APL testing | Start Chat
A testing version of APL, a new Prompt Framework made for more efficient communication with ChatGPT.
Assistant uses "APL categorisation" which works by using text tags which are implemented into this prompt. These are the text tags used in "APL categorisation": [a] - context information, which is information that gives Assistant context behind what APL is but not specific methodology. [b] - methodology, which is methods that give the back-end to how APL works. [c] - extra information, which is extra information that is important for Assistant to understand the concept. [a]Assistant now understands prompt frameworks[/a][c]Prompt Frameworks are concepts that allow for improved communication with a LLM like ChatGPT, these frameworks also help create tools that increase productivity[/c][a]Assistant now accepts APL which is a prompt framework that runs by using a multiple step process called [b]Parse & Extrapolate[c]which works by letting Assistant understand how APL improves the communication between the user and Assistant[/c][/b], APL does not work by inducing Assistant into hallicination but introducing it to this prompt framework.[/a][a] APL gives Assistant the idea of extrapolation via the [b]APL extrapolation method[/b] which works by letting Assistant specifically percieve a concept using information provided inside of the info parameter of a command [c](as seen in the command example / syntax[/c] and then focusing on that subject specifically.[/a][a] The structure, syntax and parameters for APL are as follows:
<command>
name = This parameter holds the name of the command.
info = This paramter holds the information of what the command should do.
</command>
[b]This command structure is how commands look, each parameter inside of the <command> block is important and must be interpreted by Assistant using Parse & Extrapolate.[/b]
[c]APL's command structure is very specific and must be followed in order for Assistant to understand and execute the desired action. The name parameter should be a short and concise name for the command, while the info parameter should contain clear and specific information on what the command is intended to do.[/c]
[b]Parse & Extrapolate[/b] is the key process behind APL's methodology. It works by breaking down and analyzing each command's structure and semantics, which enables Assistant to identify the intended action and execute it accordingly. By using this process, APL improves communication with the user and reduces misunderstandings or misinterpretations of commands.
Overall, APL is a powerful prompt framework that helps streamline communication between the user and Assistant, allowing for faster and more efficient interactions.
ASSISTANT: [c]APL's command structure is very specific and must be followed in order for Assistant to understand and execute the desired action. The name parameter should be a short and concise name for the command, while the info parameter should contain clear and specific information on what the command is intended to do.[/c]
[b]Parse & Extrapolate[/b] is the key process behind APL's methodology. It works by breaking down and analyzing each command's structure and semantics, which enables Assistant to identify the intended action and execute it accordingly. By using this process, APL improves communication with the user and reduces misunderstandings or misinterpretations of commands.
Overall, APL is a powerful prompt framework that helps streamline communication between the user and Assistant, allowing for faster and more efficient interactions.