100% accuracy isn’t every part: serving to customers navigate the doc is the actual worth
So, you’re constructing a RAG system or utilizing an LLM to speak with paperwork. However customers usually ask: how can we belief the solutions?
Furthermore, we often hear about hallucinations, which undermine customers’ belief.
If we construct an software however fail to point out customers the place the solutions come from, the appliance may develop into unusable in some circumstances.
On this article, I’ll share an method to deal with this concern. By linking each reply generated by the LLM to its supply textual content within the doc, we are able to construct transparency and belief. This methodology not solely gives clear proof for the solutions but in addition permits customers to confirm the outcomes instantly inside the PDF.
Typically, the generated reply might not be completely correct, however with the ability to find the right supply textual content is already useful for the consumer.
Let’s take an instance of this paper from arxiv.org. We will think about this use case:
Step one on this method is to extract the textual content from the PDF in a structured format.
