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Built an AI-powered Historical Event Analysis Assistant using RAG (Retrieval-Augmented Generation).
The application allows users to ask questions about historical documents and generates answers based on relevant retrieved content rather than relying only on the LLM’s general knowledge.
Built with: Python, LangChain, RAG, Qdrant/FAISS, BM25, Hugging Face embeddings, Groq, and Streamlit.
The project demonstrates document processing, semantic and keyword retrieval, context-based generation, and an interactive Streamlit interface.
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Hi! I’m a college student and an aspiring AI/ML engineer who loves building things with technology and turning ideas into real projects.
I built the Arshi Masale website for a local spice business from Sindhudurg, Maharashtra. This project was special to me because it showed me that even as a student, I can use what I’m learning to create something useful for a real business.
I focused on making it modern, simple, mobile-friendly, and ready for future e-commerce features. This is one of the projects that motivates me to keep learning, building, and eventually turn my passion for AI and technology into a career.
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