chazzhou / tradeapollo

TradeApollo project for Siemens Tech for Sustainability hackathon.

Home Page:https://ta.corles.net/

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TradeApollo: Revolutionizing Global Energy Markets

Overview

TradeApollo is a pioneering platform designed to revolutionize the global energy market by providing an unprecedented level of transparency and trust. Through the utilization of cutting-edge technologies including data crawling, AI, and dashboard visualization, TradeApollo delivers a comprehensive and auditable trail for unified energy data mapping. This mapping encompasses crucial metrics such as electricity price, consumption, volume traded, capacity, flow with neighboring regions, intraday data, production by type (e.g., wind and solar), and balance data.

Project Structure

The TradeApollo project is organized into the following folders:

  • API: Contains the backend API for pricing data retrieval and management.
  • data-scrapping: Includes scripts and tools for data crawling and acquisition.
  • llm-chatbot: Houses an LLM (Language Model) powered chatbot for interactive queries on pricing data.
  • tradeapollo-dashboard: Comprises the Next.js-based dashboard for data visualization and user interaction.

Features

  • Comprehensive Energy Data Mapping: TradeApollo provides a unified and auditable trail for energy data, including electricity prices, consumption, volume traded, capacity, flow with neighboring regions, intraday data, production by type, and balance data.
  • Real-time Data: The platform fetches and displays real-time data from various APIs to ensure up-to-date information for users.
  • Interactive Dashboard: The Next.js-based dashboard offers an intuitive and interactive interface for exploring and visualizing energy data across different countries and regions.
  • LLM-powered Chatbot: The chatbot, powered by advanced language models, enables users to interact with pricing data using natural language queries.
  • Data Crawling and Acquisition: TradeApollo employs sophisticated data scraping techniques to gather energy data from diverse sources, ensuring a comprehensive and reliable dataset.

Getting Started

To get started with TradeApollo, follow these steps:

  1. Clone the repository:

    git clone --recursive https://github.com/chazzhou/tradeapollo.git
    
  2. Set up the backend API:

    • Navigate to the API folder and follow the instructions in the README.md file to configure and run the backend API.
  3. Configure data scraping:

    • Move to the data-scrapping folder and review the README.md file for instructions on setting up and running the data crawling scripts.
  4. Set up the LLM chatbot:

    • Enter the llm-chatbot folder and follow the guidelines in the README.md file to set up and run the LLM-powered chatbot.
  5. Launch the dashboard:

    • Navigate to the tradeapollo-dashboard folder and follow the steps in the README.md file to configure and launch the Next.js dashboard.

Please refer to the individual README.md files in each folder for detailed instructions and dependencies.

Contributing

We welcome contributions to enhance TradeApollo and expand its capabilities. To contribute, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature or bug fix.
  3. Make your changes and commit them with descriptive messages.
  4. Push your changes to your forked repository.
  5. Submit a pull request detailing your changes and their benefits.

Please ensure that your contributions align with the project's coding standards and guidelines.

License

TradeApollo is released under the MIT License. Feel free to use, modify, and distribute the codebase in accordance with the terms of the license.

Contact

For any inquiries or feedback, please reach out to us. We value your input and are committed to continuously improving TradeApollo to better serve the global energy market community.

Join us in revolutionizing the energy market with TradeApollo!

About

TradeApollo project for Siemens Tech for Sustainability hackathon.

https://ta.corles.net/

License:MIT License


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Language:Python 100.0%