Nemesys is an ethical cybersecurity tool designed to automate exploitation and post-exploitation tasks using Metasploit. It enhances target attacks, privilege escalation, and system analysis while providing intelligent reporting through cloud-based large language models (LLMs). 🚀📊

🧠 Multimodal Retrieval-Augmented Generation that "weaves" together text and images seamlessly. 🪡

It allows users to upload PDFs and ask questions about the content within these documents.

This repository highlights my learning journey in building Retrieval-Augmented Generation (RAG) pipelines using DeepSeek on Lightning AI, covering document ingestion, retrieval, and integration with generative AI. It showcases fine-tuning, evaluation, and optimization for accurate open-domain QA and knowledge management.

Budget Buddy is a finance chatbot built using Chainlit and the LLaMA language model. It analyzes PDF documents, such as bank statements and budget reports, to provide personalized financial advice and insights. The chatbot is integrated with Hugging Face for model management, offering an interactive way to manage personal finances.

This project uses the CrewAI framework to automate stock analysis, enabling AI agents to collaborate and execute complex tasks efficiently. Example stock: Nvidia. Technologies include Python, CrewAI, Unstructured, PyOWM, Tools, Wikipedia, yFinance, SEC-API, tiktoken, faiss-cpu, python-dotenv, langchain-community, langchain-core, and OpenAI.

CICD Answering-Question Chatbot for RAG (Retrieval-Augmented Generation) using Streamlit

Museo.ai is an AI-powered chatbot designed for efficient and seamless museum ticket booking. Built using HTML for the frontend and Python for the backend, Museo.ai provides an engaging user interface and powerful backend logic to handle booking requests, manage user interactions, and streamline the ticket purchasing process.

A Chat bot for Graphic Era Deemed University using Streamlit.

Efficiently search and retrieve information from PDF documents using a Retrieval-Augmented Generation (RAG) approach. This project leverages DeepSeek-R1 (1.5B) for advanced language understanding, FAISS for high-speed vector search, and Hugging Face’s ecosystem for enhanced NLP capabilities. With an intuitive Streamlit interface and Ollama for mode

Metallum/Metal-Archives scrapers, datasets, analysis and recommendations website

An easy way to understand vector store working and creation.

Research Mate is a web-based application designed to assist researchers, students, and professionals in efficiently processing and extracting insights from research articles and online content. Users can input multiple research URLs, which the app processes and converts into useful information. Powered by OpenAI’s GPT models and LangChain, the app

Pratham bot is a Gemini powered bot for inquiring information about pratham.org