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AstrBot/astrbot/core/db/po.py
Soulter 241f1c26d3 feat: context compress (#4322)
* feat: context compressor

Co-authored-by: kawayiYokami <289104862@qq.com>

* Add comprehensive tests for ContextManager and ContextTruncator

- Implemented a full test suite for ContextManager covering initialization, message processing, token-based compression, and error handling.
- Added tests for ContextTruncator focusing on message fixing, truncation by turns, dropping oldest turns, and halving.
- Ensured that both test suites validate edge cases and maintain expected behavior with various message types, including system and tool messages.

* feat: add MockProvider for LLM compression tests

* chore: remove lock

* ruff fix

* fix

* perf

* feat: enhance context compression with token tracking and logging

* feat: update logging for context compression trigger

* feat: implement context compression logic with dynamic threshold and token tracking

* fix: reorder import statements for consistency

* feat: add token_usage tracking to conversations and update related processing logic

---------

Co-authored-by: kawayiYokami <289104862@qq.com>
2026-01-05 17:26:10 +08:00

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import uuid
from dataclasses import dataclass, field
from datetime import datetime, timezone
from typing import TypedDict
from sqlmodel import JSON, Field, SQLModel, Text, UniqueConstraint
class PlatformStat(SQLModel, table=True):
"""This class represents the statistics of bot usage across different platforms.
Note: In astrbot v4, we moved `platform` table to here.
"""
__tablename__: str = "platform_stats"
id: int = Field(primary_key=True, sa_column_kwargs={"autoincrement": True})
timestamp: datetime = Field(nullable=False)
platform_id: str = Field(nullable=False)
platform_type: str = Field(nullable=False) # such as "aiocqhttp", "slack", etc.
count: int = Field(default=0, nullable=False)
__table_args__ = (
UniqueConstraint(
"timestamp",
"platform_id",
"platform_type",
name="uix_platform_stats",
),
)
class ConversationV2(SQLModel, table=True):
__tablename__: str = "conversations"
inner_conversation_id: int | None = Field(
default=None,
primary_key=True,
sa_column_kwargs={"autoincrement": True},
)
conversation_id: str = Field(
max_length=36,
nullable=False,
unique=True,
default_factory=lambda: str(uuid.uuid4()),
)
platform_id: str = Field(nullable=False)
user_id: str = Field(nullable=False)
content: list | None = Field(default=None, sa_type=JSON)
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
)
title: str | None = Field(default=None, max_length=255)
persona_id: str | None = Field(default=None)
token_usage: int = Field(default=0, nullable=False)
"""content is a list of OpenAI-formated messages in list[dict] format.
token_usage is the total token value of the messages.
when 0, will use estimated token counter.
"""
__table_args__ = (
UniqueConstraint(
"conversation_id",
name="uix_conversation_id",
),
)
class Persona(SQLModel, table=True):
"""Persona is a set of instructions for LLMs to follow.
It can be used to customize the behavior of LLMs.
"""
__tablename__: str = "personas"
id: int | None = Field(
primary_key=True,
sa_column_kwargs={"autoincrement": True},
default=None,
)
persona_id: str = Field(max_length=255, nullable=False)
system_prompt: str = Field(sa_type=Text, nullable=False)
begin_dialogs: list | None = Field(default=None, sa_type=JSON)
"""a list of strings, each representing a dialog to start with"""
tools: list | None = Field(default=None, sa_type=JSON)
"""None means use ALL tools for default, empty list means no tools, otherwise a list of tool names."""
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
)
__table_args__ = (
UniqueConstraint(
"persona_id",
name="uix_persona_id",
),
)
class Preference(SQLModel, table=True):
"""This class represents preferences for bots."""
__tablename__: str = "preferences"
id: int | None = Field(
default=None,
primary_key=True,
sa_column_kwargs={"autoincrement": True},
)
scope: str = Field(nullable=False)
"""Scope of the preference, such as 'global', 'umo', 'plugin'."""
scope_id: str = Field(nullable=False)
"""ID of the scope, such as 'global', 'umo', 'plugin_name'."""
key: str = Field(nullable=False)
value: dict = Field(sa_type=JSON, nullable=False)
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
)
__table_args__ = (
UniqueConstraint(
"scope",
"scope_id",
"key",
name="uix_preference_scope_scope_id_key",
),
)
class PlatformMessageHistory(SQLModel, table=True):
"""This class represents the message history for a specific platform.
It is used to store messages that are not LLM-generated, such as user messages
or platform-specific messages.
"""
__tablename__: str = "platform_message_history"
id: int | None = Field(
primary_key=True,
sa_column_kwargs={"autoincrement": True},
default=None,
)
platform_id: str = Field(nullable=False)
user_id: str = Field(nullable=False) # An id of group, user in platform
sender_id: str | None = Field(default=None) # ID of the sender in the platform
sender_name: str | None = Field(
default=None,
) # Name of the sender in the platform
content: dict = Field(sa_type=JSON, nullable=False) # a message chain list
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
)
class PlatformSession(SQLModel, table=True):
"""Platform session table for managing user sessions across different platforms.
A session represents a chat window for a specific user on a specific platform.
Each session can have multiple conversations (对话) associated with it.
"""
__tablename__: str = "platform_sessions"
inner_id: int | None = Field(
primary_key=True,
sa_column_kwargs={"autoincrement": True},
default=None,
)
session_id: str = Field(
max_length=100,
nullable=False,
unique=True,
default_factory=lambda: str(uuid.uuid4()),
)
platform_id: str = Field(default="webchat", nullable=False)
"""Platform identifier (e.g., 'webchat', 'qq', 'discord')"""
creator: str = Field(nullable=False)
"""Username of the session creator"""
display_name: str | None = Field(default=None, max_length=255)
"""Display name for the session"""
is_group: int = Field(default=0, nullable=False)
"""0 for private chat, 1 for group chat (not implemented yet)"""
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
)
__table_args__ = (
UniqueConstraint(
"session_id",
name="uix_platform_session_id",
),
)
class Attachment(SQLModel, table=True):
"""This class represents attachments for messages in AstrBot.
Attachments can be images, files, or other media types.
"""
__tablename__: str = "attachments"
inner_attachment_id: int | None = Field(
primary_key=True,
sa_column_kwargs={"autoincrement": True},
default=None,
)
attachment_id: str = Field(
max_length=36,
nullable=False,
unique=True,
default_factory=lambda: str(uuid.uuid4()),
)
path: str = Field(nullable=False) # Path to the file on disk
type: str = Field(nullable=False) # Type of the file (e.g., 'image', 'file')
mime_type: str = Field(nullable=False) # MIME type of the file
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
)
__table_args__ = (
UniqueConstraint(
"attachment_id",
name="uix_attachment_id",
),
)
class CommandConfig(SQLModel, table=True):
"""Per-command configuration overrides for dashboard management."""
__tablename__ = "command_configs" # type: ignore
handler_full_name: str = Field(
primary_key=True,
max_length=512,
)
plugin_name: str = Field(nullable=False, max_length=255)
module_path: str = Field(nullable=False, max_length=255)
original_command: str = Field(nullable=False, max_length=255)
resolved_command: str | None = Field(default=None, max_length=255)
enabled: bool = Field(default=True, nullable=False)
keep_original_alias: bool = Field(default=False, nullable=False)
conflict_key: str | None = Field(default=None, max_length=255)
resolution_strategy: str | None = Field(default=None, max_length=64)
note: str | None = Field(default=None, sa_type=Text)
extra_data: dict | None = Field(default=None, sa_type=JSON)
auto_managed: bool = Field(default=False, nullable=False)
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
)
class CommandConflict(SQLModel, table=True):
"""Conflict tracking for duplicated command names."""
__tablename__ = "command_conflicts" # type: ignore
id: int | None = Field(
default=None, primary_key=True, sa_column_kwargs={"autoincrement": True}
)
conflict_key: str = Field(nullable=False, max_length=255)
handler_full_name: str = Field(nullable=False, max_length=512)
plugin_name: str = Field(nullable=False, max_length=255)
status: str = Field(default="pending", max_length=32)
resolution: str | None = Field(default=None, max_length=64)
resolved_command: str | None = Field(default=None, max_length=255)
note: str | None = Field(default=None, sa_type=Text)
extra_data: dict | None = Field(default=None, sa_type=JSON)
auto_generated: bool = Field(default=False, nullable=False)
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc),
sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
)
__table_args__ = (
UniqueConstraint(
"conflict_key",
"handler_full_name",
name="uix_conflict_handler",
),
)
@dataclass
class Conversation:
"""LLM 对话类
对于 WebChathistory 存储了包括指令、回复、图片等在内的所有消息。
对于其他平台的聊天,不存储非 LLM 的回复(因为考虑到已经存储在各自的平台上)。
在 v4.0.0 版本及之后WebChat 的历史记录被迁移至 `PlatformMessageHistory` 表中,
"""
platform_id: str
user_id: str
cid: str
"""对话 ID, 是 uuid 格式的字符串"""
history: str = ""
"""字符串格式的对话列表。"""
title: str | None = ""
persona_id: str | None = ""
created_at: int = 0
updated_at: int = 0
token_usage: int = 0
"""对话的总 token 数量。AstrBot 会保留最近一次 LLM 请求返回的总 token 数方便统计。token_usage 可能为 0表示未知。"""
class Personality(TypedDict):
"""LLM 人格类。
在 v4.0.0 版本及之后,推荐使用上面的 Persona 类。并且, mood_imitation_dialogs 字段已被废弃。
"""
prompt: str
name: str
begin_dialogs: list[str]
mood_imitation_dialogs: list[str]
"""情感模拟对话预设。在 v4.0.0 版本及之后,已被废弃。"""
tools: list[str] | None
"""工具列表。None 表示使用所有工具,空列表表示不使用任何工具"""
# cache
_begin_dialogs_processed: list[dict]
_mood_imitation_dialogs_processed: str
# ====
# Deprecated, and will be removed in future versions.
# ====
@dataclass
class Platform:
"""平台使用统计数据"""
name: str
count: int
timestamp: int
@dataclass
class Stats:
platform: list[Platform] = field(default_factory=list)