/plushcap/analysis/weaviate/weaviate-generative-feedback-loop-with-weaviate-and-spcs

Weaviate in Snowflake’s Snowpark Container Services

What's this blog post about?

A Generative Feedback Loop is a powerful use case that combines a Large Language Model (LLM) with semantic search. This technique can be used to enrich, enhance or summarize data, enabling new opportunities for searching through information and providing better search results. In this blog post, the author demonstrates how to implement a Generative Feedback Loop using open-source software like Weaviate, Ollama, and Mistral. The process involves loading product review data into Snowflake, deploying Weaviate, Ollama, and a vectorizer within Snowflake's processing engine (SPCS), generating product metadata using the latest Mistral model, and performing semantic and hybrid searches using Weaviate. This approach allows users to search for experiences, feelings, keywords, or product names of products while keeping all data within Snowflake.

Company
Weaviate

Date published
Feb. 8, 2024

Author(s)
Jonathan Tuite

Word count
2176

Language
English

Hacker News points
None found.


By Matt Makai. 2021-2024.