Tabular Data

Retrieval Augmented Generation (RAG) allows for adding knowledge from external sources into a Large Language Model (LLM) prompt. In this blog post I will be using this approach for using an LLM to retrieve data from an SAP S4/HANA system and visualizing the data using Streamlit. You will learn how to build a dashboard converting natural language questions into data visualizations using only a minimal amount of code!

Sep 21, 2023

GPT-based models have several inherent problems such as correctly aggregating figures in tabular structures and getting access to corporate data in database system. I will show an approach for connecting GPT to your custom database schema using the Langchain Python package. This allows text-based queries to be executed on the custom database schema, showing impressive results in GPTs ability to formulate complex SQL queries to the database and retrieving the correct information.

May 3, 2023

Large language models are emerging as a tool for solving many information and knowledge-related matters. Back in 2020 GPT-3 made huge improvements in the way that humans are able to interact with an AI, where the model showcased its ability to engage in compelling conversations with a human counterpart. In this article I will showcase how these large language models can be used for answering questions from data stored in tabular form, just as the majority of the world's business data.

Jan 24, 2023