ChromaDB Tutorial: Store & Query Document Embeddings (OpenAI + Python)

Want to build powerful generative AI applications? ChromaDB is a popular open source vector database for embedding storage and querying. This tutorial dives deep into ChromaDB basics and implementation using OpenAI and Python.

The tutorial uses OpenAI and Python and covers topics such as setting up the environment, creating and managing collections, adding and retrieving documents.

Netflix dataset (will be used in future video) : www.kaggle.com/datasets/shivamb/netflix-shows
Blog : mindfulcto.com/supercharge-your-openai-embeddings-…

Code : github.com/technofriends/getting-started-with-chro…

Chapters
(00:00 ) Introduction
(2:09) Setting up Environment
(04:52) Two modes of Chroma DB (local and client/server)
(05:20) Embedding Function
(05:55) Various Embedding Functions supported by Chroma
(06:11) Using same embedding for querying
(08:14) PersistentClient for Chroma DB
(10:31) Creating a collection using Chroma DB
(11:45) Listing collections
(12:19) Retrieving collection
(13:11) Adding documents to collection
(13:45) Retrieving objects from collection
(16:28) Upsert collection
(17:07) peek method for first 10 documents.


#chromadb #embeddings #vectorDatabase #generativeAI #OpenAI #python #machinelearning #AI #tutorial #coding #developer #netflix #dataScience #semanticSearch #informationretrieval