06-14, 09:00–10:30 (Europe/London), Minories
How do you build chatbots that answer questions using your organisation's data? The answer is Retrieval Augmented Generation (RAG). In this session you'll be introduced to RAG and build a simple RAG powered chatbot in Python.
Until very recently, if an organisation wanted a bespoke chatbot application, they had to spend millions of pounds and fund highly specialised teams, often training and hosting their own sophisticated AI models. Retrieval Augmented Generation (RAG) allows organisations of any size, and developers who haven't got specialised AI skills, to build capable chatbots, that can answer questions based on data that you control.
This session is designed to get you started on you RAG journey. You'll be introduced to RAG and then taken though a guided exercise to build a very simple RAG powered chatbot. We've designed this session to be suitable for participants with basic Python skills, but also be a good overview for those who consider themselves capable Python developers, but haven't tried out RAG.
Participants can get ahead and set their machines up by downloading:
https://github.com/Personify-AI/rag_short_intro
Then reading the README.md.
No previous knowledge expected
Dan is the Founder of Personify-AI, a startup specialising in building Chatbots for ecommerce.
Dan has spent 30 years working in technology in a varied career that has spanned development, management, consultancy and training.