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Description
🌍 Problem Statement
In today’s information-heavy world, extracting useful insights from long or complex documents like research papers, legal contracts, or internal PDFs is time-consuming and often inefficient. Users need an intuitive way to converse with their documents, ask follow-up questions, and get precise answers — just like chatting with a human expert.
This solution addresses:
Societal needs like making legal and healthcare documents more accessible
Educational needs by enabling students to interact with study materials
Enterprise productivity by simplifying access to internal manuals and policies
🛠 Your Solution
To solve this problem, I have customized an Azure Developer CLI (azd) template for AI chat interfaces. Here's how:
Template Used: ai-chat-app or similar conversational AI base template provided by Azure.
Modifications and Extensions:
Integrated RAG (Retrieval-Augmented Generation) using document embedding and vector stores to enable document-based Q&A.
Added support for PDF/document upload, automatic parsing, chunking, and embedding.
Implemented conversational memory to track chat history and enable follow-up questions with contextual continuity.
Enhanced the UI for seamless file upload and real-time AI chat experience.
Why It Matters:
Allows users to chat with any document in natural language.
Reduces time spent reading and interpreting lengthy documents.
Ensures context-aware conversations that simulate talking to an expert.
This approach is relevant because it combines semantic search, LLMs, and memory in a single user-friendly solution with real-world applications across industries.
🚀 Repository & Demo (if any)
GitHub Repo: (https://github.com/Anjali-d6/Open-ai-chat)
Study Jam: MLSA SPSU
🙌 Call for Upvotes
Imagine asking a document a question — and it answers like an expert! This project transforms static files into dynamic conversations.
🔹 It’s smart – powered by AI and memory.
🔹 It’s useful – for students, professionals, and anyone dealing with documents.
🔹 It’s scalable – fits into customer support, healthcare, legal tech, and more.
If you’ve ever wanted Google-level answers from your own files — this project delivers it.
🗳 Help bring document intelligence to everyone. Vote for this project for the People’s Choice Award!