async def set_training_state_to_initiated(workspace_id: ObjectId):
await WorkspaceRepository(get_async_db()).set_training_state(
workspace_id, TrainingState.TRAINING_INITIATED)
async def get_prediction_key(prediction_id: ObjectId) -> PredictionKey:
key = await MlModelRepository(get_async_db()
).get_prediction_key(prediction_id)
return key
async def generate_prediction_id_for_model(workspace_id: ObjectId,
ml_model_id: ObjectId):
key = PredictionKey(None, workspace_id=workspace_id, model_id=ml_model_id)
return await MlModelRepository(get_async_db()).add_prediction_key(key)
async def delete_ml_model_ref_from_workspace(workspace_id: ObjectId,
ml_model_ref: ObjectId):
await WorkspaceRepository(get_async_db()
).delete_ml_model_ref(workspace_id, ml_model_ref)
async def delete_ml_model(ml_model_id: ObjectId):
await MlModelRepository(get_async_db()).delete_ml_model(ml_model_id)
async def get_ml_model(ml_model_id: ObjectId) -> MlModel:
model = await MlModelRepository(get_async_db()).get_ml_model(ml_model_id)
return model
async def add_workspace(workspace: Workspace):
workspace_repository = WorkspaceRepository(get_async_db())
if await workspace_repository.workspace_exists(workspace._id):
raise HTTPException(status.HTTP_406_NOT_ACCEPTABLE,
detail="This workspace id is already in use.")
await WorkspaceRepository(get_async_db()).add_workspace(workspace)
async def get_workspace(workspace_id: ObjectId) -> Workspace:
workspace = await WorkspaceRepository(get_async_db()
).get_workspace(workspace_id)
return workspace