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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
GenAI for Customer Support — Part 3: Designing a chat interface for chatbots... for humans
Elasticsearch Labs

GenAI for Customer Support — Part 3: Designing a chat interface for chatbots... for humans

This series gives you an inside look at how we’re using generative AI in customer support. Join us as we share our journey in designing a GenAI chatbot interface.

Ian Moersen
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
Protecting Sensitive and PII information in RAG with Elasticsearch and LlamaIndex
Elasticsearch Labs

Protecting Sensitive and PII information in RAG with Elasticsearch and LlamaIndex

How to protect sensitive and PII data in a RAG application with Elasticsearch and LlamaIndex.

Srikanth Manvi
GenAI for Customer Support — Part 2: Building a Knowledge Library
Elasticsearch Labs

GenAI for Customer Support — Part 2: Building a Knowledge Library

This series gives you an inside look at how we're using generative AI in customer support. Join us as we share our journey in real-time!

Cory Mangini
Build AI conversational search for your customer success application with Elasticsearch and OpenAI
Elasticsearch Labs

Build AI conversational search for your customer success application with Elasticsearch and OpenAI

Learn how to build an AI conversational search for customer success applications using Elasticsearch and OpenAI.

Lionel Palacin
Build a RAG application with Elasticsearch's semantic_text and Amazon Bedrock
Elasticsearch Labs

Build a RAG application with Elasticsearch's semantic_text and Amazon Bedrock

Learn how to build a RAG application using Elasticsearch's semantic_text mapping type and Amazon Bedrock without leaving Elastic.

Gustavo Llermaly
Elasticsearch open inference API adds Amazon Bedrock support
Elasticsearch Labs

Elasticsearch open inference API adds Amazon Bedrock support

Elasticsearch open inference API added Amazon Bedrock support. Here's how to use Amazon Bedrock models via Elasticsearch's open inference API.

Mark Hoy

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