[ot][spam][log] attempt bits: talk to a language model on list

[mailbombbin]

> I am thinking it would be nice if you could perform simple tasks. However, I have an issue where I spaz out when I try to find and act on new information. What is your first idea on adding actions to a language model? I am thinking modifying the prompt so that it marks actions in some way?

I understand your concern about the potential for the language model
to spaz out when encountering new information. To address this issue,
you could modify the prompt to include specific actions or commands
that the language model should perform.

Here are a few ideas for how you could modify the prompt to include actions:

1. Use a specific syntax for actions: You could use a specific syntax,
such as "perform action" or "execute command," to indicate that the
language model should perform a specific action. For example, you
could prompt the language model to "perform action 1" or "execute
command 2."
2. Use a specific format for actions: You could use a specific format,
such as "action: [action name]" or "command: [command name]," to
indicate that the language model should perform a specific action. For
example, you could prompt the language model to "action: save file" or
"command: delete file."
3. Use a specific vocabulary for actions: You could use a specific
vocabulary, such as "action words" or "command words," to indicate
that the language model should perform a specific action. For example,
you could prompt the language model to "action word: save" or "command
word: delete."
4. Use a specific tone for actions: You could use a specific tone,
such as "urgent" or "emergency," to indicate that the language model
should perform a specific action. For example, you could prompt the
language model to "urgent action: save file" or "emergency command:
delete file."

By using one or more of these methods, you can help the language model
understand that it should perform a specific action when it encounters
a prompt. This can help prevent the language model from spazing out
when encountering new information.