1) Prompting : A good prompt can drastically change the output of a large language model,
effective prompts will be elaborated on in the
selectPage( pages[ 2 ] ) }>next section.
2) Clarify : As the saying "garbage in, garbage out" goes with computing, it continues here to an extraordinary extent.
One of, if not, the most effective methods of improving LLM responses is by providing and continually improving:
queries, instructions, sample code, or other data you feed into the language model that fits your current need.
3) Reminders : LLMs, just like humans, need reminders sometimes. If you are sending large amounts of data, or
if you are having a model make many web requests, it's very likely you will leave the model's
context window. This can lead to unpredictable and unexplainable results, so do with that information
what you will.
4) Tooling : Luckily for you, utilizing our provided
selectPage( pages[ 4 ] ) }>tooling is not something that you will have to initiate.
Models equipped with tooling functionality will automatically use our provided tools to better complete your requests.
All this being said, you will have to "manage" your tooling. For web requests, as mentioned above, they can quickly
devour your avaiable context window and cause erroneous responses to occur. Notes as well, when above capacity, can
cause the same. We do provide a way to manage notes, and we can only suggest to keep web requests to a minimum.