初始化

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雅诺狐
2025-08-11 19:34:18 +08:00
committed by Windpicker-owo
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commit 23ee3767ef
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"""SQLAlchemy数据库模型定义
替换Peewee ORM使用SQLAlchemy提供更好的连接池管理和错误恢复能力
"""
from sqlalchemy import Column, String, Float, Integer, Boolean, Text, Index, create_engine, DateTime
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy.pool import QueuePool
import os
import datetime
from src.config.config import global_config
from src.common.logger import get_logger
import threading
from contextlib import contextmanager
logger = get_logger("sqlalchemy_models")
# 创建基类
Base = declarative_base()
# MySQL兼容的字段类型辅助函数
def get_string_field(max_length=255, **kwargs):
"""
根据数据库类型返回合适的字符串字段
MySQL需要指定长度的VARCHAR用于索引SQLite可以使用Text
"""
if global_config.database.database_type == "mysql":
return String(max_length, **kwargs)
else:
return Text(**kwargs)
class SessionProxy:
"""线程安全的Session代理类自动管理session生命周期"""
def __init__(self):
self._local = threading.local()
def _get_current_session(self):
"""获取当前线程的session如果没有则创建新的"""
if not hasattr(self._local, 'session') or self._local.session is None:
_, SessionLocal = initialize_database()
self._local.session = SessionLocal()
return self._local.session
def _close_current_session(self):
"""关闭当前线程的session"""
if hasattr(self._local, 'session') and self._local.session is not None:
try:
self._local.session.close()
except:
pass
finally:
self._local.session = None
def __getattr__(self, name):
"""代理所有session方法"""
session = self._get_current_session()
attr = getattr(session, name)
# 如果是方法,需要特殊处理一些关键方法
if callable(attr):
if name in ['commit', 'rollback']:
def wrapper(*args, **kwargs):
try:
result = attr(*args, **kwargs)
if name == 'commit':
# commit后不要清除session只是刷新状态
pass # 保持session活跃
return result
except Exception as e:
try:
if session and hasattr(session, 'rollback'):
session.rollback()
except:
pass
# 发生错误时重新创建session
self._close_current_session()
raise
return wrapper
elif name == 'close':
def wrapper(*args, **kwargs):
result = attr(*args, **kwargs)
self._close_current_session()
return result
return wrapper
elif name in ['execute', 'query', 'add', 'delete', 'merge']:
def wrapper(*args, **kwargs):
try:
return attr(*args, **kwargs)
except Exception as e:
# 如果是连接相关错误重新创建session再试一次
if "not bound to a Session" in str(e) or "provisioning a new connection" in str(e):
logger.warning(f"Session问题重新创建session: {e}")
self._close_current_session()
new_session = self._get_current_session()
new_attr = getattr(new_session, name)
return new_attr(*args, **kwargs)
raise
return wrapper
return attr
def new_session(self):
"""强制创建新的session关闭当前的创建新的"""
self._close_current_session()
return self._get_current_session()
def ensure_fresh_session(self):
"""确保使用新鲜的session如果当前session有问题则重新创建"""
if hasattr(self._local, 'session') and self._local.session is not None:
try:
# 测试session是否还可用
self._local.session.execute("SELECT 1")
except Exception:
# session有问题重新创建
self._close_current_session()
return self._get_current_session()
# 创建全局session代理实例
_global_session_proxy = SessionProxy()
def get_session():
"""返回线程安全的session代理自动管理生命周期"""
return _global_session_proxy
class ChatStreams(Base):
"""聊天流模型"""
__tablename__ = 'chat_streams'
id = Column(Integer, primary_key=True, autoincrement=True)
stream_id = Column(get_string_field(64), nullable=False, unique=True, index=True)
create_time = Column(Float, nullable=False)
group_platform = Column(Text, nullable=True)
group_id = Column(get_string_field(100), nullable=True, index=True)
group_name = Column(Text, nullable=True)
last_active_time = Column(Float, nullable=False)
platform = Column(Text, nullable=False)
user_platform = Column(Text, nullable=False)
user_id = Column(get_string_field(100), nullable=False, index=True)
user_nickname = Column(Text, nullable=False)
user_cardname = Column(Text, nullable=True)
__table_args__ = (
Index('idx_chatstreams_stream_id', 'stream_id'),
Index('idx_chatstreams_user_id', 'user_id'),
Index('idx_chatstreams_group_id', 'group_id'),
)
class LLMUsage(Base):
"""LLM使用记录模型"""
__tablename__ = 'llm_usage'
id = Column(Integer, primary_key=True, autoincrement=True)
model_name = Column(get_string_field(100), nullable=False, index=True)
user_id = Column(get_string_field(50), nullable=False, index=True)
request_type = Column(get_string_field(50), nullable=False, index=True)
endpoint = Column(Text, nullable=False)
prompt_tokens = Column(Integer, nullable=False)
completion_tokens = Column(Integer, nullable=False)
total_tokens = Column(Integer, nullable=False)
cost = Column(Float, nullable=False)
status = Column(Text, nullable=False)
timestamp = Column(DateTime, nullable=False, index=True, default=datetime.datetime.now)
__table_args__ = (
Index('idx_llmusage_model_name', 'model_name'),
Index('idx_llmusage_user_id', 'user_id'),
Index('idx_llmusage_request_type', 'request_type'),
Index('idx_llmusage_timestamp', 'timestamp'),
)
class Emoji(Base):
"""表情包模型"""
__tablename__ = 'emoji'
id = Column(Integer, primary_key=True, autoincrement=True)
full_path = Column(get_string_field(500), nullable=False, unique=True, index=True)
format = Column(Text, nullable=False)
emoji_hash = Column(get_string_field(64), nullable=False, index=True)
description = Column(Text, nullable=False)
query_count = Column(Integer, nullable=False, default=0)
is_registered = Column(Boolean, nullable=False, default=False)
is_banned = Column(Boolean, nullable=False, default=False)
emotion = Column(Text, nullable=True)
record_time = Column(Float, nullable=False)
register_time = Column(Float, nullable=True)
usage_count = Column(Integer, nullable=False, default=0)
last_used_time = Column(Float, nullable=True)
__table_args__ = (
Index('idx_emoji_full_path', 'full_path'),
Index('idx_emoji_hash', 'emoji_hash'),
)
class Messages(Base):
"""消息模型"""
__tablename__ = 'messages'
id = Column(Integer, primary_key=True, autoincrement=True)
message_id = Column(get_string_field(100), nullable=False, index=True)
time = Column(Float, nullable=False)
chat_id = Column(get_string_field(64), nullable=False, index=True)
reply_to = Column(Text, nullable=True)
interest_value = Column(Float, nullable=True)
is_mentioned = Column(Boolean, nullable=True)
# 从 chat_info 扁平化而来的字段
chat_info_stream_id = Column(Text, nullable=False)
chat_info_platform = Column(Text, nullable=False)
chat_info_user_platform = Column(Text, nullable=False)
chat_info_user_id = Column(Text, nullable=False)
chat_info_user_nickname = Column(Text, nullable=False)
chat_info_user_cardname = Column(Text, nullable=True)
chat_info_group_platform = Column(Text, nullable=True)
chat_info_group_id = Column(Text, nullable=True)
chat_info_group_name = Column(Text, nullable=True)
chat_info_create_time = Column(Float, nullable=False)
chat_info_last_active_time = Column(Float, nullable=False)
# 从顶层 user_info 扁平化而来的字段
user_platform = Column(Text, nullable=True)
user_id = Column(get_string_field(100), nullable=True, index=True)
user_nickname = Column(Text, nullable=True)
user_cardname = Column(Text, nullable=True)
processed_plain_text = Column(Text, nullable=True)
display_message = Column(Text, nullable=True)
memorized_times = Column(Integer, nullable=False, default=0)
priority_mode = Column(Text, nullable=True)
priority_info = Column(Text, nullable=True)
additional_config = Column(Text, nullable=True)
is_emoji = Column(Boolean, nullable=False, default=False)
is_picid = Column(Boolean, nullable=False, default=False)
is_command = Column(Boolean, nullable=False, default=False)
is_notify = Column(Boolean, nullable=False, default=False)
__table_args__ = (
Index('idx_messages_message_id', 'message_id'),
Index('idx_messages_chat_id', 'chat_id'),
Index('idx_messages_time', 'time'),
Index('idx_messages_user_id', 'user_id'),
)
class ActionRecords(Base):
"""动作记录模型"""
__tablename__ = 'action_records'
id = Column(Integer, primary_key=True, autoincrement=True)
action_id = Column(get_string_field(100), nullable=False, index=True)
time = Column(Float, nullable=False)
action_name = Column(Text, nullable=False)
action_data = Column(Text, nullable=False)
action_done = Column(Boolean, nullable=False, default=False)
action_build_into_prompt = Column(Boolean, nullable=False, default=False)
action_prompt_display = Column(Text, nullable=False)
chat_id = Column(get_string_field(64), nullable=False, index=True)
chat_info_stream_id = Column(Text, nullable=False)
chat_info_platform = Column(Text, nullable=False)
__table_args__ = (
Index('idx_actionrecords_action_id', 'action_id'),
Index('idx_actionrecords_chat_id', 'chat_id'),
Index('idx_actionrecords_time', 'time'),
)
class Images(Base):
"""图像信息模型"""
__tablename__ = 'images'
id = Column(Integer, primary_key=True, autoincrement=True)
image_id = Column(Text, nullable=False, default="")
emoji_hash = Column(get_string_field(64), nullable=False, index=True)
description = Column(Text, nullable=True)
path = Column(get_string_field(500), nullable=False, unique=True)
count = Column(Integer, nullable=False, default=1)
timestamp = Column(Float, nullable=False)
type = Column(Text, nullable=False)
vlm_processed = Column(Boolean, nullable=False, default=False)
__table_args__ = (
Index('idx_images_emoji_hash', 'emoji_hash'),
Index('idx_images_path', 'path'),
)
class ImageDescriptions(Base):
"""图像描述信息模型"""
__tablename__ = 'image_descriptions'
id = Column(Integer, primary_key=True, autoincrement=True)
type = Column(Text, nullable=False)
image_description_hash = Column(get_string_field(64), nullable=False, index=True)
description = Column(Text, nullable=False)
timestamp = Column(Float, nullable=False)
__table_args__ = (
Index('idx_imagedesc_hash', 'image_description_hash'),
)
class OnlineTime(Base):
"""在线时长记录模型"""
__tablename__ = 'online_time'
id = Column(Integer, primary_key=True, autoincrement=True)
timestamp = Column(Text, nullable=False, default=str(datetime.datetime.now))
duration = Column(Integer, nullable=False)
start_timestamp = Column(DateTime, nullable=False, default=datetime.datetime.now)
end_timestamp = Column(DateTime, nullable=False, index=True)
__table_args__ = (
Index('idx_onlinetime_end_timestamp', 'end_timestamp'),
)
class PersonInfo(Base):
"""人物信息模型"""
__tablename__ = 'person_info'
id = Column(Integer, primary_key=True, autoincrement=True)
person_id = Column(get_string_field(100), nullable=False, unique=True, index=True)
person_name = Column(Text, nullable=True)
name_reason = Column(Text, nullable=True)
platform = Column(Text, nullable=False)
user_id = Column(get_string_field(50), nullable=False, index=True)
nickname = Column(Text, nullable=True)
impression = Column(Text, nullable=True)
short_impression = Column(Text, nullable=True)
points = Column(Text, nullable=True)
forgotten_points = Column(Text, nullable=True)
info_list = Column(Text, nullable=True)
know_times = Column(Float, nullable=True)
know_since = Column(Float, nullable=True)
last_know = Column(Float, nullable=True)
attitude = Column(Integer, nullable=True, default=50)
__table_args__ = (
Index('idx_personinfo_person_id', 'person_id'),
Index('idx_personinfo_user_id', 'user_id'),
)
class Memory(Base):
"""记忆模型"""
__tablename__ = 'memory'
id = Column(Integer, primary_key=True, autoincrement=True)
memory_id = Column(get_string_field(64), nullable=False, index=True)
chat_id = Column(Text, nullable=True)
memory_text = Column(Text, nullable=True)
keywords = Column(Text, nullable=True)
create_time = Column(Float, nullable=True)
last_view_time = Column(Float, nullable=True)
__table_args__ = (
Index('idx_memory_memory_id', 'memory_id'),
)
class Expression(Base):
"""表达风格模型"""
__tablename__ = 'expression'
id = Column(Integer, primary_key=True, autoincrement=True)
situation = Column(Text, nullable=False)
style = Column(Text, nullable=False)
count = Column(Float, nullable=False)
last_active_time = Column(Float, nullable=False)
chat_id = Column(get_string_field(64), nullable=False, index=True)
type = Column(Text, nullable=False)
create_date = Column(Float, nullable=True)
__table_args__ = (
Index('idx_expression_chat_id', 'chat_id'),
)
class ThinkingLog(Base):
"""思考日志模型"""
__tablename__ = 'thinking_logs'
id = Column(Integer, primary_key=True, autoincrement=True)
chat_id = Column(get_string_field(64), nullable=False, index=True)
trigger_text = Column(Text, nullable=True)
response_text = Column(Text, nullable=True)
trigger_info_json = Column(Text, nullable=True)
response_info_json = Column(Text, nullable=True)
timing_results_json = Column(Text, nullable=True)
chat_history_json = Column(Text, nullable=True)
chat_history_in_thinking_json = Column(Text, nullable=True)
chat_history_after_response_json = Column(Text, nullable=True)
heartflow_data_json = Column(Text, nullable=True)
reasoning_data_json = Column(Text, nullable=True)
created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
__table_args__ = (
Index('idx_thinkinglog_chat_id', 'chat_id'),
)
class GraphNodes(Base):
"""记忆图节点模型"""
__tablename__ = 'graph_nodes'
id = Column(Integer, primary_key=True, autoincrement=True)
concept = Column(get_string_field(255), nullable=False, unique=True, index=True)
memory_items = Column(Text, nullable=False)
hash = Column(Text, nullable=False)
created_time = Column(Float, nullable=False)
last_modified = Column(Float, nullable=False)
__table_args__ = (
Index('idx_graphnodes_concept', 'concept'),
)
class GraphEdges(Base):
"""记忆图边模型"""
__tablename__ = 'graph_edges'
id = Column(Integer, primary_key=True, autoincrement=True)
source = Column(get_string_field(255), nullable=False, index=True)
target = Column(get_string_field(255), nullable=False, index=True)
strength = Column(Integer, nullable=False)
hash = Column(Text, nullable=False)
created_time = Column(Float, nullable=False)
last_modified = Column(Float, nullable=False)
__table_args__ = (
Index('idx_graphedges_source', 'source'),
Index('idx_graphedges_target', 'target'),
)
# 数据库引擎和会话管理
_engine = None
_SessionLocal = None
def get_database_url():
"""获取数据库连接URL"""
config = global_config.database
if config.database_type == "mysql":
# 对用户名和密码进行URL编码处理特殊字符
from urllib.parse import quote_plus
encoded_user = quote_plus(config.mysql_user)
encoded_password = quote_plus(config.mysql_password)
return (
f"mysql+pymysql://{encoded_user}:{encoded_password}"
f"@{config.mysql_host}:{config.mysql_port}/{config.mysql_database}"
f"?charset={config.mysql_charset}"
)
else: # SQLite
# 如果是相对路径,则相对于项目根目录
if not os.path.isabs(config.sqlite_path):
ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
db_path = os.path.join(ROOT_PATH, config.sqlite_path)
else:
db_path = config.sqlite_path
# 确保数据库目录存在
os.makedirs(os.path.dirname(db_path), exist_ok=True)
return f"sqlite:///{db_path}"
def initialize_database():
"""初始化数据库引擎和会话"""
global _engine, _SessionLocal
if _engine is not None:
return _engine, _SessionLocal
database_url = get_database_url()
config = global_config.database
# 配置引擎参数
engine_kwargs = {
'echo': False, # 生产环境关闭SQL日志
'future': True,
}
if config.database_type == "mysql":
# MySQL连接池配置
engine_kwargs.update({
'poolclass': QueuePool,
'pool_size': config.connection_pool_size,
'max_overflow': config.connection_pool_size * 2,
'pool_timeout': config.connection_timeout,
'pool_recycle': 3600, # 1小时回收连接
'pool_pre_ping': True, # 连接前ping检查
'connect_args': {
'autocommit': config.mysql_autocommit,
'charset': config.mysql_charset,
'connect_timeout': config.connection_timeout,
'read_timeout': 30,
'write_timeout': 30,
}
})
else:
# SQLite配置 - 添加连接池设置以避免连接耗尽
engine_kwargs.update({
'poolclass': QueuePool,
'pool_size': 20, # 增加池大小
'max_overflow': 30, # 增加溢出连接数
'pool_timeout': 60, # 增加超时时间
'pool_recycle': 3600, # 1小时回收连接
'pool_pre_ping': True, # 连接前ping检查
'connect_args': {
'check_same_thread': False,
'timeout': 30,
}
})
_engine = create_engine(database_url, **engine_kwargs)
_SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=_engine)
# 创建所有表
Base.metadata.create_all(bind=_engine)
logger.info(f"SQLAlchemy数据库初始化成功: {config.database_type}")
return _engine, _SessionLocal
@contextmanager
def get_db_session():
"""数据库会话上下文管理器 - 推荐使用这个而不是get_session()"""
session = None
try:
_, SessionLocal = initialize_database()
session = SessionLocal()
yield session
session.commit()
except Exception as e:
if session:
session.rollback()
raise
finally:
if session:
session.close()
def get_engine():
"""获取数据库引擎"""
engine, _ = initialize_database()
return engine