Generative AI
Using Eland on Elasticsearch Serverless
Learn how to use Eland on Elasticsearch Serverless
Vertex AI integration with Elasticsearch open inference API brings reranking to your RAG applications
Google Cloud customers can use Vertex AI embeddings and reranking models with Elasticsearch and take advantage of Vertex AI’s fully-managed, unified AI development platform for building generative AI apps.
Adding AI summaries to your site with Elastic
How to add an AI summary box along with the search results to enrich your search experience.
LangChain and Elasticsearch accelerate time to build AI retrieval agents
Elasticsearch and LangChain collaborate on a new retrieval agent template for LangGraph for agentic apps
Understanding BSI IT Grundschutz: A recipe for GenAI powered search on your (private) PDF treasure
An easy approach to create embeddings for and apply semantic GenAI powered search (RAG) to documents as part of the BSI IT Grundschutz using Elastic's new semantic_text field type and the Playground in Elastic.
Unlocking multilingual insights: translating datasets with Python, LangChain, and Vector Database
Learn how to translate a dataset from one language to another and use Elastic's vector database capabilities to gain more insights.
A tutorial on building local agent using LangGraph, LLaMA3 and Elasticsearch vector store from scratch
This article will provide a detailed tutorial on implementing a local, reliable agent using LangGraph, combining concepts from Adaptive RAG, Corrective RAG, and Self-RAG papers, and integrating Langchain, Elasticsearch Vector Store, Tavily AI for web search, and LLaMA3 via Ollama.
Elasticsearch open inference API adds support for Anthropic’s Claude
Interact with Anthropic's Claude 3.5 Sonnet and other models to generate content and perform question & answering.
ChatGPT and Elasticsearch revisited: The RAG really tied the app together
Learn how to create a chatbot using ChatGPT and Elasticsearch, utilizing all of the newest RAG features.
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.