Evaluating agentic search in OpenSearch by Josh Palis

Evaluating agentic search in OpenSearch

This article details the evaluation of OpenSearch's agentic search capabilities, which uses LLMs to enable natural language interaction with data. Testing focused on two key areas: **search relevance** (how well relevant documents are ranked) and **execution accuracy** (correctness of the generated search queries). Results were measured using standard benchmarks like BEIR and BRIGHT, comparing traditional search methods to agentic search variants with different prompting strategies tailored to leverage the strengths of lexical and neural retrieval techniques. Read more...

Traffic
This article had been accessed 94 times so far
Recent posts from this blog
  1. Online index migration and shard scaling in OpenSearch with the AOSC plugin | Arpit Singla
  2. From Search to Search & Apache Lucene: Growing the heart of OpenSearchCon | Kris Freedain
  3. Introducing memory retention for agentic memory in OpenSearch | Erfan Ballew
  4. Building open-source observability together: The OpenSearch Observability TAG turns one | Dotan Horovits
  5. The real cost of your observability stack | Shenoy Pratik Gurudatt