Blog - LanceDB Blog

Practical introduction to Adaptive-RAG

Traditional LLMs provide answers based on a fixed knowledge database on which they are trained. This limits their ability to respond with current or specific

Blog 6 min read

Effortlessly Loading and Processing Images with Lance: A Code Walkthrough

Working with large image datasets in machine learning can be challenging, often requiring significant computational resources and efficient data-handling techniques. While widely used for image

Blog 5 min read

Track AI Trends: CrewAI Agents & RAG

This article will teach us how to make an AI Trends Searcher using CrewAI Agents and their Tasks. But before diving into that, let'

Blog 5 min read

Create LLM apps using RAG

If you're considering making a personalized bot for your documents or website that responds to you, you're in the right spot. I'm here to help you create a bot using Langchain and RAG strategies for this purpose.

Blog 19 min read

Multimodal Myntra Fashion Search Engine using LanceDB

In this comprehensive guide, we aim to explain the process of creating a multi-modal search app and break it down into manageable steps. The procedure

Blog 5 min read

GTA5 Multimodal RAG application

Artificial Intelligence (AI) has been actively working with text for quite some time, but the world isn't solely centered around words. If you take a moment to look around, you'll find a mix of text, images, videos, audio, and their combinations.

Blog 11 min read

Optimizing AI Agents: Harnessing OpenAI-Compatible Technologies and Vector Databases

Ollama + litellm + Autogen + langchain + lancedb = Super agent

Blog 6 min read

Improving RAG with Query expansion & reranking models

Exploring Rerankers such as Cross Encoders, Colbert v2 & FlashRank

Blog 7 min read

Implementing Corrective RAG in the Easiest Way

Even though text-generation models are good at generating content, they sometimes need to improve in returning facts. This happens because of the way they are

Blog 4 min read

Hybrid search and custom reranking with LanceDB

Search has historically been a complex problem in computer science. This is partly due to limitations in natural language or contextual understanding, and partly due

Blog 12 min read

Hybrid search: RAG for real-life production-grade applications

by Mahesh Deshwal What is Hybrid Search, and what’s the need for it? With the increasing usage of LLMs in RAG setting, there’s

Blog 6 min read

Benchmarking New OpenAI Embedding Models with LanceDB

A couple of weeks ago, OpenAI launched their new and most performant embedding models with higher multilingual performance and new parameters to control the overall

Blog 3 min read