Saurabh Taneja
10/25/2023, 3:32 PMCountryHolidays
to date_features
and I keep on getting ApiError: status_code: 413
error -
INFO:nixtlats.timegpt:Validating inputs...
INFO:nixtlats.timegpt:Preprocessing dataframes...
INFO:nixtlats.timegpt:Calling Forecast Endpoint...
WARNING:nixtlats.timegpt:The specified horizon "h" exceeds the model horizon. This may lead to less accurate forecasts. Please consider using a smaller horizon.
---------------------------------------------------------------------------
ApiError Traceback (most recent call last)
Cell In[75], line 2
1 # Forecasting multiple series simultaneously. Forecast horizon (h) of 365 days, 10 fine-tune steps.
----> 2 Y_hat_df = timegpt.forecast(df=filtered_df, h=365, freq='D', finetune_steps=10, id_col='unique_id', time_col='ds', target_col='y', date_features=[CountryHolidays(['US'])])
File ~/.local/share/virtualenvs/timegpt-XqoHAN5_/lib/python3.11/site-packages/nixtlats/timegpt.py:1001, in TimeGPT.forecast(self, df, h, freq, id_col, time_col, target_col, X_df, level, finetune_steps, clean_ex_first, validate_token, add_history, date_features, date_features_to_one_hot, num_partitions)
937 """Forecast your time series using TimeGPT.
938
939 Parameters
(...)
998 predictions (if level is not None).
999 """
1000 if isinstance(df, pd.DataFrame):
-> 1001 return self._forecast(
1002 df=df,
1003 h=h,
1004 freq=freq,
1005 id_col=id_col,
1006 time_col=time_col,
1007 target_col=target_col,
1008 X_df=X_df,
1009 level=level,
1010 finetune_steps=finetune_steps,
1011 clean_ex_first=clean_ex_first,
1012 validate_token=validate_token,
1013 add_history=add_history,
1014 date_features=date_features,
1015 date_features_to_one_hot=date_features_to_one_hot,
1016 )
1017 else:
1018 from nixtlats.distributed.timegpt import _DistributedTimeGPT
File ~/.local/share/virtualenvs/timegpt-XqoHAN5_/lib/python3.11/site-packages/nixtlats/timegpt.py:699, in _TimeGPT._forecast(self, df, h, freq, id_col, time_col, target_col, X_df, level, finetune_steps, clean_ex_first, validate_token, add_history, date_features, date_features_to_one_hot)
690 raise Exception("Token not valid, please email ops@nixtla.io")
692 df, X_df, drop_uid = self._validate_inputs(
693 df=df,
694 X_df=X_df,
(...)
697 target_col=target_col,
698 )
--> 699 fcst_df = self._multi_series_forecast(
700 df=df,
701 h=h,
702 freq=freq,
703 X_df=X_df,
704 level=level,
705 finetune_steps=finetune_steps,
706 clean_ex_first=clean_ex_first,
707 add_history=add_history,
708 date_features=date_features,
709 date_features_to_one_hot=date_features_to_one_hot,
710 )
711 fcst_df = self._validate_outputs(
712 fcst_df=fcst_df,
713 id_col=id_col,
(...)
716 drop_uid=drop_uid,
717 )
718 return fcst_df
File ~/.local/share/virtualenvs/timegpt-XqoHAN5_/lib/python3.11/site-packages/nixtlats/timegpt.py:526, in _TimeGPT._multi_series_forecast(self, df, h, freq, X_df, level, finetune_steps, clean_ex_first, add_history, date_features, date_features_to_one_hot)
524 input_size, model_horizon = self._get_model_params(freq)
525 main_logger.info("Calling Forecast Endpoint...")
--> 526 fcst_df = self._hit_multi_series_endpoint(
527 Y_df=Y_df,
528 X_df=X_df,
529 h=h,
530 freq=freq,
531 clean_ex_first=clean_ex_first,
532 finetune_steps=finetune_steps,
533 x_cols=x_cols,
534 level=level,
535 input_size=input_size,
536 model_horizon=model_horizon,
537 )
538 if add_history:
539 main_logger.info("Calling Historical Forecast Endpoint...")
File ~/.local/share/virtualenvs/timegpt-XqoHAN5_/lib/python3.11/site-packages/nixtlats/timegpt.py:455, in _TimeGPT._hit_multi_series_endpoint(self, Y_df, X_df, x_cols, h, freq, finetune_steps, clean_ex_first, level, input_size, model_horizon)
448 self._validate_input_size(
449 Y_df=Y_df,
450 input_size=input_size,
451 model_horizon=model_horizon,
452 require_history=finetune_steps > 0 or level is not None,
453 )
454 y, x = self._transform_dataframes(Y_df, X_df)
--> 455 response_timegpt = self.client.timegpt_multi_series(
456 y=y,
457 x=x,
458 fh=h,
459 freq=freq,
460 level=level,
461 finetune_steps=finetune_steps,
462 clean_ex_first=clean_ex_first,
463 )
464 if "data" in response_timegpt:
465 response_timegpt = response_timegpt["data"]
File ~/.local/share/virtualenvs/timegpt-XqoHAN5_/lib/python3.11/site-packages/nixtlats/client.py:158, in Nixtla.timegpt_multi_series(self, freq, level, fh, y, x, clean_ex_first, finetune_steps)
156 except JSONDecodeError:
157 raise ApiError(status_code=_response.status_code, body=_response.text)
--> 158 raise ApiError(status_code=_response.status_code, body=_response_json)
ApiError: status_code: 413, body: {'data': None, 'message': 'Request failed with status code 413', 'code': 'B30', 'requestID': 'ZKZMHPGF2F', 'support': 'If you have questions or need support, please email ops@nixtla.io'}
date_features=['month']
Max (Nixtla)
10/25/2023, 4:09 PMSaurabh Taneja
10/25/2023, 4:10 PMMax (Nixtla)
10/25/2023, 4:12 PMSaurabh Taneja
10/25/2023, 4:13 PM