I'm trying to implement a chatbot for a lumberyard that can answer user queries about any residential construction project they're building. It needs to have RAG functionality that references Wisconsion building code. I bought a PDF copy of that building code, chopped it up into chunks by following langchain RAG docs (I have a simple chunking notebook I built for chopping pdfs and sending them to a Pinecone DB if anyone wants it), used OpenAi for embedding those chunks, and was able to store them in a Pinecone vector database with that entire 800-some page doc stored as vectors. I have a functioning streamlit app that can answer one question correctly based on the database. I've been hung up for weeks trying to fix a deprecation warning on how the langchain chain declaration is made. My functioning github repo: ctsTech2/wiCodeAgent (github.com) Based on something I heard a few minutes ago 😏 Langchain may not be the way to go for my use case. I'm open to any thoughts I'd like the chatbot to be able to answer follow up questions, maintain context, and generate estimates for projects with the current lumberyard prices.