(
model_id,
exception_handler=lambda e: maxkb_logger.error(
_("Failed to obtain vector model: {error} {traceback}").format(error=str(e), traceback=traceback.format_exc())
),
)
| 23 | |
| 24 | |
| 25 | def get_embedding_model( |
| 26 | model_id, |
| 27 | exception_handler=lambda e: maxkb_logger.error( |
| 28 | _("Failed to obtain vector model: {error} {traceback}").format(error=str(e), traceback=traceback.format_exc()) |
| 29 | ), |
| 30 | ): |
| 31 | try: |
| 32 | model = QuerySet(Model).filter(id=model_id).first() |
| 33 | |
| 34 | default_params = get_model_default_params(model) |
| 35 | |
| 36 | embedding_model = ModelManage.get_model(model_id, lambda _id: get_model(model, **{**default_params})) |
| 37 | except Exception as e: |
| 38 | exception_handler(e) |
| 39 | raise e |
| 40 | return embedding_model |
| 41 | |
| 42 | |
| 43 | @celery_app.task(base=QueueOnce, once={"keys": ["paragraph_id"]}, name="celery:embedding_by_paragraph") |
no test coverage detected