pamela fox's blog

In a recent blog post, I talked about the importance of evaluating the answer quality from any RAG-powered chat app, and I shared my ai-rag-chat-evaluator repo for running bulk evaluations.
In that post, I focused on evaluating a model’s answers for a set of questions that could be answered by the data. But what about all those questions that can’t be answered by the data? Does your model know how to say “I don’t know?” LLMs are very eager...

Retrieval Augmented Generation (RAG) is a popular technique to get LLMs to provide answers that are grounded in a data source. When we use RAG, we use the user's question to search a knowledge base (like Azure AI Search), then pass along both the question...

When I introduce app developers to the concept of RAG (Retrieval Augmented Generation), I often present a diagram like this:
The app receives a user question, uses the user question to search a knowledge base, then sends the question and matching bits of information to the LLM, instructing the LLM to adhere to the sources....

In this post, I'll share a fairly easy way to convert HTML pages to PDF files using the Playwright E2E testing library.
Background: I am working on a RAG chat app solution that has a PDF ingestion pipeline. For a conference demo, I needed it to ingest HTML webpages instead. I could have written my own HTML parser or tried to integrate the LlamaIndex reader, but since...