Search
Run the Chatbot RAG App with Vertex AI - using Google Kubernetes Engine
Follow the step-by-step process of setting up and running the Elastic Chatbot RAG example app with Google Cloud Vertex AI. This tour demonstrates how to use Google Cloud Shell Editor to configure and deploy the app to Google Kubernetes Engine (GKE).
Explore similar demos

Search
Elasticsearch Vector Database - Python & PDF in S3, Claude Code (with AWS resource creation steps)
Walk through all the steps required to create a Vector Database, how to create an Amazon S3 bucket as a place to privately store original document source files, and how to use Python code to index a PDF document from the S3 bucket into a Vector Database index. Then we'll create an Elastic workflow and MCP tool that can be queried by Claude Code to give it custom context.

Search
Elasticsearch Vector Database - Python & PDF in S3, Claude Code
Walk through the steps required to create a Vector Database and how to use Python code to index a PDF document from an Amazon S3 bucket into a Vector Database index. Then we'll create an Elastic workflow and MCP tool that can be queried by Claude Code to give it custom context.

Search
Elasticsearch Vector Database - Getting Started
Use Elastic Serverless to create an Elasticsearch Vector Database project. No infrastructure to manage. We add data, generate embeddings, and get started fast with code samples you can run in the Elastic Cloud console.