Log Entry 003 - My Lag in RAG-in-a-box

In my recent blog post, I was pretty happy about setting up a simple RAG system. Well, it turns out it wasn't that big of a deal. After reading more on the topic, I realized my approach was just scratching the surface. That is why I added a quick P.S. to the original post with a reality check. Reflecting on my "RAG in a box", I realized the following issues: My AI factory pattern is essentially a hardcoded if/else block, lacking dynamic registration. My Docker configuration is perfectly functional but very basic; there is nothing highly app-specific about it. My approach to chunking documents relied purely on LlamaIndex's built-in functionality, which I now know is a black box that can lead to retrieval failures and hallucinations when data gets messy. My response payload is blind: The API currently just spits out a text string. Because I am not returning any source nodes, citations, or similarity scores, I have no way to prove if the system actually retrieved the answer from my PDF, o