Member-only story

Build a Question Answering App Using Pinecone And Python

How to use Pinecone to add semantic search to your app

Kirshi Yin
Better Programming
4 min readMar 21, 2022

--

A pinecone flying in the air
Photo by Antonio Janeski on Unsplash

Project Motivation

Let’s imagine you own a website where customers can find the answers to common problems. Instead of maintaining a customer support service, you choose to create a powerful and intelligent search engine. People can simply type their issues in a search field and see similar questions. This way, you reduce duplicate topics, and customers can easily find what they are looking for.
How to ensure that the search is smart enough to show the best matching results to the users? This is when the semantic search comes into play. It tries to understand the intent and context of the search query to provide more accurate results.

In this article, we’ll create a similarity search engine. We’ll use Python and Pinecone, a fully managed vector database, to achieve this goal.

Let’s get started!

Pinecone Key Concepts

Vector representations of objects

In Machine Learning(ML), vector embeddings represent a collection of continuous numbers to determine similarities between various objects. We calculate how close the objects’ vectors are in…

--

--

Kirshi Yin
Kirshi Yin

Written by Kirshi Yin

Self-taught Java Developer. Explores topics about Spring Boot, NLP, Linux, low-coding, and more. Interested in foreign languages, investment, personal growth.

Responses (1)

What are your thoughts?