Getting Started with On-Device AI: RAG using ObjectBox Vector Database and LangChain

Today, we're exploring on-device AI / Edge AI, where the hardware isn’t a limit and the cloud optional.

Vector databases have transformed how we handle unstructured data like images, videos, and texts, making it searchable and more usable. Until today, however, they needed powerful servers or a cloud infrastructure.

With on-device vector database, you can bring this capability directly onto a wide range of devices, from mobile phones to IoT and embedded systems. In this tutorial, we’ll explore how you can set up your local AI tech stack to build new on-device AI use cases.

We’ll guide you through creating a Retrieval Augmented Generation (RAG) app using ObjectBox and LangChain. RAG techniques allow us to augment a language model's knowledge base actively, ensuring your AI can access and reason with your data and the very latest information. With ObjectBox you can do that, without the data ever needing to leave the device.

Stay tuned as we explore how to integrate these technologies into your projects effectively, and don't forget to check out the GitHub link below for the code: 

Docs: https://docs.objectbox.io/ann-vector-search

github code : https://github.com/krishnaik06/Updated-Langchain/tree/main/objectbox

Видео Getting Started with On-Device AI: RAG using ObjectBox Vector Database and LangChain канала Krish Naik