import json import logging from typing import Optional import peewee as pw from playhouse.shortcuts import model_to_dict from pydantic import BaseModel, ConfigDict from apps.web.internal.db import DB, JSONField from config import SRC_LOG_LEVELS log = logging.getLogger(__name__) log.setLevel(SRC_LOG_LEVELS["MODELS"]) #################### # Models DB Schema #################### # ModelParams is a model for the data stored in the params field of the Model table # It isn't currently used in the backend, but it's here as a reference class ModelParams(BaseModel): model_config = ConfigDict(extra="allow") pass # ModelMeta is a model for the data stored in the meta field of the Model table # It isn't currently used in the backend, but it's here as a reference class ModelMeta(BaseModel): description: Optional[str] = None """ User-facing description of the model. """ vision_capable: Optional[bool] = None """ A flag indicating if the model is capable of vision and thus image inputs """ model_config = ConfigDict(extra="allow") pass class Model(pw.Model): id = pw.TextField(unique=True) """ The model's id as used in the API. If set to an existing model, it will override the model. """ user_id = pw.TextField() base_model_id = pw.TextField(null=True) """ An optional pointer to the actual model that should be used when proxying requests. Currently unused - but will be used to support Modelfile like behaviour in the future """ name = pw.TextField() """ The human-readable display name of the model. """ params = JSONField() """ Holds a JSON encoded blob of parameters, see `ModelParams`. """ meta = JSONField() """ Holds a JSON encoded blob of metadata, see `ModelMeta`. """ updated_at: int # timestamp in epoch created_at: int # timestamp in epoch class Meta: database = DB class ModelModel(BaseModel): id: str base_model_id: Optional[str] = None name: str params: ModelParams meta: ModelMeta #################### # Forms #################### class ModelsTable: def __init__( self, db: pw.SqliteDatabase | pw.PostgresqlDatabase, ): self.db = db self.db.create_tables([Model]) def get_all_models(self) -> list[ModelModel]: return [ModelModel(**model_to_dict(model)) for model in Model.select()] def update_all_models(self, models: list[ModelModel]) -> bool: try: with self.db.atomic(): # Fetch current models from the database current_models = self.get_all_models() current_model_dict = {model.id: model for model in current_models} # Create a set of model IDs from the current models and the new models current_model_keys = set(current_model_dict.keys()) new_model_keys = set(model.id for model in models) # Determine which models need to be created, updated, or deleted models_to_create = [ model for model in models if model.id not in current_model_keys ] models_to_update = [ model for model in models if model.id in current_model_keys ] models_to_delete = current_model_keys - new_model_keys # Perform the necessary database operations for model in models_to_create: Model.create(**model.model_dump()) for model in models_to_update: Model.update(**model.model_dump()).where( Model.id == model.id ).execute() for model_id, model_source in models_to_delete: Model.delete().where(Model.id == model_id).execute() return True except Exception as e: log.exception(e) return False Models = ModelsTable(DB)