Warn: This README is AI generated, just like all the source files of this project.

Junior is an exploratory project aimed at revolutionizing the way programmers interact with the development process. Just like how Linus Torvalds oversees the Linux Kernel development without coding himself, this project allows developers to communicate with the AI and supervise the development process.

By providing specific task details in a prompt descriptor and highlighting the relevant parts of your project, you can delegate code implementation, documentation, testing, and more to your AI Junior.

To install, clone the repository and run npm install in the root directory.

There are two ways to use this project: a command-line interface (CLI) and a web interface.

To start the CLI, use npm run cli. This mode uses the ChatGPT API, and you'll need an API key stored in the OPENAI_API_KEY environment variable.

Run the application with npm start to start a local server on port 3000, where you can generate a prompt and automatically copy it to paste into ChatGPT. The web interface is designed for use with ChatGPT Pro and doesn't require an API key.

A prompt descriptor is a YAML file (prompt.yaml) outlining the details necessary for generating a task prompt for the AI model.

Here's an example of a prompt descriptor:

task: prompt/task/feature/implement.md
attention:
  - src/interactiveSession/startInteractiveSession.js
  - src/prompt/createPrompt.js
  - src/attention/readAttention.js
  - prompt.yaml
requirements: >
  Write a README.md for this _exploratory_ project!
format: prompt/format/new_file_version.md

Each element in the descriptor serves a specific purpose:

• task: Describes the task type and scope. For example, feature/implement, bug/fix, or refactor/. You can check out the prompt/task/feature/implement.md file as an example.
• attention: Lists the files and directories most relevant to the task.
• requirements: Describes the actual task in a human-readable format.
• format: Determines how the output will be formatted.

The attention mechanism guides the AI model by providing it with a working set. It helps overcome the limited working memory of large language models.

The working set is a subset of the entire project that's currently in focus. It includes both files and directories. For files, the content is directly provided to the AI. For directories, a brief list of files and subdirectories within them is presented.

Contributions are welcome! Remember, we eat our own dog food in this project. Junior is designed to write itself. Your main role will be to oversee the work, provide detailed prompts, and review the outcomes.

For support, please create an issue in the GitHub repository.

Note: For meaningful results, it's recommended to use the GPT-4 model or a more recent version.