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timegpt-forecaster-streamlit's Introduction

TimeGPT-Forecaster - Unleashing Time Series Predictions ๐Ÿ“ˆโฒ๏ธ

Welcome ๐Ÿ™ to the TimeGPT-Forecaster code repository. This project presents a potent ๐Ÿ”ฅ tool for performing time series forecasts ๐Ÿ’น with your own data, powered by Nixtla's TimeGPT ๐Ÿ’ก.

Here is a working version: https://nixtla-timegpt-forecaster.streamlit.app/ (Just click Run Forecast to see a live demo!)

Prerequisites ๐Ÿ“š

Before executing ๐Ÿƒ the project, ensure you have installed the following:

mamba create -n timegpt-forecaster python=3.10
conda activate timegpt-forecaster
pip install -r requirements.txt

Configuration ๐Ÿ”ง

To run this project, several environment variables must be set. These variables include:

  • NIXTLA_TOKEN: Your Nixtla API key ๐Ÿ”‘

Please contact us to secure your API keys.

Clone the Repository ๐Ÿ”„

To clone the repository, issue the following command:

git clone https://github.com/Nixtla/timegpt-forecaster.git

Running the Project ๐Ÿƒโ€โ™€๏ธ

After setting the environment variables and installing the dependencies, you can execute the project with the following command:

streamlit run app.py

This command will start a local server, and you can access the web application by navigating to the supplied URL (typically http://localhost:8501) in your web browser ๐ŸŒ.

How to Use ๐Ÿ› ๏ธ

  1. On opening the application, upload your time series data (and optional exogenous variables) using the provided interface.
  2. Define the frequency of your data, the forecasting horizon and additional variables (such as calendar effects).
  3. Click 'Run Forecast' to initiate a forecast based on the uploaded data.
  4. If required, you can also adjust various forecasting parameters using the available fields before initiating the forecast.
  5. The application will display the forecast results, which can be downloaded for further analysis.

Please bear in mind that some operations may take longer due to the complex calculations involved. Your patience is valued. Revel in the power of time series forecasting! โœจ

Contributing ๐Ÿ‘ฅ

Pull requests are welcomed. For significant changes, kindly open an issue first to discuss what you would like to alter.

License ๐Ÿ“ƒ

Please refer to the LICENSE file for specifics.

Contact ๐Ÿ“ž

For any queries, feel free to get in touch. We're always ready to assist!

timegpt-forecaster-streamlit's People

Contributors

azulgarza avatar

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