repo_description: The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.
repo_topics: ai comfy comfyui python pytorch stable-diffusion
code: from typing import Any
  from datetime import datetime
  from sqlalchemy import MetaData
  from sqlalchemy.orm import DeclarativeBase
  
  NAMING_CONVENTION = {
      "ix": "ix_%(table_name)s_%(column_0_N_name)s",
      "uq": "uq_%(table_name)s_%(column_0_N_name)s",
      "ck": "ck_%(table_name)s_%(constraint_name)s",
      "fk": "fk_%(table_name)s_%(column_0_name)s_%(referred_table_name)s",
      "pk": "pk_%(table_name)s",
  }
  
  class Base(DeclarativeBase):
      metadata = MetaData(naming_convention=NAMING_CONVENTION)
  
  def to_dict(obj: Any, include_none: bool = False) -> dict[str, Any]:
      fields = obj.__table__.columns.keys()
      out: dict[str, Any] = {}
      for field in fields:
          val = getattr(obj, field)
          if val is None and not include_none:
              continue
          if isinstance(val, datetime):
              out[field] = val.isoformat()
          else:
              out[field] = val
      return out
  
  # TODO: Define models here
  