mirror of https://github.com/Mai-with-u/MaiBot.git
feat(database): 支持 MySQL 数据库
- 新增 MySQL 数据库支持，配置文件中增加数据库类型、主机、端口、用户名、密码等设置项 - 修改数据库连接逻辑，支持 SQLite 和 MySQL两种数据库类型 - 更新数据库模型，使用 CharField 替代 TextField，限制字段长度 -增加数据库表前缀配置，方便多项目共用数据库pull/1163/head^2
cuckoo711
parent
3d98b56c15
commit
12e738427e
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@ -1,9 +1,11 @@
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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 peewee import MySQLDatabase, SqliteDatabase
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from pymongo.database import Database
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from rich.traceback import install
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from src.config.config import global_config
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install(extra_lines=3)
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_client = None
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@ -57,26 +59,39 @@ class DBWrapper:
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return get_db()[key] # type: ignore
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def create_peewee_database():
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data_base_config = global_config.data_base
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if data_base_config.db_type == "mysql":
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return MySQLDatabase(
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data_base_config.database_name,
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user=data_base_config.username,
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password=data_base_config.password,
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host=data_base_config.host,
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port=int(data_base_config.port),
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charset='utf8mb4'
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)
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elif data_base_config.db_type == "sqlite":
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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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os.makedirs(_DB_DIR, exist_ok=True)
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return SqliteDatabase(
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_DB_FILE,
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pragmas={
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"journal_mode": "wal", # WAL模式提高并发性能
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"cache_size": -64 * 1000, # 64MB缓存
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"foreign_keys": 1,
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"ignore_check_constraints": 0,
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"synchronous": 0, # 异步写入提高性能
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"busy_timeout": 1000, # 1秒超时而不是3秒
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}, )
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else:
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raise ValueError(f"Unsupported PEEWEE_DB_TYPE: {data_base_config.db_type}")
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# 全局数据库访问点
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memory_db: Database = DBWrapper() # type: ignore
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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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memory_db: Database | DBWrapper = DBWrapper()
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# 全局 Peewee SQLite 数据库访问点
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db = SqliteDatabase(
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_DB_FILE,
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pragmas={
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"journal_mode": "wal", # WAL模式提高并发性能
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"cache_size": -64 * 1000, # 64MB缓存
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"foreign_keys": 1,
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"ignore_check_constraints": 0,
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"synchronous": 0, # 异步写入提高性能
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"busy_timeout": 1000, # 1秒超时而不是3秒
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},
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)
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db = create_peewee_database()
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@ -1,9 +1,11 @@
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from peewee import Model, DoubleField, IntegerField, BooleanField, TextField, FloatField, DateTimeField
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from peewee import CharField, 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 src.common.logger import get_logger
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table_prefix = "" # 数据库表前缀
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logger = get_logger("database_model")
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logger.info(f"正在加载数据库模型...数据库表前缀为: {table_prefix}")
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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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@ -34,7 +36,7 @@ class ChatStreams(BaseModel):
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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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stream_id = CharField(max_length=64, unique=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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@ -70,7 +72,7 @@ class ChatStreams(BaseModel):
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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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table_name = table_prefix + "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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@ -78,9 +80,9 @@ class LLMUsage(BaseModel):
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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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model_name = CharField(max_length=64, index=True) # 添加索引
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user_id = CharField(max_length=64, index=True) # 添加索引
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request_type = CharField(max_length=64, 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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@ -92,15 +94,15 @@ class LLMUsage(BaseModel):
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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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table_name = table_prefix + "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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full_path = CharField(max_length=512, unique=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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emoji_hash = CharField(max_length=64, 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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@ -114,7 +116,7 @@ class Emoji(BaseModel):
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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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table_name = table_prefix + "emoji"
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class Messages(BaseModel):
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@ -122,10 +124,10 @@ class Messages(BaseModel):
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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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message_id = CharField(max_length=128, 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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chat_id = CharField(max_length=128, index=True) # 对应的 ChatStreams stream_id
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reply_to = TextField(null=True)
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@ -165,7 +167,7 @@ class Messages(BaseModel):
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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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table_name = table_prefix + "messages"
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class ActionRecords(BaseModel):
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@ -183,13 +185,13 @@ class ActionRecords(BaseModel):
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action_build_into_prompt = BooleanField(default=False)
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action_prompt_display = TextField()
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chat_id = TextField(index=True) # 对应的 ChatStreams stream_id
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chat_id = CharField(max_length=128, index=True) # 对应的 ChatStreams stream_id
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chat_info_stream_id = TextField()
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chat_info_platform = TextField()
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class Meta:
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# database = db # 继承自 BaseModel
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table_name = "action_records"
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table_name = table_prefix + "action_records"
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class Images(BaseModel):
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@ -198,9 +200,9 @@ class Images(BaseModel):
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"""
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image_id = TextField(default="") # 图片唯一ID
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emoji_hash = TextField(index=True) # 图像的哈希值
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emoji_hash = CharField(max_length=64, 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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path = CharField(max_length=512, unique=True) # 图像文件的路径
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# base64 = TextField() # 图片的base64编码
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count = IntegerField(default=1) # 图片被引用的次数
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timestamp = FloatField() # 时间戳
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@ -208,7 +210,7 @@ class Images(BaseModel):
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vlm_processed = BooleanField(default=False) # 是否已经过VLM处理
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class Meta:
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table_name = "images"
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table_name = table_prefix + "images"
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class ImageDescriptions(BaseModel):
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@ -217,13 +219,13 @@ class ImageDescriptions(BaseModel):
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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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image_description_hash = CharField(max_length=64, 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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table_name = table_prefix + "image_descriptions"
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class OnlineTime(BaseModel):
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@ -232,14 +234,14 @@ class OnlineTime(BaseModel):
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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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timestamp = CharField(max_length=64, 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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table_name = table_prefix + "online_time"
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class PersonInfo(BaseModel):
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@ -247,11 +249,11 @@ class PersonInfo(BaseModel):
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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_id = CharField(max_length=64, unique=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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user_id = CharField(max_length=64, index=True) # 用户ID
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nickname = TextField() # 用户昵称
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impression = TextField(null=True) # 个人印象
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short_impression = TextField(null=True) # 个人印象的简短描述
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@ -266,11 +268,11 @@ class PersonInfo(BaseModel):
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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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table_name = table_prefix + "person_info"
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class Memory(BaseModel):
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memory_id = TextField(index=True)
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memory_id = CharField(max_length=128, index=True)
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chat_id = TextField(null=True)
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memory_text = TextField(null=True)
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keywords = TextField(null=True)
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@ -278,7 +280,7 @@ class Memory(BaseModel):
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last_view_time = FloatField(null=True)
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class Meta:
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table_name = "memory"
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table_name = table_prefix + "memory"
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class Expression(BaseModel):
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@ -290,16 +292,16 @@ class Expression(BaseModel):
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style = TextField()
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count = FloatField()
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last_active_time = FloatField()
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chat_id = TextField(index=True)
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chat_id = CharField(max_length=128, index=True)
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type = TextField()
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create_date = FloatField(null=True) # 创建日期，允许为空以兼容老数据
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class Meta:
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table_name = "expression"
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table_name = table_prefix + "expression"
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class ThinkingLog(BaseModel):
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chat_id = TextField(index=True)
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chat_id = CharField(max_length=128, index=True)
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trigger_text = TextField(null=True)
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response_text = TextField(null=True)
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@ -319,7 +321,7 @@ class ThinkingLog(BaseModel):
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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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table_name = table_prefix + "thinking_logs"
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class GraphNodes(BaseModel):
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@ -327,14 +329,14 @@ class GraphNodes(BaseModel):
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用于存储记忆图节点的模型
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"""
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concept = TextField(unique=True, index=True) # 节点概念
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concept = CharField(max_length=128, unique=True) # 节点概念
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memory_items = TextField() # JSON格式存储的记忆列表
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hash = TextField() # 节点哈希值
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created_time = FloatField() # 创建时间戳
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last_modified = FloatField() # 最后修改时间戳
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class Meta:
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table_name = "graph_nodes"
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table_name = table_prefix + "graph_nodes"
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class GraphEdges(BaseModel):
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@ -342,15 +344,15 @@ class GraphEdges(BaseModel):
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用于存储记忆图边的模型
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"""
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source = TextField(index=True) # 源节点
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target = TextField(index=True) # 目标节点
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source = CharField(max_length=128, index=True) # 源节点
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target = CharField(max_length=128, index=True) # 目标节点
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strength = IntegerField() # 连接强度
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hash = TextField() # 边哈希值
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created_time = FloatField() # 创建时间戳
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last_modified = FloatField() # 最后修改时间戳
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class Meta:
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table_name = "graph_edges"
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table_name = table_prefix + "graph_edges"
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def create_tables():
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@ -400,7 +402,7 @@ def initialize_database():
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GraphEdges,
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ActionRecords, # 添加 ActionRecords 到初始化列表
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]
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del_extra = False # 是否删除多余字段
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try:
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with db: # 管理 table_exists 检查的连接
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for model in models:
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@ -452,6 +454,8 @@ def initialize_database():
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logger.error(f"添加字段 '{field_name}' 失败: {e}")
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# 检查并删除多余字段（新增逻辑）
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if not del_extra:
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continue
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extra_fields = existing_columns - model_fields
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if extra_fields:
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logger.warning(f"表 '{table_name}' 存在多余字段: {extra_fields}")
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@ -14,6 +14,7 @@ from src.common.logger import get_logger
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from src.config.config_base import ConfigBase
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from src.config.official_configs import (
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BotConfig,
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DataBaseConfig,
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PersonalityConfig,
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ExpressionConfig,
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ChatConfig,
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@ -348,6 +349,7 @@ class Config(ConfigBase):
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debug: DebugConfig
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custom_prompt: CustomPromptConfig
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voice: VoiceConfig
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data_base: DataBaseConfig
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@dataclass
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@ -598,3 +598,24 @@ class LPMMKnowledgeConfig(ConfigBase):
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embedding_dimension: int = 1024
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"""嵌入向量维度，应该与模型的输出维度一致"""
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class DataBaseConfig(ConfigBase):
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"""数据库配置类"""
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db_type: Literal["sqlite", "mysql"] = "sqlite"
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"""数据库类型，支持sqlite、mysql"""
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host: str = "127.0.0.1"
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"""数据库主机地址"""
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port: int = 3306
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"""数据库端口号"""
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username: str = ""
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"""数据库用户名"""
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password: str = ""
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"""数据库密码"""
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database_name: str = "MaiBot"
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"""数据库名称"""
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@ -1,5 +1,5 @@
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[inner]
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||||
version = "6.0.0"
|
||||
version = "6.1.0"
|
||||
|
||||
#----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
|
||||
#如果你想要修改配置文件，请在修改后将version的值进行变更
|
||||
|
|
@ -232,3 +232,12 @@ enable = true
|
|||
|
||||
[experimental] #实验性功能
|
||||
enable_friend_chat = false # 是否启用好友聊天
|
||||
|
||||
[data_base] #数据库配置
|
||||
# 数据库类型，可选：sqlite, mysql
|
||||
db_type = "sqlite" # 数据库类型
|
||||
host = "" # 数据库主机地址,如果是sqlite则不需要填写
|
||||
port = 3306 # 数据库端口,如果是sqlite则不需要填写
|
||||
user = "" # 数据库用户名,如果是sqlite则不需要填写
|
||||
password = "" # 数据库密码,如果是sqlite则不需要填写
|
||||
database = "MaiBot" # 数据库名称,如果是sqlite则不需要填写
|
||||
Loading…
Reference in New Issue