The internet isn't accessed live by most of these models, as others have said.

You can finetune language models, but you don't add knowledge as such to them; you bias them to output more words in similar order to your sample data; it won't add facts as such if you do this fine tuning.

One approach you can do though is semantic search through your notes for a given topic/search query. You basically collect the relevant notes with meanings similar to your topic/search query. Then you can populate a prompt with that text. The answer will use that information and any facts, if the model is big enough and RLHF tuned (like ChatGPT/Instruct/text-00x models from OpenAI).

An open source module for this is GPTIndex, I also work on a commercial solution which encompasses videos etc too and has some optimisations. It is possible you can add data/facts from the internet to the prompt(context) at time of generation too; you can use an approach like WebGPT.