Searching complex documents with ColPali - part 1
The article introduces the ColPali model, a late-interaction model that simplifies the process of searching complex documents with images and tables, and discusses its implementation in Elasticsearch.
Semantic text in Elasticsearch: Simpler, better, leaner, stronger
Our latest semantic_text iteration brings a host of improvements. In addition to streamlining representation in _source, benefits include reduced verbosity, more efficient disk utilization, and better integration with other Elasticsearch features. You can now use highlighting to retrieve the chunks most relevant to your query. And perhaps best of all, it is now a generally available (GA) feature!
Unifying Elastic vector database and LLM functions for intelligent query
Leverage LLM functions for query parsing and Elasticsearch search templates to translate complex user requests into structured, schema-based searches for highly accurate results.
Elasticsesarch semantic search, leveled up: now with native match, knn and sparse_vector support
Semantic text search becomes even more powerful, with native support for match, knn and sparse_vector queries. This allows us to keep the simplicity of the semantic query while offering the flexibility of the Elasticsearch query DSL.
Filtered HNSW search, fast mode
Explore the improvements we have made for HNSW vector search in Apache Lucene through our ACORN-1 algorithm implementation.
Alibaba Cloud AI Service & Elasticsearch: Embeddings and reranking
Using Alibaba Cloud AI Service features with Elasticsearch.
Understanding sparse vector embeddings with trained ML models
Learn about sparse vector embeddings, understand what they do/mean, how they differ from dense vector embeddings, and how to implement semantic search with them.
Elasticsearch Open Inference API adds support for Jina AI Embeddings and Rerank Model
Explore how to access Jina AI models using the Elasticsearch Open Inference API.
Elasticsearch hybrid search
Learn about hybrid search, the types of hybrid search queries Elasticsearch supports, and how to craft them.
Self-querying retrievers with Elasticsearch: Unleashing your metadata
Discover how to utilize self querying retrievers with Elasticsearch to increase the relevance of your semantic search with structured filters.
How to set up vector search in Elasticsearch
Learn how to set up vector search in Elasticsearch and execute k-NN searches.
A quick introduction to vector search
This article is the first in a series of three that will dive into the intricacies of vector search, also known as semantic search, and how it is implemented in Elasticsearch.