Streamlit

MindMate is an open-source AI-powered assistant designed to support mental wellness through empathetic and non-judgmental conversations. Built on Hugging Face Chat Assistants with meta-llama/Llama-3-70B-Instruct as the base model, it provides mindfulness suggestions, stress management tips, and gentle motivational prompts. The goal of MindMate is to create a safe, conversational space where users can find support for stress, anxiety, and emotional challenges, while maintaining privacy and open-source transparency.

BakBak-Bot

BakBak-Bot is an advanced conversational AI assistant built for linguistic research, machine learning training, and digital archiving purposes. The bot leverages natural language processing (NLP) to understand and respond to user queries in multiple languages, making it an ideal tool for researchers, educators, and developers working on language technologies.

Key Features Multi-language Support: Communicate in various languages Intelligent Conversations: Context-aware responses using NLP Research-Oriented: Designed for linguistic analysis and data collection Digital Archiving: Store and retrieve conversation data efficiently Extensible Architecture: Easy to customize and extend functionality

A stylish Python + Streamlit chatbot with gradient avatars, multiple moods (Friendly, Formal, Sassy), and basic Q&A support. Perfect for beginners to explore interactive AI chat UIs.

Telugu Farmer Assistant is a free, AI-powered platform for farmers in Telangana and Andhra Pradesh. It provides crop disease diagnosis, soil-based crop planning, and real-time weather updates — all in Telugu language, with an offline-first design for accessibility.

AI/ML-based tool that predicts the likelihood of diabetes using medical parameters such as glucose, BMI, age, and blood pressure.

An open-source AI assistant designed by Nandini Golla using Hugging Face. ShaktiAI helps girls and students by providing friendly guidance, motivation, and emotional support through natural conversation.

Chitra Vani is an AI-driven platform for generating and managing images and media content using intuitive interfaces and automated tools.

AI-powered platform for collecting and analyzing multilingual cultural narratives from global communities, built with Streamlit and Python.

“Mana Ruchulu is a Telugu recipe assistant web app that helps users search, view, and explore traditional recipes.”

An AI-powered assistant designed for medical camps that streamlines patient appointment booking and schedule management while simultaneously preserving Telugu culture and heritage. Built with Streamlit frontend, FastAPI backend, and Gemini API, the app enables healthcare efficiency and cultural data collection, creating a digital archive of proverbs, traditions, and stories.

A family recipe sharing app built with Python for managing and sharing recipes across family members.

MitraBot – Student & Community Corpus Assistant. Helps students manage timetables, exams, notes, and community contributions (proverbs, recipes, stories).

An open-source, AI-powered application for preserving and sharing Telugu proverbs and their meanings. Built with Streamlit, it allows users to crowdsource proverbs, view a public gallery of sayings, and uses an AI model for automated classification of proverbs by theme.

A community-driven Streamlit application for collecting a corpus of Telugu cultural data, with a focus on food and culinary heritage.

BharatVivid deployment project for managing configurations, CI/CD pipelines, and automated deployments. Ensures smooth integration, testing, and release management within the Swecha ecosystem.

Hyderabad Food AI Assistant The Hyderabad Food AI Assistant is an intelligent and interactive tool designed to help users discover and get information about food in Hyderabad. It serves as a conversational assistant for exploring the city's diverse culinary landscape, providing details on restaurants, specific dishes, ratings, prices, and more.

The assistant is built with a hybrid search architecture to ensure both speed and flexibility. It first attempts to answer a user's query by searching a structured CSV file (hyderabad_menu_100.csv). This approach is highly efficient for specific, data-driven questions. If the structured search does not yield any results, the system intelligently falls back to a large language model (Flan-T5) to provide a more general, conversational response.

The application is built using the Streamlit framework, providing a clean and easy-to-use web interface for users to interact with the assistant. The core logic is encapsulated within the

FoodAssistant class, which manages the seamless transition between the CSV-based search and the LLM fallback. This architecture ensures that the assistant is always able to provide a helpful response, whether the information is contained in its local data or requires broader AI knowledge.

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

A cryptocurrency price prediction system using LSTM neural networks. Groups coins by market dynamics and forecasts future prices for investors and traders.

SwechaBot: A conversational AI chatbot built with Streamlit, Hugging Face Transformers, and Torch

TailorMyCV: An AI-powered resume and cover letter generator that helps job seekers beat ATS filters, get shortlisted, and showcase their true skills.