The post discusses the challenges of managing customer information, with a focus on using Snowflake Cortex to integrate and compare customer data. It highlights the addition of VECTOR data types and LLM functions to assist in text vectorization, as well as methods for scoring customer name similarity. The creation of a Streamlit app for demonstration and the use of various models for vectorizing data are also covered. The author emphasizes the need for careful monitoring and tuning of scoring thresholds to ensure accurate customer identification.
Category Archives: Python
Snowflake AI LLM Showdown: Easily Compare Models with Streamlit
The post discusses the increasing prevalence of AI and the process of building a Streamlit app to compare responses from different LLM models within Snowflake Cortex. It outlines the setup processes for Snowflake and Streamlit and demonstrates the creation of a chatbot interface to compare model outputs for a given prompt.
TL;DR Made Easy: Summarizing Web Content with Snowflake and Streamlit
This article discusses leveraging Snowflake’s Cortex to create a Streamlit app that summarizes web content. It outlines prerequisites, importing libraries, inputting the URL, parsing HTML with BeautifulSoup, and using Snowflake to summarize the content. The app is executed and its potential is highlighted. The author offers the complete code on GitHub for exploration.
Eric Heilman 