id = TextField(unique=True, index=True)
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# create_time: 1746096761.4490178 (时间戳，精确到小数点后7位)
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# DoubleField 用于存储浮点数，适合此类时间戳。
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create_time = DoubleField()
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# group_info 字段:
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# platform: "qq"
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# group_id: "941657197"
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# group_name: "测试"
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group_platform = TextField()
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group_id = TextField()
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group_name = TextField()
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# last_active_time: 1746623771.4825106 (时间戳，精确到小数点后7位)
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last_active_time = DoubleField()
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# platform: "qq" (顶层平台字段)
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platform = TextField()
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# user_info 字段:
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# platform: "qq"
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# user_id: "1787882683"
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# user_nickname: "墨梓柒(IceSakurary)"
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# user_cardname: ""
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user_platform = TextField()
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user_id = TextField()
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user_nickname = TextField()
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# user_cardname 可能为空字符串或不存在，设置 null=True 更具灵活性。
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user_cardname = TextField(null=True)
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class Meta:
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# 如果 BaseModel.Meta.database 已设置，则此模型将继承该数据库配置。
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# 如果不使用带有数据库实例的 BaseModel，或者想覆盖它，
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# 请取消注释并在下面设置数据库实例：
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# database = db
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table_name = "chat_streams" # 可选：明确指定数据库中的表名
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class LLMUsage(BaseModel):
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"""
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用于存储 API 使用日志数据的模型。
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"""
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model_name = TextField(index=True) # 添加索引
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user_id = TextField(index=True) # 添加索引
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request_type = TextField(index=True) # 添加索引
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endpoint = TextField()
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prompt_tokens = IntegerField()
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completion_tokens = IntegerField()
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total_tokens = IntegerField()
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cost = DoubleField()
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status = TextField()
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timestamp = DateTimeField(index=True) # 更改为 DateTimeField 并添加索引
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class Meta:
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# 如果 BaseModel.Meta.database 已设置，则此模型将继承该数据库配置。
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# database = db
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table_name = "llm_usage"
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class Emoji(BaseModel):
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"""表情包"""
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full_path = TextField(unique=True, index=True) # 文件的完整路径 (包括文件名)
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format = TextField() # 图片格式
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emoji_hash = TextField(index=True) # 表情包的哈希值
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description = TextField() # 表情包的描述
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query_count = IntegerField(default=0) # 查询次数（用于统计表情包被查询描述的次数）
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is_registered = BooleanField(default=False) # 是否已注册
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is_banned = BooleanField(default=False) # 是否被禁止注册
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# emotion: list[str] # 表情包的情感标签 - 存储为文本，应用层处理序列化/反序列化
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emotion = TextField(null=True)
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record_time = FloatField() # 记录时间（被创建的时间）
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register_time = FloatField(null=True) # 注册时间（被注册为可用表情包的时间）
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usage_count = IntegerField(default=0) # 使用次数（被使用的次数）
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last_used_time = FloatField(null=True) # 上次使用时间
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class Meta:
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# database = db # 继承自 BaseModel
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table_name = "emoji"
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class Messages(BaseModel):
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"""
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用于存储消息数据的模型。
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"""
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message_id = TextField(index=True) # 消息 ID (更改自 IntegerField)
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time = DoubleField() # 消息时间戳
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chat_id = TextField(index=True) # 对应的 ChatStreams stream_id
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# 从 chat_info 扁平化而来的字段
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chat_info_stream_id = TextField()
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chat_info_platform = TextField()
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chat_info_user_platform = TextField()
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chat_info_user_id = TextField()
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chat_info_user_nickname = TextField()
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chat_info_user_cardname = TextField(null=True)
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chat_info_group_platform = TextField(null=True) # 群聊信息可能不存在
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chat_info_group_id = TextField(null=True)
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chat_info_group_name = TextField(null=True)
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chat_info_create_time = DoubleField()
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chat_info_last_active_time = DoubleField()
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# 从顶层 user_info 扁平化而来的字段 (消息发送者信息)
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user_platform = TextField()
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user_id = TextField()
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user_nickname = TextField()
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user_cardname = TextField(null=True)
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processed_plain_text = TextField(null=True) # 处理后的纯文本消息
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detailed_plain_text = TextField(null=True) # 详细的纯文本消息
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memorized_times = IntegerField(default=0) # 被记忆的次数
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class Meta:
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# database = db # 继承自 BaseModel
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table_name = "messages"
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class Images(BaseModel):
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"""
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用于存储图像信息的模型。
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"""
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emoji_hash = TextField(index=True) # 图像的哈希值
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description = TextField(null=True) # 图像的描述
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path = TextField(unique=True) # 图像文件的路径
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timestamp = FloatField() # 时间戳
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type = TextField() # 图像类型，例如 "emoji"
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class Meta:
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# database = db # 继承自 BaseModel
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table_name = "images"
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class ImageDescriptions(BaseModel):
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"""
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用于存储图像描述信息的模型。
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"""
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type = TextField() # 类型，例如 "emoji"
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image_description_hash = TextField(index=True) # 图像的哈希值
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description = TextField() # 图像的描述
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timestamp = FloatField() # 时间戳
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class Meta:
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# database = db # 继承自 BaseModel
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table_name = "image_descriptions"
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class OnlineTime(BaseModel):
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"""
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用于存储在线时长记录的模型。
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"""
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# timestamp: "$date": "2025-05-01T18:52:18.191Z" (存储为字符串)
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timestamp = TextField(default=datetime.datetime.now) # 时间戳
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duration = IntegerField() # 时长，单位分钟
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start_timestamp = DateTimeField(default=datetime.datetime.now)
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end_timestamp = DateTimeField(index=True)
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class Meta:
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# database = db # 继承自 BaseModel
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table_name = "online_time"
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class PersonInfo(BaseModel):
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"""
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用于存储个人信息数据的模型。
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"""
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person_id = TextField(unique=True, index=True) # 个人唯一ID
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person_name = TextField(null=True) # 个人名称 (允许为空)
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name_reason = TextField(null=True) # 名称设定的原因
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platform = TextField() # 平台
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user_id = TextField(index=True) # 用户ID
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nickname = TextField() # 用户昵称
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relationship_value = IntegerField(default=0) # 关系值
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know_time = FloatField() # 认识时间 (时间戳)
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msg_interval = IntegerField() # 消息间隔
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# msg_interval_list: 存储为 JSON 字符串的列表
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msg_interval_list = TextField(null=True)
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class Meta:
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# database = db # 继承自 BaseModel
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table_name = "person_info"
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class Knowledges(BaseModel):
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"""
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用于存储知识库条目的模型。
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"""
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content = TextField() # 知识内容的文本
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embedding = TextField() # 知识内容的嵌入向量，存储为 JSON 字符串的浮点数列表
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# 可以添加其他元数据字段，如 source, create_time 等
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class Meta:
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# database = db # 继承自 BaseModel
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table_name = "knowledges"
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class ThinkingLog(BaseModel):
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chat_id = TextField(index=True)
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trigger_text = TextField(null=True)
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response_text = TextField(null=True)
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# Store complex dicts/lists as JSON strings
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trigger_info_json = TextField(null=True)
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response_info_json = TextField(null=True)
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timing_results_json = TextField(null=True)
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chat_history_json = TextField(null=True)
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chat_history_in_thinking_json = TextField(null=True)
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chat_history_after_response_json = TextField(null=True)
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heartflow_data_json = TextField(null=True)
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reasoning_data_json = TextField(null=True)
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# Add a timestamp for the log entry itself
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# Ensure you have: from peewee import DateTimeField
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# And: import datetime
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created_at = DateTimeField(default=datetime.datetime.now)
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class Meta:
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table_name = "thinking_logs"
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class RecalledMessages(BaseModel):
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"""
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用于存储撤回消息记录的模型。
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"""
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message_id = TextField(index=True) # 被撤回的消息 ID
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time = DoubleField() # 撤回操作发生的时间戳
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stream_id = TextField() # 对应的 ChatStreams stream_id
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||||
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class Meta:
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table_name = "recalled_messages"
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def create_tables():
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"""
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创建所有在模型中定义的数据库表。
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"""
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with db:
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db.create_tables(
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[
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ChatStreams,
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LLMUsage,
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Emoji,
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Messages,
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Images,
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ImageDescriptions,
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OnlineTime,
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PersonInfo,
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Knowledges,
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ThinkingLog,
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RecalledMessages, # 添加新模型
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]
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)
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def initialize_database():
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||||
"""
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||||
检查所有定义的表是否存在，如果不存在则创建它们。
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||||
检查所有表的所有字段是否存在，如果缺失则警告用户并退出程序。
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"""
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import sys
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models = [
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ChatStreams,
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LLMUsage,
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Emoji,
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||||
Messages,
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||||
Images,
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||||
ImageDescriptions,
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OnlineTime,
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PersonInfo,
|
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Knowledges,
|
||||
ThinkingLog,
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||||
RecalledMessages, # 添加新模型
|
||||
]
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||||
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||||
needs_creation = False
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||||
try:
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||||
with db: # 管理 table_exists 检查的连接
|
||||
for model in models:
|
||||
table_name = model._meta.table_name
|
||||
if not db.table_exists(model):
|
||||
logger.warning(f"表 '{table_name}' 未找到。")
|
||||
needs_creation = True
|
||||
break # 一个表丢失，无需进一步检查。
|
||||
if not needs_creation:
|
||||
# 检查字段
|
||||
for model in models:
|
||||
table_name = model._meta.table_name
|
||||
cursor = db.execute_sql(f"PRAGMA table_info('{table_name}')")
|
||||
existing_columns = {row[1] for row in cursor.fetchall()}
|
||||
model_fields = model._meta.fields
|
||||
for field_name in model_fields:
|
||||
if field_name not in existing_columns:
|
||||
logger.error(f"表 '{table_name}' 缺失字段 '{field_name}'，请手动迁移数据库结构后重启程序。")
|
||||
sys.exit(1)
|
||||
except Exception as e:
|
||||
logger.exception(f"检查表或字段是否存在时出错: {e}")
|
||||
# 如果检查失败（例如数据库不可用），则退出
|
||||
return
|
||||
|
||||
if needs_creation:
|
||||
logger.info("正在初始化数据库：一个或多个表丢失。正在尝试创建所有定义的表...")
|
||||
try:
|
||||
create_tables() # 此函数有其自己的 'with db:' 上下文管理。
|
||||
logger.info("数据库表创建过程完成。")
|
||||
except Exception as e:
|
||||
logger.exception(f"创建表期间出错: {e}")
|
||||
else:
|
||||
logger.info("所有数据库表及字段均已存在。")
|
||||
|
||||
|
||||
# 模块加载时调用初始化函数
|
||||
initialize_database()
|
||||
@@ -1,11 +1,19 @@
|
||||
from src.common.database import db
|
||||
from src.common.database.database_model import Messages # 更改导入
|
||||
from src.common.logger import get_module_logger
|
||||
import traceback
|
||||
from typing import List, Any, Optional
|
||||
from peewee import Model # 添加 Peewee Model 导入
|
||||
|
||||
logger = get_module_logger(__name__)
|
||||
|
||||
|
||||
def _model_to_dict(model_instance: Model) -> dict[str, Any]:
|
||||
"""
|
||||
将 Peewee 模型实例转换为字典。
|
||||
"""
|
||||
return model_instance.__data__
|
||||
|
||||
|
||||
def find_messages(
|
||||
message_filter: dict[str, Any],
|
||||
sort: Optional[List[tuple[str, int]]] = None,
|
||||
@@ -16,39 +24,84 @@ def find_messages(
|
||||
根据提供的过滤器、排序和限制条件查找消息。
|
||||
|
||||
Args:
|
||||
message_filter: MongoDB 查询过滤器。
|
||||
sort: MongoDB 排序条件列表，例如 [('time', 1)]。仅在 limit 为 0 时生效。
|
||||
message_filter: 查询过滤器字典，键为模型字段名，值为期望值或包含操作符的字典 (例如 {'$gt': value}).
|
||||
sort: 排序条件列表，例如 [('time', 1)] (1 for asc, -1 for desc)。仅在 limit 为 0 时生效。
|
||||
limit: 返回的最大文档数，0表示不限制。
|
||||
limit_mode: 当 limit > 0 时生效。 'earliest' 表示获取最早的记录， 'latest' 表示获取最新的记录（结果仍按时间正序排列）。默认为 'latest'。
|
||||
|
||||
Returns:
|
||||
消息文档列表，如果出错则返回空列表。
|
||||
消息字典列表，如果出错则返回空列表。
|
||||
"""
|
||||
try:
|
||||
query = db.messages.find(message_filter)
|
||||
query = Messages.select()
|
||||
|
||||
# 应用过滤器
|
||||
if message_filter:
|
||||
conditions = []
|
||||
for key, value in message_filter.items():
|
||||
if hasattr(Messages, key):
|
||||
field = getattr(Messages, key)
|
||||
if isinstance(value, dict):
|
||||
# 处理 MongoDB 风格的操作符
|
||||
for op, op_value in value.items():
|
||||
if op == "$gt":
|
||||
conditions.append(field > op_value)
|
||||
elif op == "$lt":
|
||||
conditions.append(field < op_value)
|
||||
elif op == "$gte":
|
||||
conditions.append(field >= op_value)
|
||||
elif op == "$lte":
|
||||
conditions.append(field <= op_value)
|
||||
elif op == "$ne":
|
||||
conditions.append(field != op_value)
|
||||
elif op == "$in":
|
||||
conditions.append(field.in_(op_value))
|
||||
elif op == "$nin":
|
||||
conditions.append(field.not_in(op_value))
|
||||
else:
|
||||
logger.warning(f"过滤器中遇到未知操作符 '{op}' (字段: '{key}')。将跳过此操作符。")
|
||||
else:
|
||||
# 直接相等比较
|
||||
conditions.append(field == value)
|
||||
else:
|
||||
logger.warning(f"过滤器键 '{key}' 在 Messages 模型中未找到。将跳过此条件。")
|
||||
if conditions:
|
||||
query = query.where(*conditions)
|
||||
|
||||
if limit > 0:
|
||||
if limit_mode == "earliest":
|
||||
# 获取时间最早的 limit 条记录，已经是正序
|
||||
query = query.sort([("time", 1)]).limit(limit)
|
||||
results = list(query)
|
||||
query = query.order_by(Messages.time.asc()).limit(limit)
|
||||
peewee_results = list(query)
|
||||
else: # 默认为 'latest'
|
||||
# 获取时间最晚的 limit 条记录
|
||||
query = query.sort([("time", -1)]).limit(limit)
|
||||
latest_results = list(query)
|
||||
query = query.order_by(Messages.time.desc()).limit(limit)
|
||||
latest_results_peewee = list(query)
|
||||
# 将结果按时间正序排列
|
||||
# 假设消息文档中总是有 'time' 字段且可排序
|
||||
results = sorted(latest_results, key=lambda msg: msg.get("time"))
|
||||
peewee_results = sorted(latest_results_peewee, key=lambda msg: msg.time)
|
||||
else:
|
||||
# limit 为 0 时，应用传入的 sort 参数
|
||||
if sort:
|
||||
query = query.sort(sort)
|
||||
results = list(query)
|
||||
peewee_sort_terms = []
|
||||
for field_name, direction in sort:
|
||||
if hasattr(Messages, field_name):
|
||||
field = getattr(Messages, field_name)
|
||||
if direction == 1: # ASC
|
||||
peewee_sort_terms.append(field.asc())
|
||||
elif direction == -1: # DESC
|
||||
peewee_sort_terms.append(field.desc())
|
||||
else:
|
||||
logger.warning(f"字段 '{field_name}' 的排序方向 '{direction}' 无效。将跳过此排序条件。")
|
||||
else:
|
||||
logger.warning(f"排序字段 '{field_name}' 在 Messages 模型中未找到。将跳过此排序条件。")
|
||||
if peewee_sort_terms:
|
||||
query = query.order_by(*peewee_sort_terms)
|
||||
peewee_results = list(query)
|
||||
|
||||
return results
|
||||
return [_model_to_dict(msg) for msg in peewee_results]
|
||||
except Exception as e:
|
||||
log_message = (
|
||||
f"查找消息失败 (filter={message_filter}, sort={sort}, limit={limit}, limit_mode={limit_mode}): {e}\n"
|
||||
f"使用 Peewee 查找消息失败 (filter={message_filter}, sort={sort}, limit={limit}, limit_mode={limit_mode}): {e}\n"
|
||||
+ traceback.format_exc()
|
||||
)
|
||||
logger.error(log_message)
|
||||
@@ -60,18 +113,57 @@ def count_messages(message_filter: dict[str, Any]) -> int:
|
||||
根据提供的过滤器计算消息数量。
|
||||
|
||||
Args:
|
||||
message_filter: MongoDB 查询过滤器。
|
||||
message_filter: 查询过滤器字典，键为模型字段名，值为期望值或包含操作符的字典 (例如 {'$gt': value}).
|
||||
|
||||
Returns:
|
||||
符合条件的消息数量，如果出错则返回 0。
|
||||
"""
|
||||
try:
|
||||
count = db.messages.count_documents(message_filter)
|
||||
query = Messages.select()
|
||||
|
||||
# 应用过滤器
|
||||
if message_filter:
|
||||
conditions = []
|
||||
for key, value in message_filter.items():
|
||||
if hasattr(Messages, key):
|
||||
field = getattr(Messages, key)
|
||||
if isinstance(value, dict):
|
||||
# 处理 MongoDB 风格的操作符
|
||||
for op, op_value in value.items():
|
||||
if op == "$gt":
|
||||
conditions.append(field > op_value)
|
||||
elif op == "$lt":
|
||||
conditions.append(field < op_value)
|
||||
elif op == "$gte":
|
||||
conditions.append(field >= op_value)
|
||||
elif op == "$lte":
|
||||
conditions.append(field <= op_value)
|
||||
elif op == "$ne":
|
||||
conditions.append(field != op_value)
|
||||
elif op == "$in":
|
||||
conditions.append(field.in_(op_value))
|
||||
elif op == "$nin":
|
||||
conditions.append(field.not_in(op_value))
|
||||
else:
|
||||
logger.warning(
|
||||
f"计数时，过滤器中遇到未知操作符 '{op}' (字段: '{key}')。将跳过此操作符。"
|
||||
)
|
||||
else:
|
||||
# 直接相等比较
|
||||
conditions.append(field == value)
|
||||
else:
|
||||
logger.warning(f"计数时，过滤器键 '{key}' 在 Messages 模型中未找到。将跳过此条件。")
|
||||
if conditions:
|
||||
query = query.where(*conditions)
|
||||
|
||||
count = query.count()
|
||||
return count
|
||||
except Exception as e:
|
||||
log_message = f"计数消息失败 (message_filter={message_filter}): {e}\n" + traceback.format_exc()
|
||||
log_message = f"使用 Peewee 计数消息失败 (message_filter={message_filter}): {e}\n{traceback.format_exc()}"
|
||||
logger.error(log_message)
|
||||
return 0
|
||||
|
||||
|
||||
# 你可以在这里添加更多与 messages 集合相关的数据库操作函数，例如 find_one_message, insert_message 等。
|
||||
# 注意：对于 Peewee，插入操作通常是 Messages.create(...) 或 instance.save()。
|
||||
# 查找单个消息可以是 Messages.get_or_none(...) 或 query.first()。
|
||||
|
||||
@@ -35,7 +35,7 @@ class TelemetryHeartBeatTask(AsyncTask):
|
||||
info_dict = {
|
||||
"os_type": "Unknown",
|
||||
"py_version": platform.python_version(),
|
||||
"mmc_version": global_config.MAI_VERSION,
|
||||
"mmc_version": global_config.MMC_VERSION,
|
||||
}
|
||||
|
||||
match platform.system():
|
||||
@@ -133,10 +133,9 @@ class TelemetryHeartBeatTask(AsyncTask):
|
||||
|
||||
async def run(self):
|
||||
# 发送心跳
|
||||
if global_config.remote_enable:
|
||||
if self.client_uuid is None:
|
||||
if not await self._req_uuid():
|
||||
logger.error("获取UUID失败，跳过此次心跳")
|
||||
return
|
||||
if global_config.telemetry.enable:
|
||||
if self.client_uuid is None and not await self._req_uuid():
|
||||
logger.error("获取UUID失败，跳过此次心跳")
|
||||
return
|
||||
|
||||
await self._send_heartbeat()
|
||||
|
||||
Reference in New Issue
Block a user