Agentic RAG with LangChain
It appears that 2024 is the year of agentic applications! This means that people and companies are now looking to build LLM and RAG applications connected to tools capable of reasoning, taking action, and observing.
A fully autonomous agent runs in a loop, or a cycle, using a Reasoning-Action approach. The tool with the largest community-building LLM applications is LangChain, and with their release of LangChain v0.1, they also released LangGraph, the engine that powers these autonomous agentic cycles.
In this event, we’ll provide a brief history of Agents before spending time on the details of building what is becoming the industry-standard agentic RAG application, namely, one with access to backup internet searches. Per LangChain's recommended best practices, we’ll use OpenAI Function Calling to build an OpenAI Functions Agent.
Who should attend the event?
LLM practitioners who want to understand how to build agentic RAG applications
Aspiring AI Engineers who want to start building at the open-source edge with LangChain
AI Engineering leaders interested connecting LLMs to RAG apps and other tools simultaneously
Speakers:
Dr. Greg Loughnane is the Co-Founder & CEO of AI Makerspace, where he serves as an instructor for their AI Engineering Bootcamp. Since 2021 he has built and led industry-leading Machine Learning education programs. Previously, he worked as an AI product manager, a university professor teaching AI, an AI consultant and startup advisor, and an ML researcher. He loves trail running and is based in Dayton, Ohio.
Chris Alexiuk is the Co-Founder & CTO at AI Makerspace, where he serves as an instructor for their AI Engineering Bootcamp. Previously, he’s held roles as a Founding Machine Learning Engineer, Data Scientist, and ML curriculum developer and instructor. He’s a YouTube content creator YouTube who’s motto is “Build, build, build!” He loves Dungeons & Dragons and is based in Toronto, Canada.
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