All You Must Find out about Vector Databases and The right way to Use Them to Increase Your LLM Apps | by Dominik Polzer | Sep, 2023

A Step-by-Step Information to Uncover and Harness the Energy of Vector Databases


Why we want Vector Shops for LLM apps — Picture by the writer


What is so special about Vector Databases?
How do we map the meaning of a sentence to a numerical representation?
How does that help our LLM app?
Why can’t we just give the LLM all the data we have?

Hands-On Tutorial — Text to Embeddings and Distance Metrics

1. Text to Embeddings
2. Plot 384 dimensions in 2 using PCA
3. Calculate the distance metrics

In direction of Vector Shops

How to accelerate the Similarity Search?
What are the different Vector Stores we can choose from?

Hands-On Tutorial — Set up your first Vector Store

1. Install chroma
2. Get/create a chroma client and collection
3. Add some text documents to the collection
4. Extract all entries from database to excel file
5. Query the collection


Vector databases are a scorching matter proper now. Firms hold elevating cash to develop their vector databases or so as to add vector search capabilities to their current SQL or NoSQL databases.

Vector Retailer Funding — Picture by the writer (Chroma, 2023; Cook dinner, 2022; Miller, 2022)

Vector Databases make it doable to shortly search and evaluate giant collections of vectors. That is so fascinating as a result of probably the most up-to-date embedding fashions are extremely able to understanding the semantics/which means behind phrases and translating them into vectors. This permits us to effectively evaluate sentences with one another.

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