Join us for a comprehensive two-hour workshop designed to guide participants through the development of a custom research paper engine using Google Gemini, based on the Retrieval Augmented Generation (RAG) framework. This session will begin with a foundational understanding of RAG and an introduction to the Gemini ecosystem. Participants will learn how to set up Gemini API for local projects and build a functional application capable of handling complex queries.

Workshop Schedule

Introduction to the Workshop

Overview of the session's objectives and key outcomes.

Exploring Gemini and AI Studio

Introduction to Gemini's capabilities followed by a demonstration of AI Studio.

Fundamentals of Retrieval Augmented Generation (RAG)

A detailed discussion on how RAG works and its importance in modern AI applications.

Hands-On Setup: Colab and API Key Configuration

Participants will set up their environment in Google Colab and configure their API keys.

Creating a Vector Database for Document Ingestion

Step-by-step guidance on setting up the database necessary for RAG's retrieval component.

Developing the Retrieval and Generation Pipeline

Implementation of the core pipeline that retrieves and generates responses based on user queries.

Building the Research Paper Engine Application

A final activity where participants will build an application that queries retrieves, and synthesizes information from research papers.

System and Software Requirements

Hardware: A laptop with stable internet access.

Software and Accounts:

Sign up for Google Colab at Google Colab to avoid local dependency issues.

Google Cloud credits will be provided during the workshop for API usage.

Create an account on Google AI Studio to access necessary tools and resources.