A repository for demonstrating GitHub Copilot Agents

A tool for exploring relational databases using a large language model

This project explores running modern GenAI workloads directly on mobile devices (iOS & Android) — including LLM inference, vector database search, and RAG — as a scalable alternative to centralized AI servers.

This repository explores Generative AI (GenAI) techniques for text processing, including chunking, embeddings, retrieval-augmented generation (RAG), semantic search, and text classification. It provides, optimizations, and integrations with LLMs, vector databases, and NLP models to enhance AI-driven text applications.

Learning journey with Vector Databases for GenAI RAG applications, exploring Chroma, Pinecone, and Weaviate for efficient retrieval, indexing, and querying in AI-driven systems.

🧠 genai-rag-playground A personal learning lab for experimenting with Generative AI, RAG (Retrieval-Augmented Generation), and Streamlit. This repository contains multiple mini-projects and prototypes that explore how to build intelligent applications using Large Language Models (LLMs), vector databases, document retrieval, and modern UIs.

A collection of hands-on LLM engineering projects exploring RAG, fine-tuning, prompt design, vector databases, and GenAI application development

Text-to-SQL Explorer – A modern GenAI agent built with LangGraph, Gemini, and Streamlit that turns natural language questions into safe SQL queries across SQLite, PostgreSQL, and MySQL database

A hands-on LangChain GenAI project exploring vector database integration using ChromaDB for efficient document retrieval and semantic search. Includes PDF loading, chunking with text splitters, embedding, and storage in Chroma vector DB.

Interactive Python toolkit that converts plain English queries into SQLite commands using Google GenAI, executes them on an employee database, and returns results as pandas DataFrames. Perfect for non-technical users to explore data effortlessly.