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Multi-Modal RAG Assistant

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December 3, 2025 at 06:10 PM

Project Demo

Submission Details

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name

Priyanshi Shah

College / University Name

Vellore Institute of Technology, Vellore

Project Title

Multi-Modal RAG Assistant

Describe what your project does?

RAG Assistant is a multi-modal AI document agent built with LangChain that enables intelligent search and question-answering across PDFs, Word files, Excel sheets, presentations, and even images/screenshots. It automatically extracts text (with OCR for images), chunks the content, generates embeddings, and stores them in a vector database. When a user asks a question, the agent retrieves the most relevant chunks using LangChain’s RAG pipeline and generates accurate, context-aware answers with GPT-5.1, along with full source attribution. This matters because organizations deal with massive amounts of unstructured data spread across many file formats. Manually searching these documents is slow and error-prone. RAG Assistant provides a fast, flexible, and production-ready solution for document intelligence — enabling research, analysis, data extraction, and knowledge retrieval in seconds.

Hosted Project Link (if any)

https://rag-vector.emergent.host/

artifacts/ supporting material

Is this project your original and proprietary work?

Yes

Does your project include any private, sensitive, or restricted code or content?

No

Do you give us (AI Demos & partners) permission to feature your work on our website and share it with our community (with full credit)?

Yes

Do you consent to us showcasing your name/profile on our social media platforms and YouTube

Yes

Are you open to freelance, internship, or collaborative opportunities based on this project?

Yes, I’m interested

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