Integrations
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 environments. GPU support is available.
ES|QL queries to TypeScript types
Explore how to use the JavaScript Elasticsearch 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 natural language processing capabilities. NVIDIA NIM offers features such as in-flight batching, which not only speeds up request processing but also integrates seamlessly with Elasticsearch to boost data indexing and search functionalities.
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.
Elasticsearch open inference API adds Azure AI Studio support
Elasticsearch open inference API adds support for embeddings generated from models hosted on Azure AI Studio and completion tasks from large language models such as Meta-Llama-3-8B-Instruct."
Elasticsearch open inference API adds support for Azure OpenAI chat completions
Elasticsearch open inference API adds support for Azure Open AI chat completions, providing full developer access to the Azure AI ecosystem
Elasticsearch open inference API adds support for Azure OpenAI embeddings
Elasticsearch open inference API adds support for Azure OpenAI embeddings to be stored in the world's most downloaded vector database.