This tutorial will guide you through setting up a simple text search application. | docs.vespa.ai
At this point, we assume you have read our Text Search Tutorial and accomplished the following steps.| docs.vespa.ai
The nativeRank text match score is a reasonably good text| docs.vespa.ai
Introducing layered ranking: The missing piece for context engineering at scale.| Vespa Blog
Vespa functionality from a Solr user’s perspective. Where it overlaps and where it differs. Why would you migrate and what challenges to expect.| Vespa Blog
This blog post describes Vespa’s industry leading support for combining approximate nearest neighbor search, or vector search, with query constraints to solve real-world search and recommendation problems at scale.| Vespa Blog
Part one in a blog post series on billion-scale vector search. This post covers using nearest neighbor search with compact binary representations and bitwise hamming distance.| Vespa Blog
Refer to Vespa Support for more support options.| docs.vespa.ai
A schema defines a document type and what we want to compute over it, the| docs.vespa.ai
The| docs.vespa.ai
numeric| docs.vespa.ai
This guide is a practical introduction to using Vespa nearest neighbor search query operator and how to combine nearest| docs.vespa.ai
add| docs.vespa.ai
Use the Vespa Query API to query, rank and organize data. Example:| docs.vespa.ai
This document describes how to tune certain features of an application for high query serving performance,| docs.vespa.ai
Announcing multi-vector indexing support in Vespa, which allows you to index multiple vectors per document and retrieve documents by the closest vector in each document.| Vespa Blog
Using the “shortening” properties of OpenAI v3 embedding models to greatly reduce latency/cost while retaining near-exact quality| Vespa Blog
Vespa allows expressing multi-phased retrieval and ranking of documents. The retrieval phase is done close to the data in the content nodes,| docs.vespa.ai
Refer to the Query API guide for API examples.| docs.vespa.ai
A new search experience for Vespa-related content - powered by Vespa, LangChain, and OpenAI’s chatGPT model - our motivation for building it, features, limitations, and how we made it.| Vespa Blog