Unified AI Multi-modal Chatbot

In today’s digital age, we are surrounded by a massive amount of information in different formats—documents, images, and videos. However, making sense of all this data in a meaningful way is still a challenge. This project proposes a smart, unified chatbot system that can understand and interact with content from multiple sources using a multi-modal Retrieval-Augmented Generation (RAG) approach powered by Google’s Gemini-1.5 model. The chatbot allows users to upload PDFs, Word documents, CSV files, images containing text, and even YouTube links. It then extracts key information using techniques like OCR and video transcription, and allows users to ask questions directly about the content. What makes this system powerful is its ability to merge different types of inputs and generate accurate, context-aware answers. The entire interface is built using Streamlit, offering an easy and interactive user experience with features like real-time previews, downloadable notes, chat history, and multilingual support.The project reflects the growing need for AI systems that are intelligent, flexible, and capable of understanding information the way humans do—from all angles and in all forms.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-05-05
DOI
https://doi.org/10.30574/wjaets.2025.15.2.0513
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
Controls
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Unified AI Multi-modal Chatbot

M. Sami, P. Chiranjeevi, Nagalaxmi Kalluri, Sai Saket Gurubhagavatula et al.
1 citations
World Journal of Advanced Engineering Technology and Sciences
AI in Service Interactions
2.48
article

Unified AI Multi-modal Chatbot

M. Sami, P. Chiranjeevi, Nagalaxmi Kalluri, Sai Saket Gurubhagavatula, Abhishek Kuncham
article en
1 citations

Abstract

In today’s digital age, we are surrounded by a massive amount of information in different formats—documents, images, and videos. However, making sense of all this data in a meaningful way is still a challenge. This project proposes a smart, unified chatbot system that can understand and interact with content from multiple sources using a multi-modal Retrieval-Augmented Generation (RAG) approach powered by Google’s Gemini-1.5 model. The chatbot allows users to upload PDFs, Word documents, CSV files, images containing text, and even YouTube links. It then extracts key information using techniques like OCR and video transcription, and allows users to ask questions directly about the content. What makes this system powerful is its ability to merge different types of inputs and generate accurate, context-aware answers. The entire interface is built using Streamlit, offering an easy and interactive user experience with features like real-time previews, downloadable notes, chat history, and multilingual support.The project reflects the growing need for AI systems that are intelligent, flexible, and capable of understanding information the way humans do—from all angles and in all forms.

World Journal of Advanced Engineering Technology and SciencesVol. 15(2)
Openalex Percentile: Top 11%
AI in Service Interactions
2.48
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