816 lines
33 KiB
Python
816 lines
33 KiB
Python
import inspect
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from datetime import datetime
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from enum import Enum
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from functools import wraps
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from pprint import pformat
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from typing import TYPE_CHECKING, List, Literal, Optional, Tuple, Union
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from sqlalchemy import Sequence, String, and_, delete, func, or_, select
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from sqlalchemy.exc import DBAPIError, IntegrityError, TimeoutError
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy.orm import Mapped, Session, mapped_column
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from sqlalchemy.orm.exc import StaleDataError
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from sqlalchemy.orm.interfaces import ORMOption
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from letta.log import get_logger
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from letta.orm.base import Base, CommonSqlalchemyMetaMixins
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from letta.orm.errors import DatabaseTimeoutError, ForeignKeyConstraintViolationError, NoResultFound, UniqueConstraintViolationError
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from letta.settings import DatabaseChoice
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if TYPE_CHECKING:
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from pydantic import BaseModel
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logger = get_logger(__name__)
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def handle_db_timeout(func):
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"""Decorator to handle SQLAlchemy TimeoutError and wrap it in a custom exception."""
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if not inspect.iscoroutinefunction(func):
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@wraps(func)
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def wrapper(*args, **kwargs):
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try:
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return func(*args, **kwargs)
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except TimeoutError as e:
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logger.error(f"Timeout while executing {func.__name__} with args {args} and kwargs {kwargs}: {e}")
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raise DatabaseTimeoutError(message=f"Timeout occurred in {func.__name__}.", original_exception=e)
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return wrapper
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else:
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@wraps(func)
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async def async_wrapper(*args, **kwargs):
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try:
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return await func(*args, **kwargs)
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except TimeoutError as e:
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logger.error(f"Timeout while executing {func.__name__} with args {args} and kwargs {kwargs}: {e}")
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raise DatabaseTimeoutError(message=f"Timeout occurred in {func.__name__}.", original_exception=e)
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return async_wrapper
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def is_postgresql_session(session: Session) -> bool:
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"""Check if the database session is PostgreSQL instead of SQLite for setting query options."""
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return session.bind.dialect.name == "postgresql"
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class AccessType(str, Enum):
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ORGANIZATION = "organization"
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USER = "user"
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class SqlalchemyBase(CommonSqlalchemyMetaMixins, Base):
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__abstract__ = True
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__order_by_default__ = "created_at"
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id: Mapped[str] = mapped_column(String, primary_key=True)
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@classmethod
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@handle_db_timeout
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async def list_async(
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cls,
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*,
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db_session: "AsyncSession",
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before: Optional[str] = None,
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after: Optional[str] = None,
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start_date: Optional[datetime] = None,
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end_date: Optional[datetime] = None,
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limit: Optional[int] = 50,
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query_text: Optional[str] = None,
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query_embedding: Optional[List[float]] = None,
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ascending: bool = True,
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actor: Optional["User"] = None,
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access: Optional[List[Literal["read", "write", "admin"]]] = ["read"],
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access_type: AccessType = AccessType.ORGANIZATION,
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join_model: Optional[Base] = None,
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join_conditions: Optional[Union[Tuple, List]] = None,
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identifier_keys: Optional[List[str]] = None,
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identity_id: Optional[str] = None,
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query_options: Sequence[ORMOption] | None = None, # ← new
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has_feedback: Optional[bool] = None,
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**kwargs,
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) -> List["SqlalchemyBase"]:
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"""
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Async version of list method above.
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NOTE: Keep in sync.
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List records with before/after pagination, ordering by created_at.
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Can use both before and after to fetch a window of records.
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Args:
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db_session: SQLAlchemy session
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before: ID of item to paginate before (upper bound)
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after: ID of item to paginate after (lower bound)
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start_date: Filter items after this date
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end_date: Filter items before this date
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limit: Maximum number of items to return
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query_text: Text to search for
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query_embedding: Vector to search for similar embeddings
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ascending: Sort direction
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**kwargs: Additional filters to apply
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"""
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if start_date and end_date and start_date > end_date:
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raise ValueError("start_date must be earlier than or equal to end_date")
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logger.debug(f"Listing {cls.__name__} with kwarg filters {kwargs}")
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# Get the reference objects for pagination
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before_obj = None
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after_obj = None
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if before:
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before_obj = await db_session.get(cls, before)
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if not before_obj:
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raise NoResultFound(f"No {cls.__name__} found with id {before}")
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if after:
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after_obj = await db_session.get(cls, after)
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if not after_obj:
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raise NoResultFound(f"No {cls.__name__} found with id {after}")
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# Validate that before comes after the after object if both are provided
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if before_obj and after_obj and before_obj.created_at < after_obj.created_at:
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raise ValueError("'before' reference must be later than 'after' reference")
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query = cls._list_preprocess(
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before_obj=before_obj,
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after_obj=after_obj,
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start_date=start_date,
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end_date=end_date,
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limit=limit,
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query_text=query_text,
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query_embedding=query_embedding,
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ascending=ascending,
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actor=actor,
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access=access,
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access_type=access_type,
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join_model=join_model,
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join_conditions=join_conditions,
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identifier_keys=identifier_keys,
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identity_id=identity_id,
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has_feedback=has_feedback,
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**kwargs,
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)
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if query_options:
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for opt in query_options:
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query = query.options(opt)
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# Execute the query
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results = await db_session.execute(query)
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results = list(results.scalars())
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results = cls._list_postprocess(
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before=before,
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after=after,
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limit=limit,
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results=results,
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)
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return results
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@classmethod
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def _list_preprocess(
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cls,
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*,
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before_obj,
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after_obj,
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start_date: Optional[datetime] = None,
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end_date: Optional[datetime] = None,
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limit: Optional[int] = 50,
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query_text: Optional[str] = None,
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query_embedding: Optional[List[float]] = None,
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ascending: bool = True,
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actor: Optional["User"] = None,
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access: Optional[List[Literal["read", "write", "admin"]]] = ["read"],
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access_type: AccessType = AccessType.ORGANIZATION,
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join_model: Optional[Base] = None,
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join_conditions: Optional[Union[Tuple, List]] = None,
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identifier_keys: Optional[List[str]] = None,
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identity_id: Optional[str] = None,
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check_is_deleted: bool = False,
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has_feedback: Optional[bool] = None,
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**kwargs,
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):
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"""
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Constructs the query for listing records.
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"""
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query = select(cls)
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if join_model and join_conditions:
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query = query.join(join_model, and_(*join_conditions))
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# Apply access predicate if actor is provided
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if actor:
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query = cls.apply_access_predicate(query, actor, access, access_type)
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if identifier_keys and hasattr(cls, "identities"):
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query = query.join(cls.identities).filter(cls.identities.property.mapper.class_.identifier_key.in_(identifier_keys))
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# given the identity_id, we can find within the agents table any agents that have the identity_id in their identity_ids
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if identity_id and hasattr(cls, "identities"):
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query = query.join(cls.identities).filter(cls.identities.property.mapper.class_.id == identity_id)
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# Apply filtering logic from kwargs
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# 1 part: <column> // 2 parts: <table>.<column> OR <column>.<json_key> // 3 parts: <table>.<column>.<json_key>
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# TODO (cliandy): can make this more robust down the line
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for key, value in kwargs.items():
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parts = key.split(".")
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if len(parts) == 1:
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column = getattr(cls, key)
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elif len(parts) == 2:
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if locals().get(parts[0]) or globals().get(parts[0]):
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# It's a joined table column
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joined_table = locals().get(parts[0]) or globals().get(parts[0])
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column = getattr(joined_table, parts[1])
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else:
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# It's a JSON field on the main table
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column = getattr(cls, parts[0])
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column = column.op("->>")(parts[1])
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elif len(parts) == 3:
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table_name, column_name, json_key = parts
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joined_table = locals().get(table_name) or globals().get(table_name)
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column = getattr(joined_table, column_name)
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column = column.op("->>")(json_key)
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else:
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raise ValueError(f"Unhandled column name {key}")
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if isinstance(value, (list, tuple, set)):
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query = query.where(column.in_(value))
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else:
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query = query.where(column == value)
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# Date range filtering
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if start_date:
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query = query.filter(cls.created_at > start_date)
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if end_date:
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query = query.filter(cls.created_at < end_date)
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# Feedback filtering
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if has_feedback is not None and hasattr(cls, "feedback"):
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if has_feedback:
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query = query.filter(cls.feedback.isnot(None))
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else:
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query = query.filter(cls.feedback.is_(None))
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# Handle pagination based on before/after
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if before_obj or after_obj:
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conditions = []
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if before_obj and after_obj:
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# Window-based query - get records between before and after
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conditions.append(
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or_(cls.created_at < before_obj.created_at, and_(cls.created_at == before_obj.created_at, cls.id < before_obj.id))
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)
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conditions.append(
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or_(cls.created_at > after_obj.created_at, and_(cls.created_at == after_obj.created_at, cls.id > after_obj.id))
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)
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else:
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# Pure pagination query
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if before_obj:
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conditions.append(
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or_(
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cls.created_at < before_obj.created_at if ascending else cls.created_at > before_obj.created_at,
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and_(cls.created_at == before_obj.created_at, cls.id < before_obj.id),
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)
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)
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if after_obj:
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conditions.append(
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or_(
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cls.created_at > after_obj.created_at if ascending else cls.created_at < after_obj.created_at,
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and_(cls.created_at == after_obj.created_at, cls.id > after_obj.id),
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)
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)
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if conditions:
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query = query.where(and_(*conditions))
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# Text search
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if query_text:
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if hasattr(cls, "text"):
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query = query.filter(func.lower(cls.text).contains(func.lower(query_text)))
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elif hasattr(cls, "name"):
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# Special case for Agent model - search across name
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query = query.filter(func.lower(cls.name).contains(func.lower(query_text)))
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# Embedding search (for Passages)
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is_ordered = False
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if query_embedding:
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if not hasattr(cls, "embedding"):
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raise ValueError(f"Class {cls.__name__} does not have an embedding column")
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from letta.settings import settings
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if settings.database_engine is DatabaseChoice.POSTGRES:
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# PostgreSQL with pgvector
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query = query.order_by(cls.embedding.cosine_distance(query_embedding).asc())
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else:
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# SQLite with custom vector type
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from letta.orm.sqlite_functions import adapt_array
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query_embedding_binary = adapt_array(query_embedding)
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query = query.order_by(
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func.cosine_distance(cls.embedding, query_embedding_binary).asc(),
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cls.created_at.asc() if ascending else cls.created_at.desc(),
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cls.id.asc(),
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)
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is_ordered = True
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# Handle soft deletes
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if check_is_deleted and hasattr(cls, "is_deleted"):
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query = query.where(cls.is_deleted == False)
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# Apply ordering
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if not is_ordered:
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if ascending:
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query = query.order_by(cls.created_at.asc(), cls.id.asc())
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else:
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query = query.order_by(cls.created_at.desc(), cls.id.desc())
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# Apply limit, adjusting for both bounds if necessary
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if before_obj and after_obj:
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# When both bounds are provided, we need to fetch enough records to satisfy
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# the limit while respecting both bounds. We'll fetch more and then trim.
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query = query.limit(limit * 2)
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else:
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query = query.limit(limit)
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return query
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@classmethod
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def _list_postprocess(
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cls,
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before: str | None,
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after: str | None,
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limit: int | None,
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results: list,
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):
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# If we have both bounds, take the middle portion
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if before and after and len(results) > limit:
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middle = len(results) // 2
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start = max(0, middle - limit // 2)
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end = min(len(results), start + limit)
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results = results[start:end]
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return results
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@classmethod
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@handle_db_timeout
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async def read_async(
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cls,
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db_session: "AsyncSession",
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identifier: Optional[str] = None,
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actor: Optional["User"] = None,
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access: Optional[List[Literal["read", "write", "admin"]]] = ["read"],
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access_type: AccessType = AccessType.ORGANIZATION,
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check_is_deleted: bool = False,
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**kwargs,
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) -> "SqlalchemyBase":
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"""The primary accessor for an ORM record. Async version of read method.
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Args:
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db_session: the database session to use when retrieving the record
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identifier: the identifier of the record to read, can be the id string or the UUID object for backwards compatibility
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actor: if specified, results will be scoped only to records the user is able to access
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access: if actor is specified, records will be filtered to the minimum permission level for the actor
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kwargs: additional arguments to pass to the read, used for more complex objects
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Returns:
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The matching object
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Raises:
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NoResultFound: if the object is not found
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"""
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identifiers = [] if identifier is None else [identifier]
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query, query_conditions = cls._read_multiple_preprocess(identifiers, actor, access, access_type, check_is_deleted, **kwargs)
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if query is None:
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raise NoResultFound(f"{cls.__name__} not found with identifier {identifier}")
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result = await db_session.execute(query)
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item = result.scalar_one_or_none()
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if item is None:
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raise NoResultFound(f"{cls.__name__} not found with {', '.join(query_conditions if query_conditions else ['no conditions'])}")
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return item
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@classmethod
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@handle_db_timeout
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async def read_multiple_async(
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cls,
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db_session: "AsyncSession",
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identifiers: List[str] = [],
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actor: Optional["User"] = None,
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access: Optional[List[Literal["read", "write", "admin"]]] = ["read"],
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access_type: AccessType = AccessType.ORGANIZATION,
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check_is_deleted: bool = False,
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**kwargs,
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) -> List["SqlalchemyBase"]:
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"""
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Async version of read_multiple(...)
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The primary accessor for ORM record(s)
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"""
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query, query_conditions = cls._read_multiple_preprocess(identifiers, actor, access, access_type, check_is_deleted, **kwargs)
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if query is None:
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return []
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results = await db_session.execute(query)
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return cls._read_multiple_postprocess(results.scalars().all(), identifiers, query_conditions)
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@classmethod
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def _read_multiple_preprocess(
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cls,
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identifiers: List[str],
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actor: Optional["User"],
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access: Optional[List[Literal["read", "write", "admin"]]],
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access_type: AccessType,
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check_is_deleted: bool,
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**kwargs,
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):
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logger.debug(f"Reading {cls.__name__} with ID(s): {identifiers} with actor={actor}")
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# Start the query
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query = select(cls)
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# Collect query conditions for better error reporting
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query_conditions = []
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# If an identifier is provided, add it to the query conditions
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if identifiers:
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if len(identifiers) == 1:
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query = query.where(cls.id == identifiers[0])
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else:
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query = query.where(cls.id.in_(identifiers))
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query_conditions.append(f"id='{identifiers}'")
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elif not kwargs:
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logger.debug(f"No identifiers provided for {cls.__name__}, returning empty list")
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return None, query_conditions
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if kwargs:
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query = query.filter_by(**kwargs)
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query_conditions.append(", ".join(f"{key}='{value}'" for key, value in kwargs.items()))
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if actor:
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query = cls.apply_access_predicate(query, actor, access, access_type)
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query_conditions.append(f"access level in {access} for actor='{actor}'")
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if check_is_deleted and hasattr(cls, "is_deleted"):
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query = query.where(cls.is_deleted == False)
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query_conditions.append("is_deleted=False")
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return query, query_conditions
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@classmethod
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def _read_multiple_postprocess(cls, results, identifiers: List[str], query_conditions) -> List["SqlalchemyBase"]:
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if results: # if empty list a.k.a. no results
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if len(identifiers) > 0:
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# find which identifiers were not found
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# only when identifier length is greater than 0 (so it was used in the actual query)
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identifier_set = set(identifiers)
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results_set = set(map(lambda obj: obj.id, results))
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# we log a warning message if any of the queried IDs were not found.
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# TODO: should we error out instead?
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if identifier_set != results_set:
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# Construct a detailed error message based on query conditions
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conditions_str = ", ".join(query_conditions) if query_conditions else "no specific conditions"
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logger.debug(f"{cls.__name__} not found with {conditions_str}. Queried ids: {identifier_set}, Found ids: {results_set}")
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return results
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# Construct a detailed error message based on query conditions
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conditions_str = ", ".join(query_conditions) if query_conditions else "no specific conditions"
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logger.debug(f"{cls.__name__} not found with {conditions_str}")
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return []
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@handle_db_timeout
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async def create_async(
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self,
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db_session: "AsyncSession",
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actor: Optional["User"] = None,
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no_commit: bool = False,
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no_refresh: bool = False,
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) -> "SqlalchemyBase":
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"""Async version of create function"""
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logger.debug(f"Creating {self.__class__.__name__} with ID: {self.id} with actor={actor}")
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if actor:
|
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self._set_created_and_updated_by_fields(actor.id)
|
|
try:
|
|
db_session.add(self)
|
|
if no_commit:
|
|
await db_session.flush() # no commit, just flush to get PK
|
|
else:
|
|
await db_session.commit()
|
|
|
|
if not no_refresh:
|
|
await db_session.refresh(self)
|
|
return self
|
|
except (DBAPIError, IntegrityError) as e:
|
|
self._handle_dbapi_error(e)
|
|
|
|
@classmethod
|
|
@handle_db_timeout
|
|
async def batch_create_async(
|
|
cls,
|
|
items: List["SqlalchemyBase"],
|
|
db_session: "AsyncSession",
|
|
actor: Optional["User"] = None,
|
|
no_commit: bool = False,
|
|
no_refresh: bool = False,
|
|
) -> List["SqlalchemyBase"]:
|
|
"""
|
|
Async version of batch_create method.
|
|
Create multiple records in a single transaction for better performance.
|
|
Args:
|
|
items: List of model instances to create
|
|
db_session: AsyncSession session
|
|
actor: Optional user performing the action
|
|
no_commit: Whether to commit the transaction
|
|
no_refresh: Whether to refresh the created objects
|
|
Returns:
|
|
List of created model instances
|
|
"""
|
|
logger.debug(f"Async batch creating {len(items)} {cls.__name__} items with actor={actor}")
|
|
|
|
if not items:
|
|
return []
|
|
|
|
# Set created/updated by fields if actor is provided
|
|
if actor:
|
|
for item in items:
|
|
item._set_created_and_updated_by_fields(actor.id)
|
|
|
|
try:
|
|
db_session.add_all(items)
|
|
if no_commit:
|
|
await db_session.flush()
|
|
else:
|
|
await db_session.commit()
|
|
|
|
if no_refresh:
|
|
return items
|
|
else:
|
|
# Re-query the objects to get them with relationships loaded
|
|
item_ids = [item.id for item in items]
|
|
query = select(cls).where(cls.id.in_(item_ids))
|
|
if hasattr(cls, "created_at"):
|
|
query = query.order_by(cls.created_at)
|
|
|
|
result = await db_session.execute(query)
|
|
return list(result.scalars())
|
|
except (DBAPIError, IntegrityError) as e:
|
|
cls._handle_dbapi_error(e)
|
|
|
|
@handle_db_timeout
|
|
async def delete_async(self, db_session: "AsyncSession", actor: Optional["User"] = None) -> "SqlalchemyBase":
|
|
"""Soft delete a record asynchronously (mark as deleted)."""
|
|
logger.debug(f"Soft deleting {self.__class__.__name__} with ID: {self.id} with actor={actor} (async)")
|
|
|
|
if actor:
|
|
self._set_created_and_updated_by_fields(actor.id)
|
|
|
|
self.is_deleted = True
|
|
return await self.update_async(db_session)
|
|
|
|
@handle_db_timeout
|
|
async def hard_delete_async(self, db_session: "AsyncSession", actor: Optional["User"] = None) -> None:
|
|
"""Permanently removes the record from the database asynchronously."""
|
|
# Capture ID before deletion attempt to avoid lazy loading in exception handler
|
|
obj_id = self.id
|
|
obj_class = self.__class__.__name__
|
|
logger.debug(f"Hard deleting {obj_class} with ID: {obj_id} with actor={actor} (async)")
|
|
|
|
try:
|
|
await db_session.delete(self)
|
|
await db_session.commit()
|
|
except Exception as e:
|
|
await db_session.rollback()
|
|
logger.exception(f"Failed to hard delete {obj_class} with ID {obj_id}")
|
|
raise ValueError(f"Failed to hard delete {obj_class} with ID {obj_id}: {e}")
|
|
|
|
@classmethod
|
|
@handle_db_timeout
|
|
async def bulk_hard_delete_async(
|
|
cls,
|
|
db_session: "AsyncSession",
|
|
identifiers: List[str],
|
|
actor: Optional["User"],
|
|
access: Optional[List[Literal["read", "write", "admin"]]] = ["write"],
|
|
access_type: AccessType = AccessType.ORGANIZATION,
|
|
) -> None:
|
|
"""Permanently removes the record from the database asynchronously."""
|
|
logger.debug(f"Hard deleting {cls.__name__} with IDs: {identifiers} with actor={actor} (async)")
|
|
|
|
if len(identifiers) == 0:
|
|
logger.debug(f"No identifiers provided for {cls.__name__}, nothing to delete")
|
|
return
|
|
|
|
query = delete(cls)
|
|
query = query.where(cls.id.in_(identifiers))
|
|
query = cls.apply_access_predicate(query, actor, access, access_type)
|
|
try:
|
|
result = await db_session.execute(query)
|
|
await db_session.commit()
|
|
logger.debug(f"Successfully deleted {result.rowcount} {cls.__name__} records")
|
|
except Exception as e:
|
|
await db_session.rollback()
|
|
logger.exception(f"Failed to hard delete {cls.__name__} with identifiers {identifiers}")
|
|
raise ValueError(f"Failed to hard delete {cls.__name__} with identifiers {identifiers}: {e}")
|
|
|
|
@handle_db_timeout
|
|
async def update_async(
|
|
self, db_session: "AsyncSession", actor: Optional["User"] = None, no_commit: bool = False, no_refresh: bool = False
|
|
) -> "SqlalchemyBase":
|
|
"""Async version of update function"""
|
|
logger.debug(f"Updating {self.__class__.__name__} with ID: {self.id} with actor={actor}")
|
|
|
|
if actor:
|
|
self._set_created_and_updated_by_fields(actor.id)
|
|
self.set_updated_at()
|
|
try:
|
|
db_session.add(self)
|
|
if no_commit:
|
|
await db_session.flush()
|
|
else:
|
|
await db_session.commit()
|
|
|
|
if not no_refresh:
|
|
await db_session.refresh(self)
|
|
return self
|
|
except StaleDataError as e:
|
|
# This can occur when using optimistic locking (version_id_col) and:
|
|
# 1. The row doesn't exist (0 rows matched)
|
|
# 2. The version has changed (concurrent update)
|
|
# We convert this to NoResultFound to return a proper 404 error
|
|
raise NoResultFound(f"{self.__class__.__name__} with id '{self.id}' not found or was updated by another transaction") from e
|
|
except (DBAPIError, IntegrityError) as e:
|
|
self._handle_dbapi_error(e)
|
|
|
|
@classmethod
|
|
def _size_preprocess(
|
|
cls,
|
|
*,
|
|
db_session: "Session",
|
|
actor: Optional["User"] = None,
|
|
access: Optional[List[Literal["read", "write", "admin"]]] = ["read"],
|
|
access_type: AccessType = AccessType.ORGANIZATION,
|
|
check_is_deleted: bool = False,
|
|
**kwargs,
|
|
):
|
|
logger.debug(f"Calculating size for {cls.__name__} with filters {kwargs}")
|
|
query = select(func.count(1)).select_from(cls)
|
|
|
|
if actor:
|
|
query = cls.apply_access_predicate(query, actor, access, access_type)
|
|
|
|
# Apply filtering logic based on kwargs
|
|
for key, value in kwargs.items():
|
|
if value:
|
|
column = getattr(cls, key, None)
|
|
if not column:
|
|
raise AttributeError(f"{cls.__name__} has no attribute '{key}'")
|
|
if isinstance(value, (list, tuple, set)): # Check for iterables
|
|
query = query.where(column.in_(value))
|
|
else: # Single value for equality filtering
|
|
query = query.where(column == value)
|
|
|
|
if check_is_deleted and hasattr(cls, "is_deleted"):
|
|
query = query.where(cls.is_deleted == False)
|
|
|
|
return query
|
|
|
|
@classmethod
|
|
@handle_db_timeout
|
|
async def size_async(
|
|
cls,
|
|
*,
|
|
db_session: "AsyncSession",
|
|
actor: Optional["User"] = None,
|
|
access: Optional[List[Literal["read", "write", "admin"]]] = ["read"],
|
|
access_type: AccessType = AccessType.ORGANIZATION,
|
|
check_is_deleted: bool = False,
|
|
**kwargs,
|
|
) -> int:
|
|
"""
|
|
Get the count of rows that match the provided filters.
|
|
Args:
|
|
db_session: SQLAlchemy session
|
|
**kwargs: Filters to apply to the query (e.g., column_name=value)
|
|
Returns:
|
|
int: The count of rows that match the filters
|
|
Raises:
|
|
DBAPIError: If a database error occurs
|
|
"""
|
|
query = cls._size_preprocess(
|
|
db_session=db_session,
|
|
actor=actor,
|
|
access=access,
|
|
access_type=access_type,
|
|
check_is_deleted=check_is_deleted,
|
|
**kwargs,
|
|
)
|
|
|
|
try:
|
|
result = await db_session.execute(query)
|
|
count = result.scalar()
|
|
return count if count else 0
|
|
except DBAPIError as e:
|
|
logger.exception(f"Failed to calculate size for {cls.__name__}")
|
|
raise e
|
|
|
|
@classmethod
|
|
def apply_access_predicate(
|
|
cls,
|
|
query: "Select",
|
|
actor: "User",
|
|
access: List[Literal["read", "write", "admin"]],
|
|
access_type: AccessType = AccessType.ORGANIZATION,
|
|
) -> "Select":
|
|
"""applies a WHERE clause restricting results to the given actor and access level
|
|
Args:
|
|
query: The initial sqlalchemy select statement
|
|
actor: The user acting on the query. **Note**: this is called 'actor' to identify the
|
|
person or system acting. Users can act on users, making naming very sticky otherwise.
|
|
access:
|
|
what mode of access should the query restrict to? This will be used with granular permissions,
|
|
but because of how it will impact every query we want to be explicitly calling access ahead of time.
|
|
Returns:
|
|
the sqlalchemy select statement restricted to the given access.
|
|
"""
|
|
del access # entrypoint for row-level permissions. Defaults to "same org as the actor, all permissions" at the moment
|
|
if access_type == AccessType.ORGANIZATION:
|
|
org_id = getattr(actor, "organization_id", None)
|
|
if not org_id:
|
|
raise ValueError(f"object {actor} has no organization accessor")
|
|
return query.where(cls.organization_id == org_id)
|
|
elif access_type == AccessType.USER:
|
|
user_id = getattr(actor, "id", None)
|
|
if not user_id:
|
|
raise ValueError(f"object {actor} has no user accessor")
|
|
return query.where(cls.user_id == user_id)
|
|
else:
|
|
raise ValueError(f"unknown access_type: {access_type}")
|
|
|
|
@classmethod
|
|
def _handle_dbapi_error(cls, e: DBAPIError):
|
|
"""Handle database errors and raise appropriate custom exceptions."""
|
|
orig = e.orig # Extract the original error from the DBAPIError
|
|
error_code = None
|
|
error_message = str(orig) if orig else str(e)
|
|
logger.info(f"Handling DBAPIError: {error_message}")
|
|
|
|
# Handle SQLite-specific errors
|
|
if "UNIQUE constraint failed" in error_message:
|
|
raise UniqueConstraintViolationError(
|
|
f"A unique constraint was violated for {cls.__name__}. Check your input for duplicates: {e}"
|
|
) from e
|
|
|
|
if "FOREIGN KEY constraint failed" in error_message:
|
|
raise ForeignKeyConstraintViolationError(
|
|
f"A foreign key constraint was violated for {cls.__name__}. Check your input for missing or invalid references: {e}"
|
|
) from e
|
|
|
|
# For psycopg2
|
|
if hasattr(orig, "pgcode"):
|
|
error_code = orig.pgcode
|
|
# For pg8000
|
|
elif hasattr(orig, "args") and len(orig.args) > 0:
|
|
# The first argument contains the error details as a dictionary
|
|
err_dict = orig.args[0]
|
|
if isinstance(err_dict, dict):
|
|
error_code = err_dict.get("C") # 'C' is the error code field
|
|
logger.info(f"Extracted error_code: {error_code}")
|
|
|
|
# Handle unique constraint violations
|
|
if error_code == "23505":
|
|
raise UniqueConstraintViolationError(
|
|
f"A unique constraint was violated for {cls.__name__}. Check your input for duplicates: {e}"
|
|
) from e
|
|
|
|
# Handle foreign key violations
|
|
if error_code == "23503":
|
|
raise ForeignKeyConstraintViolationError(
|
|
f"A foreign key constraint was violated for {cls.__name__}. Check your input for missing or invalid references: {e}"
|
|
) from e
|
|
|
|
# Re-raise for other unhandled DBAPI errors
|
|
raise
|
|
|
|
@property
|
|
def __pydantic_model__(self) -> "BaseModel":
|
|
raise NotImplementedError("Sqlalchemy models must declare a __pydantic_model__ property to be convertable.")
|
|
|
|
def to_pydantic(self) -> "BaseModel":
|
|
"""Converts the SQLAlchemy model to its corresponding Pydantic model."""
|
|
model = self.__pydantic_model__.model_validate(self, from_attributes=True)
|
|
|
|
# Explicitly map metadata_ to metadata in Pydantic model
|
|
if hasattr(self, "metadata_") and hasattr(model, "metadata_"):
|
|
setattr(model, "metadata_", self.metadata_) # Ensures correct assignment
|
|
|
|
return model
|
|
|
|
def pretty_print_columns(self) -> str:
|
|
"""
|
|
Pretty prints all columns of the current SQLAlchemy object along with their values.
|
|
"""
|
|
if not hasattr(self, "__table__") or not hasattr(self.__table__, "columns"):
|
|
raise NotImplementedError("This object does not have a '__table__.columns' attribute.")
|
|
|
|
# Iterate over the columns correctly
|
|
column_data = {column.name: getattr(self, column.name, None) for column in self.__table__.columns}
|
|
|
|
return pformat(column_data, indent=4, sort_dicts=True)
|