BY JACQUELIINE ANE
ChatGPT has become an integral tool that most people use daily to automate various tasks. If you have used ChatGPT for any length of time, you would have realized that it can provide wrong answers and has limited to zero context on some niche topics. This brings up the question of how we can tap into chatGPT to bridge the gap and allow ChatGPT to have more custom data.
A wealth of knowledge is distributed in various platforms we interact with daily, i.e., via confluence wiki pages at work, slack groups, company knowledge base, Reddit, Stack Overflow, books, newsletters, and google documents shared by colleagues. Keeping up with all these information sources is a full-time job in itself.
Wouldn't it be nice if you could selectively choose your data sources and feed that information into ChatGPT conversation with your data with ease?
1. Feeding Data via Prompt Engineering
Before we jump into how we can extend ChatGPT, let's look at how we could extend ChatGPT manually and what the issues are. The conventional approach to extending ChatGPT is via prompt engineering.
This is quite simple to do since ChatGPT is context aware. First, we need to interact with ChatGPT by appending the original document content before the actual questions.
.jpg)
