The ability to query PDFs like ChatGPT is a powerful feature, but how do you get there? The answer is Relevance AI, a platform that can easily upload PDFs and store their text data so that it can be queried with ChatGPT. Let's take a look at how it works.
How it works
Relevance AI takes the PDFs uploaded to it and stores the text in dataset. When a query is then made to the dataset, it extracts the most relevant content from the dataset. This is the content that will be used with ChatGPT.
Once the PDF content has been extracted, it can be used with GPT. GPT is now fed the specific portions of the data that are relevant to the query, bypassing the word limit.
This can be summarised in the following steps:
- Upload PDFs to Relevance AI
- Extract text from PDF and store in dataset
- Find most relevant content in dataset to query
- Feed relevant content to GPT
Keep in mind that this is all done automatically, without code via the dashboard. You can try it out in less than 3 minutes and see the results for yourself.
Try it yourself
PDFs can be powerful resources when used with ChatGPT. With Relevance AI as the platform, you can easily upload PDFs, extract the relevant content, and query it with ChatGPT. This makes it possible to get the most accurate results from the PDFs. To try it yourself, head to https://cloud.relevanceai.com and sign up for a free account. To find a tutorial that goes through each step, read this article.