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Nixtla / nixtla

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
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ApiError: status_code: 500 #437

Closed Wzyh-32 closed 3 months ago

Wzyh-32 commented 3 months ago

import pandas as pd from nixtla import NixtlaClient

1. Instantiate the NixtlaClient

nixtla_client = NixtlaClient(api_key = '')

2. Read historic electricity demand data

df = pd.read_csv('https://raw.githubusercontent.com/Nixtla/transfer-learning-time-series/main/datasets/electricity-short.csv')

3. Forecast the next 24 hours

fcst_df = nixtla_client.forecast(df, h=24, level=[80, 90])

when i use timegpt to forecast,the error happened: nixtla.core.api_error.ApiError: status_code: 500, body: {'status': 500, 'data': None, 'message': 'Unexpected token \'m\', "modal-http"... is not valid JSON', 'details': 'Error occurred while making the request', 'code': 'B30', 'support': 'If you have questions or need support, please email ops@nixtla.io', 'requestID': '22MVFUCXU3', 'headers': {}}

feiding333 commented 3 months ago

Same error!!!!!!!!!

Wzyh-32 commented 3 months ago

同样的错误!!!!!!!! Everything was fine when I used TimeGPT for predictions yesterday, but when I used it again today, the issue mentioned above occurred. I don't know what happened.

feiding333 commented 3 months ago

@tracykteal

Wzyh-32 commented 3 months ago

it is ok today

AzulGarza commented 3 months ago

hey @feiding333 @Wzyh-32! thank you for reporting. the issue was fixed. please let us know and feel free to reopen if the issue persists.