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Building RAG on codebases: Part 2
Building a Cursor-like @codebase RAG solution. Part 2 focuses on the generating embeddings and the retrieval strategy using a combination of techniques in LanceDB.
Building RAG on codebases: Part 1
Building a Cursor-like @codebase RAG solution. Part 1 focuses on indexing techniques, chunking strategies, and generating embeddings in LanceDB.
Implement Contextual Retrieval and Prompt Caching with LanceDB
Unlock about implement contextual retrieval and prompt caching with lancedb. Get practical steps, examples, and best practices you can use now.
Training a Variational AutoEncoder from Scratch with Lance File Format
Train a Variational Autoencoder end‑to‑end using Lance for fast, scalable data handling. You’ll set up the dataset, build the VAE in PyTorch, and run training, sampling, and reconstructions.
Multi Document Agentic RAG: a Walkthrough
Unlock about multi document agentic rag: a walkthrough. Get practical steps, examples, and best practices you can use now.
Zero Shot Image Classification with Vector Search
Get about zero shot image classification with vector search. Get practical steps, examples, and best practices you can use now.
Chat with Your Stats Using Langchain Dataframe Agent & LanceDB Hybrid Search
In this blog, we’ll explore how to build a chat application that interacts with CSV and Excel files using LanceDB’s hybrid search capabilities.
Tokens per Second Is NOT All You Need
Explore about tokens per second is not all you need. Get practical steps, examples, and best practices you can use now.
Chunking Techniques with Langchain and LlamaIndex
In our last blog, we talked about chunking and why it is necessary for processing data through LLMs. We covered some simple techniques to perform text chunking.
Convert Any Image Dataset to Lance
In our article, we explored the remarkable capabilities of the Lance format, a modern, columnar data storage solution designed to revolutionize the way we work with large image datasets in machine learning.
A Primer on Text Chunking and Its Types
Text chunking is a technique in natural language processing that divides text into smaller segments, usually based on the parts of speech and grammatical meanings of the words.