diff --git a/Readme.md b/README.md similarity index 100% rename from Readme.md rename to README.md diff --git a/README.mv b/README.mv deleted file mode 100644 index 2da0c1b..0000000 --- a/README.mv +++ /dev/null @@ -1,60 +0,0 @@ -# Vantage+TimeGPT - Forecasting Cloud Costs ☁️⏲️ - -Welcome 🙏 to the Vantage+TimeGPT code repository. This project offers a powerful 🔥 tool to predict cloud costs 💰 and detect anomalies with Vantage and Nixtla, leveraging the power of Nixtla's TimeGPT and OpenAI's GPT-4 to provide explanations 💡. - -## Prerequisites 📚 - -Before running 🏃 the project, make sure you have installed the following: - -```bash -pip install -r requirements.txt -``` - -## Configuration 🔧 - -In order to run this project, you need to set several environment variables. These variables are: - -- `OPENAI_TOKEN`: Your OpenAI API key 🔑 -- `VANTAGE_TOKEN`: Your Vantage API key 🔑 -- `TIMEGPT_TOKEN`: Your Nixtla API key 🔑 - -## Clone the Repository 🔄 - -To clone the repository, run the following command: - -```bash -git clone https://github.com/Nixtla/vantage.git -``` - -## Running the Project 🏃‍♀️ - -After setting up the environment variables and installing the dependencies, you can run the project using the following command: - -```bash -streamlit run streamlit.py -``` - -This command will start a local server, and you can access the web application by navigating to the provided URL (usually `http://localhost:8501`) in your web browser 🌐. - -## How to Use 🛠️ - -1. When you open the application, enter your Vantage token to fetch cloud cost data. If you don't change the default Vantage token, the app will use synthetic data. -2. You can view available cost reports by clicking the 'Get reports' button. -3. To fetch historical data for a specific report, enter its ID and click 'Fetch historic data'. -4. Click 'Forecast costs and Detect anomalies' to request a forecast and detect any cost anomalies. -5. You can also forecast costs for a specific grouping criteria. Enter the start date, grouping criteria, and report ID in the relevant fields and click 'Fetch data and create the plot'. -6. The application will display the forecast and any detected anomalies for the selected report. - -Please note that some of the operations may take some time due to the complex computations involved. Patience is appreciated. Enjoy the magic of forecasting! ✨ - -## Contributing 👥 - -Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. - -## License 📃 - -Please see the [LICENSE](LICENSE.md) file for details. - -## Contact 📞 - -If you have any questions, feel free to reach out to us. We'd be happy to help! \ No newline at end of file