huggingface

AI Chat Assistant is a conversational platform built using Streamlit, designed to integrate multiple Large Language Models (LLMs) such as Ollama (local hosting), OpenAI, and Google Gemini. The system provides a flexible interface for seamless interaction across different models while supporting customization through fine-tuned domain-specific datasets. Its architecture emphasizes scalability, multilingual support (including Indic languages), and accessibility, making it suitable for both personal productivity and enterprise use.

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.

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.

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

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

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

Desi Proverbs & Local Lore Collector is a lightweight, mobile-friendly Streamlit app to collect Indian proverbs, folk sayings, and cultural facts across languages. It auto-detects language, stores structured metadata (language, region, tags), and exports a clean corpus for research and cultural preservation. Built for low-bandwidth users, deployable on Hugging Face Spaces, and designed with an offline-first approach.

My-Culture-My-Voice is a cultural AI project using Hugging Face and NLP to preserve Telugu traditions, language, and knowledge.

A simple chatbot built using Hugging Face and Streamlit that answers user queries about Indian temples. The app provides cultural, historical, and architectural insights in a conversational format.

KathaVichar is an interactive storytelling platform that allows users to create, submit, and explore short stories in multiple languages. Users can input stories via text or voice files, and optionally add images to enrich their narratives. The app collects user-generated content to help improve AI-driven story analysis and recommendation features. It is mobile-friendly, easy to navigate, and encourages creativity by guiding users step-by-step through the story submission process

Chatbots build with Hugging face and streamlit.

"Tejaswi" is an open-source AI assistant that provides high-quality, accurate responses in nine major Indian languages. It solves the common problem of garbled text in Indic scripts by using a unique architecture: a powerful English-language model (Mistral-7B) for reasoning, combined with a real-time translation layer. This ensures users can interact fluently in their native language and receive reliable, coherent answers.

Janavaani is a Streamlit-based portal where people can give voice complaints in their language, with location and media support, and admins can track and resolve them.

An AI powered career assistant to help in resume building and interview preparation.