Embeddings and Vectors are a great way of storing and retrieving information for use with AI services. OpenAI provides a great embedding API to do this. Postman lets you make these with easy at [ Ссылка ] (today's sponsor)
In this video we will explore how to create a Vector Database by creating embeddings using the OpenAI API and then storing them in SingleStore.
The first part of the video will cover how to create an embedding using just API requests with Postman. Then we will jump into Single Store and store these in a new database made specifically for vectors like this.
00:00 - Introduction
00:10 - What are Embeddings and Vectors
02:14 - Setup OpenAI Embeddings
03:11 - Setup Postman API Requests to create Embeddings
03:55 - Create Embedding
03:55 - Create Embedding
06:55 - Create PDF or Document Embedding
07:43 - Vector Database - Setup with SingleStore
08:20 - Vector Database - Create Database
09:32 - Vector Database - Create Table
10:41 - Vector Database - Insert Embedding Row
13:25 - Vector Database - Search Embeddings
15:18 - Embedding function with JavaScript and NodeJS
18:08 - OpenAI and GPT Digital Book
18:29 - Conclusion
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OpenAI Embedding Documentation:
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SingleStore Vector Database
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OpenAI Embeddings and Vector Databases Crash Course
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