Inquiry regarding Agent Implementation for Track 1

Orak Game Agent Challenge
#1

Hello,

I am currently participating in Track 1 of the Orak Challenge.

I would like to ask if there are any specific constraints regarding the agent implementation. Aside from the requirement to use an LLM with 8B parameters or fewer, are there any restrictions on the internal operations of the agent?

Specifically, I would like to confirm if we are permitted to perform tasks such as pre-processing data, post-processing outputs, or enabling tool usage. Furthermore, could you please confirm if we have full freedom to implement the agent in any other way beyond the examples listed above?

Additionally, I would like to ask if there is a strict rule that one act call must correspond to exactly one LLM call, or if it is permissible to make multiple calls or no calls at all within a single act.

I want to make sure there are no limitations on the internal logic or processes.

Thank you.

#2

i have the same question, what sort of additional frameworks are allowed to use, because you can use deep learning model for these tasks, and if you do, is it going to be considered violation or not? Can you be more concrete, what is allowed and what is not allowed to use?