06-11, 10:00–10:40 (Europe/Berlin), Palais Atelier
This talk introduces OpenSearch's Flow Framework and RAG (Retrieval-Augmented Generation) Tool, enabling developers to create AI-augmented agent, queries, and ingestion flows, integrate ML models, and streamline app development through a no-code/low-code builder
This talk introduces OpenSearch's Flow Framework and RAG (Retrieval-Augmented Generation) Tool, enabling developers to create AI-augmented agent, queries, and ingestion flows, integrate ML models, and streamline app development through a no-code/low-code builder. The Flow Framework offers a template for composing AI-augmented flows and integrating ML models. The RAG Tool combines large language models with relevant data from your indexes, enabling question-answering that truly understands and reasons over your proprietary data. Attendees will gain insights into building chatbots, question-and-answer search systems, and other AI-driven applications by leveraging the capabilities of OpenSearch's Flow Framework and RAG Tool.
This session is sponsored by OpenSearch
Mingshi Liu is a Machine Learning Engineer / Software Development Engineer at AWS working on OpenSearch, mainly focusing on OpenSearch core and ML Commons plugin which provides machine learning (ML) features in OpenSearch.
is a Software Engineer at AWS, focusing on OpenSearch, OpenSearch plugins, and Generative AI applications. He is a maintainer of OpenSearch core, Anomaly Detection, and Flow Framework, as well as an active contributor to various Open Source projects.