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RAG

StudentAI - AI-powered RAG chatbot for document analysis and question answering using FastAPI, React, Ollama and Retrieval-Augmented Generation (RAG).

Fully offline document Q&A system using PyMuPDF4LLM, Ollama, and llama.cpp. Dual LLM backend with pre-commit quality gates.

A Retrieval-Augmented Generation (RAG) chatbot built with Streamlit, LangChain, FAISS, and sentence-transformers. Upload PDFs and ask questions using Gemini or local Llama.cpp LLMs.

AI-powered PDF Chatbot using Retrieval Augmented Generation (RAG), FAISS, and OpenAI APIs.

EndGame RAGHub is a scalable multimodal Retrieval-Augmented Generation platform supporting document, image, audio, and video understanding using FastAPI, Qdrant, LangGraph, and modern open-source AI infrastructure.

Production-ready RAG chatbot built with Streamlit, LangChain, FAISS, and local LLM support. Features document Q&A, PDF processing, and AGPLv3 compliance.

Local-First Document Q&A with RAG using Ollama — Find-Retrieve-Answer pattern

A Streamlit-based research paper assistant that uses AI (RAG + PyMuPDF4LLM) for document summarization, Q&A, and multimedia analysis with local-first inference via Ollama.

An enterprise-grade offline Medical RAG Assistant running local quantized LLM inference engines. The system features advanced document layout ingestion processing, strict private hardware memory isolation frameworks, and automated software validation pipelines.

A local-first Retrieval-Augmented Generation chatbot for PDF Q&A built with Streamlit, LangChain, ChromaDB, and llama.cpp

CampusGPT is an AI-powered academic assistant that enables intelligent document question answering using Retrieval-Augmented Generation (RAG). Built with Streamlit, LangChain, FAISS, and Gemini/Llama.cpp, it supports semantic search, document summarization, source traceability, and fully offline operation with local GGUF models.

A complete, production-ready local-first Retrieval-Augmented Generation (RAG) assistant for researchers, professors, and students.