Category: Vector Database

Articles tagged Vector Database

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A recipe for GenAI powered search (RAG) on your PDF treasure
Elasticsearch Labs

A recipe for GenAI powered search (RAG) on your PDF treasure

An easy approach to create embeddings for and apply semantic GenAI powered search (RAG) to PDF documents using Elastic's new semantic_text field type and the Playground in Elastic.

Christine Komander
Elasticsearch open inference API adds native chunking support for Hugging Face
Elasticsearch Labs

Elasticsearch open inference API adds native chunking support for Hugging Face

Elasticsearch open inference API extends support for models from Hugging Face, and brings native chunking to Hugging Face users

Max Hniebergall
Dataset translation with LangChain, Python & Vector Database for multilingual insights
Elasticsearch Labs

Dataset translation with LangChain, Python & Vector Database for multilingual insights

Learn how to translate a dataset from one language to another and use Elastic's vector database capabilities to gain more insights.

Jessica Garson
A tutorial on building local agent using LangGraph, LLaMA3 and Elasticsearch vector store from scratch
Elasticsearch Labs

A tutorial on building local agent using LangGraph, LLaMA3 and Elasticsearch vector store from scratch

This article will provide a detailed tutorial on implementing a local, reliable agent using LangGraph, combining concepts from Adaptive RAG, Corrective RAG, and Self-RAG papers, and integrating Langchain, Elasticsearch Vector Store, Tavily AI for web search, and LLaMA3 via Ollama.

Pratik Rana
Looking back: Elastic's vector search improvements in Elasticsearch & Lucene
Elasticsearch Labs

Looking back: Elastic's vector search improvements in Elasticsearch & Lucene

Looking back at Elastic's vector search innovations in Elasticsearch and Lucene.

Kathleen DeRusso
Vector embeddings made simple with the Elasticsearch-DSL client for Python
Elasticsearch Labs

Vector embeddings made simple with the Elasticsearch-DSL client for Python

Learn how to ingest and search dense vectors in Python using the Elasticsearch-DSL client.

Miguel Grinberg
Advanced RAG techniques part 2: Querying and testing
Elasticsearch Labs

Advanced RAG techniques part 2: Querying and testing

Discussing and implementing techniques which may increase RAG performance. Part 2 of 2, focusing on querying and testing an advanced RAG pipeline.

Han Xiang Choong
Advanced RAG techniques part 1: Data processing
Elasticsearch Labs

Advanced RAG techniques part 1: Data processing

Discussing and implementing techniques which may increase RAG performance. Part 1 of 2, focusing on the data processing and ingestion component of an advanced RAG pipeline.

Han Xiang Choong
Phi-3 small models, Elastic & RAG: Creating a smart ordering system
Elasticsearch Labs

Phi-3 small models, Elastic & RAG: Creating a smart ordering system

Deploying Phi-3 models on Azure AI Studio and using them with Elastic Open Inference Service to create a RAG application.

Gustavo Llermaly
Building multilingual RAG with Elastic and Mistral
Elasticsearch Labs

Building multilingual RAG with Elastic and Mistral

Building a multilingual RAG application using Elastic and Mixtral 8x22B model

Gustavo Llermaly
Mistral AI embedding models now available via Elasticsearch Open Inference API
Elasticsearch Labs

Mistral AI embedding models now available via Elasticsearch Open Inference API

Learn more about how to use Mistral embeddings with Elastic built search experiences!

Mark Hoy
The sparse vector query: Searching sparse vectors with inference or precomputed query vectors
Elasticsearch Labs

The sparse vector query: Searching sparse vectors with inference or precomputed query vectors

Learn about the Elasticsearch sparse vector query, how it works, and how to effectively use it.

Kathleen DeRusso