ML Web App with Streamlit
A simple web application built with Streamlit that demonstrates how to serve a Machine Learning model in a user-friendly interface. Features Upload input data (CSV or manual entry) Run predictions using a pre-trained ML model Display results in an interactive UI Basic data visualization (charts & tables) Easy to deploy locally or on cloud platforms
Gemma3 Local Chat — FastAPI & Ollama Portfolio App
A lightning-fast local AI chat app using FastAPI, Python, and Ollama running Google Gemma3—streaming responses, ready for your portfolio, side projects, or prototypes! Features Local LLM: Runs Google Gemma3 (gemma3:1b, 4b, etc.) on your own hardware using Ollama. FastAPI backend: Optimized API with streaming responses for instant token display. Zero-JS frontend: Minimal HTML/JS for chat and live model replies—no […]
RAG Portfolio Project
A state-of-the-art Retrieval-Augmented Generation (RAG) system leveraging modern generative AI and vector search technologies. This project demonstrates how to build a production-grade system that enables advanced question answering, document search, and contextual generation on your own infrastructure—private, scalable, and fast. Project Overview This project showcases how to combine large language models (LLMs), local vector databases, […]