Auto-Trader

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A trading bot that automatically executes trades on your behalf, utilizing the power of large language models (LLMs).

Auto-Trader 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

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# **Auto Trader** 🧑‍💻
> Auto Trader is a tool designed to automatically trade on **Your** behalf, earning for you while you sleep 💤

## Why Auto Trader?
Trading is Easy, Profitable Trading is Not! Trading requires extensive knowledge about companies, markets, industries and trends, which with our busy life is extremely difficult. Thereby AutoTrader Was Developed.
</div>

## **Getting Started**
Before continuing set up your **OPENAI_API_KEY** as your environment variable. If you are unaware on how to do so, refer to this guide - https://help.openai.com/en/articles/5112595-best-practices-for-api-key-safety. <br/> <br/> You are also required to setup a Paper Trading Account using Alpaca. After making the account set the following environment variables as well:-
1. **ALPACA_API_KEY**:- The API Key of your Paper Trading Account
2. **ALPACA_SECRET**:- The Secret of the Alpaca API KEY
3. **ALPHA_VANTAGE_API_KEY**:- The Api Key of Alpha Vantage, which can be retrieved from here - https://www.alphavantage.co/
---

💡 - _Try Running This in a Raspberry Pi_

---

1. ### **Installation:** 
    ```shell
    git clone https://github.com/Itachi-Uchiha581/Auto-Trader.git
    ```

2. ### **Usage Through CLI:**
    ```shell
    cd Auto-Trader
    ```
    ```shell
    pip install -r requirements.txt
    ```
    ```shell
    python main.py
    ```
    __The Above Command will Start the Trading Programme__

[//]: # (## Tutorials:)

[//]: # (1. [**Creating a Customer Service Agent by Fine-Tuning GPT-3.5-Turbo**]&#40;https://medium.com/@adeebfaiyaz/auto-data-generating-custom-datasets-to-fine-tune-gpt-3-5-using-python-2fcd857d6011?source=friends_link&sk=007cbd8a75f9da6ea2e8ded82f1bc30a&#41;)
## Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request

**Contributions can be made by making the existing code efficient and cleaner, adding new engines (an example engine with guide is already given inside autodata/engines), adding LLM training data analyser, creating testing scripts etc.**
## To do:
1. _UX Improvements_
2. _Backtesting Functionalities_
3. _Algorithm Improvements_
## License

Distributed under the MIT License. See `LICENSE` for more information.

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