Generative AI projects and tutorials
I Teaching Assistant is a production-ready, full-stack Generative AI application designed to streamline classroom learning through Retrieval-Augmented Generation (RAG) and automated evaluation
Build a secure, real-time medical report diagnosis app using FastAPI, Streamlit, LangChain, Pinecone, and Groq. Features RAG for accurate insights and RBAC for role management.
Build a role-based medical chatbot using FastAPI, Groq LLaMA 3, Pinecone, and MongoDB Atlas. Features document-grounded RAG with strict RBAC for Doctors, Nurses, and Patients.
Build a Multimodal RAG pipeline using PyMuPDF, Cohere embed-v4.0, ChromaDB, and Gemini 2.5 Flash with LangChain LCEL to query both text and visual diagrams from PDFs.
Automate job role validation between structured XML files and unstructured PDFs using Google Gemini, Pinecone vector search, PyMuPDF, and fuzzy string algorithms (Levenshtein Distance & Ratcliff-Obers
Build a modular, full-stack RAG PDF chatbot from scratch using LangChain, FastAPI, Streamlit, ChromaDB, and Groq (LLaMA 3) with clean frontend-backend separation and sub-second inference.
Build a multilingual AI chatbot using Sarvam AI and Streamlit. Supports Indian languages like Hindi, Gujarati, Bengali, and Kannada with native LLM reasoning and real-time translation.
Build a custom RAG PDF chatbot using LangChain, ChromaDB, and Google Gemini API to perform fast semantic retrieval and generate grounded, context-aware answers.
Build a RAG PDF chatbot using Streamlit, LangChain, FAISS, and Google Gemini API. Extract PDF text, index embeddings in-memory with FAISS, and generate context-grounded answers in a clean web UI