Build a Multimodal GenAI App with LangChain and Gemini LLMs

In this 90 minute hands-on workshop, we'll learn how to build a multimodal GenAI app that recommends products from scratch. By the end of the workshop, you'll have built a clone of Fashion Buddy, an application that lets people search for apparel recommendations based on an uploaded photo.

We’ll build the app in Python and use RAG (retrieval augmented generation) with LangChain, Google’s Gemini LLM (large language model), and vector search with Astra DB.

LINKS NEEDED:
--Sign up for Astra: https://bit.ly/3V2XThN
--Create Vertex AI account: https://cloud.google.com/vertex-ai?hl=en
--Fashion Buddy GitHub Repo: https://bit.ly/3WJF7wV
--Google Colab: https://bit.ly/3UKcUDF

Session Agenda
Throughout the 90-minute workshop, all attendees will learn:
What is RAG and how does it work with LangChain and vector search?
How to ingest + vectorize data from CSV file into Astra DB
How Google Gemini interprets images
How to use LangChain for ingestion, embedding, and prompt retrieval
How to deploy a user interface with Streamlit to take image uploads and return similar results

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