Gemini-Powered Multimodal AI Assistant

Inspiration

We were inspired by the challenge of making AI more useful for students, developers, and researchers who work with mixed content like PDFs, images, and text. Many tools only handle text, so we wanted to build an assistant that could truly “see, read, and reason” using Google Gemini 3’s multimodal capabilities.

What it does

Gemini-Powered Multimodal AI Assistant allows users to:

Upload PDFs, images, and text
Ask questions in natural language
Get clear summaries, explanations, and insights
Interact with AI in a chat-style interface
The system understands different types of input and responds in a structured, human-friendly way.

How we built it

We built the frontend and backend using Lovable AI to rapidly generate a working web application. We integrated the Google Gemini 3 API as the core intelligence layer. The app sends user inputs (files, images, or text) to Gemini, processes the response, and displays it in a clean UI for easy interaction.

Challenges we ran into

Connecting Gemini 3 API correctly with the web app
Handling large PDF files and extracting useful text
Designing a simple but professional user interface
Ensuring fast response times from the AI
Debugging file upload and processing issues

Accomplishments that we're proud of

Successfully integrating Gemini 3 into a live web app
Building a fully functional multimodal system
Creating a clean and intuitive UI using Lovable AI
Allowing users to work with multiple file formats
Delivering a working demo within the hackathon timeline

What we learned

We learned how to work with Gemini 3’s multimodal capabilities, how AI applications are structured end-to-end, how to handle file uploads, and how to build and deploy an AI-powered web application using Lovable AI.