Overview

Elastic Cloud

Docker

Install Elasticsearch

Welcome

Requirements

Project Setup

Python Client Setup

Create an Index

Search Basics

Pagination

Filters

Faceted Search

Full-Text Search

Embeddings Intro

Generating Embeddings

Storing Embeddings

k-Nearest Neighbor Search

Hybrid Search

Vector Search

ELSER Model

Semantic Queries

Semantic Search

Conclusion

Search Tutorial

Python Back End

React Front End

Getting Started

Ingest

Chatbot Endpoint

Retrieval Phase

LLM Prompt

Generation Phase

Chat History

Implementation

Chatbot Tutorial

Examples

Answer questions with your private data with Generative AI, Langchain and Elasticsearch

Chatbot RAG Reference App

Small sample applications showing the use of OpenAI embeddings in Elasticsearch.

OpenAI embeddings in Elasticsearch

A sample application that allows you to compare results ranking between the Elastic Learned Spare Encoder model and BM25.

Relevance Workbench

Using the OpenAI service to perform semantic search with the inference API.

Semantic search using the OpenAI service of the inference API

Use eland to load a pre-trained embedding model from hugging face into Elasticsearch

Load Embedding Model into Elasticsearch

using multilingual-e5-base to search in multiple languages

Load and search with Multilingual Model

Using ELSER to perform semantic search on documents

Semantic Search with ELSER

Learn to split fictional workplace documents into passages and transform these passages into embeddings in Elasticsearch.

Question Answering with Langchain and OpenAI

Learn to split fictional workplace documents into passages, transform these passages into embeddings in Elasticsearch and integrate Langchain Bedrock LLM.

Integrate langchain Bedrock LLM and Elasticsearch

Using the Cohere service to perform semantic search with the inference API.

Semantic search using the Cohere service of the inference API

Learn how to use langchain to build a chatbot with Elasticsearch

Chatbot with Langchain and Elasticsearch

Langchain Question Answering with Self Query Retriever

Learn how to integrate traditional text-based search with semantic search