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LLM Application

🚑 MedicAssist – Tactical Field Medic Assistant

MedicAssist is an offline, CPU-first Progressive Web App (PWA) that transforms unstructured medical audio or text into structured FHIR R4 JSON. Designed for first responders, disaster relief teams, and combat medics, it enables fast and standardized patient documentation without internet connectivity.

Using Whisper.cpp for offline speech-to-text and Phi-3 Mini with llama.cpp for clinical information extraction, MedicAssist generates valid FHIR R4 Bundles containing patient details, injuries, treatments, observations, and triage information. All processing runs locally on the CPU, ensuring privacy, reliability, and uninterrupted operation in remote or emergency environments.

Key Features 🎤 Offline speech-to-text with Whisper.cpp 🤖 CPU-only AI extraction using Phi-3 Mini 📋 Converts unstructured input into FHIR R4 JSON 🌐 Progressive Web App with full offline support 💾 Local storage using IndexedDB 📤 Export FHIR JSON for later synchronization 🔒 Privacy-first with no cloud or internet dependency

MedicAssist demonstrates how offline AI can convert unstructured medical data into standardized healthcare records, making it ideal for emergency response and disaster management.

Smart Cab Finder is an AI-powered ride comparison platform that helps users compare fares, estimated arrival times, and ride options across multiple cab providers. The application includes an intelligent AI assistant for ride recommendations, supports Bring Your Own Key (BYOK) integrations, and is designed to support local AI inference through Ollama. To improve accessibility, the platform provides multilingual support in English, Hindi, and Telugu. Built using Python and Flask, the project follows secure development practices with automated testing, CI/CD pipelines, security scanning, and compliance-driven documentation.

F2P Solver extracts mathematical formulas from PDF research papers and converts them into interactive Python simulations — entirely offline, on CPU. Upload a paper, and for every formula you get a callable Python function plus a live chart with sliders for each variable: drag a slider and the curve updates instantly, with no further AI calls. Built with Streamlit, pymupdf, ollama (Qwen2.5-7B), numpy, and Plotly. Runs on any Linux/macOS machine with a single command: ./run.sh.

Offline Resume Parser is an offline-first, CPU-optimized AI application that converts unstructured PDF resumes into structured, machine-readable candidate profiles entirely on the user's device. The platform performs document extraction, AI-powered information extraction, validation, and local storage without relying on cloud services or internet connectivity.

Built with React, Vite, FastAPI, SQLite, PyMuPDF, Pydantic, and a locally hosted Small Language Model (SLM) via llama.cpp, the application provides a secure, privacy-preserving solution for recruiters and organizations handling sensitive hiring data. Its modern, responsive interface enables users to upload resumes, view extracted candidate information, browse resume history, and export structured JSON, all while running efficiently on standard CPU hardware.

A fully local Retrieval-Augmented Generation (RAG) chatbot built using Streamlit, Ollama, ChromaDB, and open-source LLMs like Qwen and Llama.

AI-powered chatbot application with React frontend and Node.js backend for interactive conversations

Project Description An AI-powered Healthcare LLM designed to assist visually impaired (blind) individuals. The system provides accessible medical guidance through natural language processing, voice interaction, and context-aware support. This project aims to enhance healthcare accessibility, improve independence, and empower blind users by bridging the gap between medical knowledge and inclusivity.

A Streamlit-based music library application that allows users to browse, search, and stream audio tracks according to thier mood and also it is an otp sign in thing where it is integrated with swecha apis. Built with Python and Streamlit, designed for fast deployment.

Ruchulu Lens AI

Ruchulu Lens AI is a cross-platform AI-powered application that celebrates India's regional food diversity. The app offers:

Regional Food Explorer – Shows local dishes based on user location, revealing region-specific ingredients, cooking styles, and preparation. Lens Feature (Food Recognition) – Users can upload or capture an image of a dish, and the AI will it and provide ingredients, recipe steps, and cultural context. AI Culinary Assistant – Interactive assistant to answer cooking-related questions, suggest dietary plans, offer substitutions, and guide users through cooking.

GramaSakshi is an AI assistant built to bridge the digital gap for villagers and provide smart assistance in healthcare. It empowers people with easy access to information, task management, and medical support tools.

Meet Chef Ahmed, your friendly AI guide to Hyderabadi cuisine! 👨‍🍳 Get easy, step-by-step recipes in Hinglish. An open-source project with a focus on Indic languages.

OCU-AI is a smart healthcare assistant that combines Natural Language Processing (NLP) and Computer Vision to assist users in understanding medical conditions and detecting eye diseases from retinal images.

This web-based application has two core components:

Medical Q&A Chatbot

Uses Retrieval-Augmented Generation (RAG) with LangChain, Pinecone, and Phi-3 LLM.

Answers user queries using embedded medical knowledge extracted from PDF files (like textbooks or research).

Designed to explain medical terms in simple, non-technical language.

Always includes a disclaimer to consult a qualified medical professional.

Eye Disease Detection Model

Allows users to upload retina images.

Predicts diseases like:

Cataract

Glaucoma

Diabetic Retinopathy

Normal (Healthy)

Uses a Keras CNN model trained on retina datasets.

After prediction, the chatbot explains the condition using natural language.

This project bridges AI-powered document retrieval, medical imaging, and LLM-based explanation, offering a foundation for real-world smart health applications.

A community hub for Telugu language enthusiasts to discuss phrases, share stories, and solve riddles, with AI assistance.