Nearest Vector Retrieval: TensorFlow universal-sentence-encoder and PGVector queries in Next.js

Learn how to build a movie recommender with TensorFlow, Postgres, PGVector, Javascript & Next.js. This is a series of videos where we build a project together step by step. Check the complete playlist here - https://www.youtube.com/playlist?list=PLo6PI-0mPVLt2nQGH10XA3wdWFZ7r8jOK.

In this chapter you’ll learn how to add an API Router in Next.js. We’ll create an API handler that will encode a string using TensorFlow and then send an SQL request to Postgres database to retrieve recommendations using PGVector.

You can find helpful links and code snippets in this accompanying article - https://aiven.io/developer/building-a-movie-recommender.

Register with Aiven to host Postgres for free and get extra credits: https://go.aiven.io/get-pgvector

Chapters:
00:00 Intro
00:43 Adding movie type with movie.d.ts
01:36 Create a new empty API route
03:32 Add TensorFlow and Postgres functionality
08:43 Run the endpoint and get the list of movies
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Видео Nearest Vector Retrieval: TensorFlow universal-sentence-encoder and PGVector queries in Next.js канала Aiven