interns

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

A modern, full-featured internship management platform designed to streamline the entire internship lifecycle. Built with Next.js and MongoDB, InternLink provides comprehensive tools for interns, mentors, and administrators to track progress, manage tasks, and foster collaboration, leveraging robust GitLab integration.

Mana Ruchulu is a Telugu-language recipe sharing and discovery platform built using Streamlit. It allows users to:

Create an account and log in securely

Upload recipes with text, images, videos, or audio instructions

View and interact with other users’ recipes

Participate in weekly cooking challenges

Post short-lived “stories” about their cooking experiences

Compete on a leaderboard based on points earned from contributions

The project supports both SQLite and Supabase backends, making it deployable on platforms like Hugging Face Spaces while being scalable for production use.

Its design emphasizes Telugu cultural heritage by supporting native script and traditional dish categorization.

Doc Bot – AI Doctor Assistant is an interactive chatbot that provides doctor-style suggestions based on user-described symptoms. Built with Streamlit for a responsive and user-friendly interface, it integrates with the Dify.ai API to generate natural language responses. This project was developed as part of an internship at Swecha Telangana.

⚠️ Disclaimer: Doc Bot is for educational and informational purposes only and does not provide professional medical advice.

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.

Festival Log – A Cultural Corpus Collection Engine

Festival Log is an open-source, AI-powered Streamlit application designed to document and preserve the rich festival traditions of India. Users can submit cultural information, stories, and personal experiences related to festivals in their local language. The app automatically translates each entry into Telugu using open-source AI models and displays all entries in a collective log. It is optimized for low-bandwidth areas, supports multilingual input, and contributes to building a parallel corpus for Indian language AI research.

This project is part of the Swecha Summer of AI Internship. It includes a compliance-ready open-source AI-powered application with documentation, templates, and VS Code setup.