Integrations
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.
semantic_text with Amazon Bedrock
Using semantic_text new feature, and AWS Bedrock as inference endpoint service
Elasticsearch open inference API adds Amazon Bedrock support
Elasticsearch open inference API adds support for embeddings generated from models hosted on Amazon Bedrock."
Search complex documents using Unstructured.io and Elasticsearch vector database
Ingest and search complex proprietary documents with Unstructured and Elasticsearch vector database for RAG applications
Building RAG with Llama 3 open-source and Elastic
Build a RAG system with Llama3 open source and Elastic.
LangChain and Elastic collaborate to add vector database and semantic reranking for RAG
Learn how LangChain and Elasticsearch can accelerate your speed of innovation in the LLM and GenAI space.
How to set up LocalAI for GPU-powered text embeddings in air-gapped environments
With LocalAI, you can compute text embeddings in air-gapped systems. GPU support is available. Here's how to set up LocalAI to compute embeddings for your data.
ES|QL queries to TypeScript types with the Elasticsearch JavaScript client
Explore how to use the Elasticsearch JavaScript client and TypeScript support to craft ES|QL queries and handle their results as native JavaScript objects.
Using NVIDIA NIM with Elasticsearch vector store
Explore how NVIDIA NIM enhances applications with NLP capabilities and learn how to integrate NVIDIA NIM with Elasticsearch.
Using Elasticsearch as a vector database for Azure OpenAI On Your Data
Explore how to quickly set up and ingest data into Elasticsearch for use as a vector database with Azure OpenAI On Your Data, enabling you to chat with your private data.