Designing a Table Format for ML Workloads
Explore designing a table format for ML workloads with practical insights and expert guidance from the LanceDB team.
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GraphRAG: Hierarchical Approach to Retrieval-Augmented Generation
Explore GraphRAG: hierarchical approach to retrieval-augmented-generation with practical insights and expert guidance from the LanceDB team.
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's first understand what CrewAI is and how we can use it for these applications.
Multimodal Myntra Fashion Search Engine Using LanceDB
Build a multimodal fashion search engine with LanceDB and CLIP embeddings. Follow a step‑by‑step workflow to register embeddings, create the table, query by text or image, and ship a Streamlit UI.
Custom Datasets for Efficient LLM Training Using Lance
See about custom datasets for efficient llm training using lance. Get practical steps, examples, and best practices you can use now.
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 trained.
Hybrid Search and Custom Reranking with LanceDB
Combine keyword and vector search for higher‑quality results with LanceDB. This post shows how to run hybrid search and compare rerankers (linear combination, Cohere, ColBERT) with code and benchmarks.
Hybrid Search: RAG for Real-Life Production-Grade Applications
Get about hybrid search: rag for real-life production-grade applications. Get practical steps, examples, and best practices you can use now.
Efficient RAG with Compression and Filtering
Discover about efficient rag with compression and filtering. Get practical steps, examples, and best practices you can use now.