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GPT_CodeInterpreter Project 🤖

GPT_CodeInterpreter is an AI-driven project designed to carry out various tasks related to code interpretation. It is built on a plugin architecture that can easily extend new features.

Creating Plugins 👩‍💻👨‍💻

To create a plugin, follow these steps:

  1. Create a new directory in the 'plugins' folder. The directory name will be the name of the plugin.

  2. In the new directory, create a file named functions.py. In this file, define the functions you want the plugin to provide. Each function should be a top-level function and should be named in a way that reflects its functionality.

  3. In the same directory, create a file named config.json. In this file, add the following JSON:

{
    "enabled": true
}

This will enable the plugin by default. If you want to disable the plugin, you can change true to false.

Running the Project 🏃‍♂️🏃‍♀️

To run this project, you need to follow these steps:

  1. First, you need to create a .env file in the root directory of the project. You can do this by copying the .env.example file.

  2. In the .env file, you need to provide your OpenAI API key. This should be a string, like OPENAI_API_KEY=your_api_key_here. Please replace your_api_key_here with your actual OpenAI API key.

  3. Still in the .env file, you need to set the base URL for the OpenAI API. This should be a string, like OPENAI_API_BASE=https://api.openai.com/v1.

  4. After saving the .env file, you need to install GPT_CodeInterpreter. You can do this with pip: pip install -r requirements.txt.

  5. Once GPT_CodeInterpreter is installed, you can run the project with the following command: chainlit run app.py.

  6. If chainlit run app.py error to communicate to openai,you can try chainlit run app_cn.py.

Hope this display is more engaging and readable! If you have any other questions or need further assistance, feel free to let me know.

Contributing

Contributions are welcome! Please read the contribution guide to learn how to contribute to this project.