Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he created and worked on the ML Platform, and previously as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence.
He is a founding member of the MLOps.community Berlin group, where he organizes Meetups and hackathons. He enjoys dancing and surfing.
In this session, we'll show how to build an advanced Agentic Retrieval-Augmented Generation (RAG) system using entirely open-source technologies. RAG has been the cool kid for a while now, but there is a new cool kid in the bloc, Agentic RAG! This makes it possible to empower RAG with automated decision capabilities.
We will talk about the different strategies to build an Agentic RAG system using Langchain, Ollama and Milvus. You will see how your RAG system can browse the internet, correct itself by adding self-reflection or self-grading on retrieved documents, and many more.
The talk will include a live demo, showcasing the end-to-end workflow and performance of the Agentic RAG system. Whether you're a seasoned developer or new to the field, this session will provide valuable insights into building sophisticated RAG systems using open-source technologies.
Searching for speaker images...