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Advanced RAG with context enrichment window

Advanced RAG with context enrichment window

.... and some advanced filtering and re-ranking technique We all know what's Vanilla RAG, how it works, and how to use it but sometimes

community 7 min read
Foundation of Compound AI Meetup Kicking Off, More LanceDB Integrations

Foundation of Compound AI Meetup Kicking Off, More LanceDB Integrations

Community contributions 💡Dspy now works with LanceDB. LanceDB helps DSPy by quickly storing and retrieving information. This lets DSPy find relevant details faster, making prompts

Newsletter 2 min read
Implement contextual retrieval and prompt caching with LanceDB

Implement contextual retrieval and prompt caching with LanceDB

Decrease chunk retrieval failure rate by 35% to 50% Have you ever worked on a task where your users search in one language and the

community 7 min read
Late interaction & efficient Multi-modal retrievers need more than a vector index

Late interaction & efficient Multi-modal retrievers need more than a vector index

A lot has happened in the last few months in AI. Let's look at what's new with document retrieval. Try this

Blog 10 min read
New Lance v0.16.1 Release, Random Access I/O, Hybrid Search+Reranking Report

New Lance v0.16.1 Release, Random Access I/O, Hybrid Search+Reranking Report

🔥New release of Lance v0.16.1🔥 Lance v0.16.1 brings new features to help manage versions and Lance file format editions, a new

Newsletter 2 min read
Training a Variational AutoEncoder from scratch with Lance file format

Training a Variational AutoEncoder from scratch with Lance file format

Autoencoders encode an input into a latent space and decode the latent representation into an output. The output is often referred to as the reconstruction,

community 8 min read
Multi document agentic RAG: A walkthrough

Multi document agentic RAG: A walkthrough

💡This is a community post by Vipul Maheshwari Agentic RAG (Retrieval-Augmented Generation) brings a notable improvement in how information is managed. While traditional RAG systems

community 9 min read
Lance v0.16.1 Feature Roundup

Lance v0.16.1 Feature Roundup

In Lance v0.16.1 we introduced several new features, implemented by a combination of LanceDB engineers and community contributors. Lance is an OSS project

Engineering 9 min read
Improve (almost) every retriever with LanceDB hybrid search and Reranking

Improve (almost) every retriever with LanceDB hybrid search and Reranking

Retrieval is a key component of any type of recommender system, including RAG. The quality of responses generated by chatbot can only be as good

Blog 7 min read
GraphRAG: Hierarchical approach to Retrieval Augmented Generation

GraphRAG: Hierarchical approach to Retrieval Augmented Generation

💡This is a community blog by Akash Desai What is RAG? Retrieval-Augmented Generation (RAG) is an architecture that combines traditional information retrieval systems with large

10 min read
The case for random access I/O

The case for random access I/O

One of the reasons we started the Lance file format and have been investigating new encodings is because we wanted a format with better support

Engineering 10 min read
My summer internship experience at LanceDB

My summer internship experience at LanceDB

I'm Raunak, a master's student at the University of Illinois, Urbana-Champaign. This summer, I had the opportunity to intern as a

Blog 6 min read

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