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chore: import upstream snapshot with attribution
2026-07-13 13:00:43 +08:00

84 lines
2.0 KiB
Python

"""Small data models for DeepTutor's optional multi-user layer."""
from __future__ import annotations
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Literal
Role = Literal["admin", "user"]
ScopeKind = Literal["admin", "user"]
@dataclass(frozen=True, slots=True)
class UserRecord:
id: str
username: str
role: Role = "user"
created_at: str = ""
disabled: bool = False
# Avatar marker: "" (deterministic fallback), "icon:<name>:<color>" for a
# picked icon, or "img:<version>" when the user uploaded an image (the
# version is bumped on every upload so clients can cache-bust).
avatar: str = ""
def public_dict(self) -> dict[str, Any]:
return {
"id": self.id,
"username": self.username,
"role": self.role,
"created_at": self.created_at,
"disabled": self.disabled,
"avatar": self.avatar,
}
@dataclass(frozen=True, slots=True)
class UserScope:
kind: ScopeKind
user_id: str
root: Path
@property
def cache_key(self) -> str:
return f"{self.kind}:{self.user_id}:{self.root.resolve()}"
@dataclass(frozen=True, slots=True)
class CurrentUser:
id: str
username: str
role: Role
scope: UserScope
@property
def is_admin(self) -> bool:
return self.role == "admin"
def public_dict(self) -> dict[str, Any]:
return {
"id": self.id,
"username": self.username,
"role": self.role,
"is_admin": self.is_admin,
}
@dataclass(frozen=True, slots=True)
class KnowledgeResource:
id: str
name: str
base_dir: Path
source: Literal["admin", "user"]
assigned: bool = False
read_only: bool = False
metadata: dict[str, Any] = field(default_factory=dict)
@property
def physical_name(self) -> str:
return self.name
LOCAL_ADMIN_ID = "local-admin"
LOCAL_ADMIN_USERNAME = "local"