This project implements a Retrieval-Augmented Generation (RAG) system that can handle different types of files. The system uses FastAPI for the backend, Qdrant as a vector database, Streamlit for the frontend interface, and includes monitoring capabilities with Grafana.

A universal Qdrant table frontend based on transformers.js

MCP server for multi-repository code indexing with Qdrant vector search and LSP integration. Provides unified context across frontend, backend, and microservices for AI coding assistants like Claude Code.

AI Cafe Chatbot adalah platform pemesanan menu kafe berbasis web dengan menggunakan Semantic Search (Multilingual-E5-Small) dan Qdrant. Chatbot berjalan lokal via Ollama (Llama 3.2:1B). Backend Drizzle ORM + Better Auth, frontend NextJs + Tailwind v4 + Shadcn/UI, dengan dashboard dapur real-time.

YouTube Chat RAG Bot is a Node.js app that lets you input a YouTube video URL, extracts and embeds the transcript using Google Gemini, stores it in Qdrant, and allows you to chat with the video content using RAG (Retrieval-Augmented Generation). Simple frontend included for easy interaction.

NewsMate is a full-stack AI chatbot that answers news-related queries using a RAG pipeline. It features Xenova embeddings, Qdrant vector search, Gemini API, Redis-based session handling, and a modern React + Tailwind CSS frontend.

🚀 UnchainAI - Assistant IA conversationnel entièrement local avec modèles Ollama. 12 personas spécialisées (Web Designer, Python, Cybersécurité, Cloud). Génération de code, création de sites web, RAG avec Qdrant. Frontend Next.js + Backend FastAPI. Confidentialité totale - vos données restent sur votre machine. Déploiement Docker en un clic.

Math Agent is an agentic Retrieval-Augmented Generation (RAG) system designed to replicate a mathematical professor. It answers math questions with step-by-step solutions, using a knowledge base, web search (MCP), guardrails, and a human-in-the-loop feedback mechanism. The system is built with FastAPI (backend), React (frontend), Qdrant (vector DB)

Chat Application with both frontend in React and backend in FastAPI using Qdrant Vector DB

Enterprise Retrieval-Augmented Generation (RAG) system with Llama 3.2 LLM, Qdrant vector database, and full-stack implementation featuring React frontend and FastAPI backend

A production-ready recommendation system built with PyTorch, Qdrant vector database, FastAPI, and a modern Next.js frontend. Processes 25M+ user-item interactions to deliver sub-100ms personalized recommendations.

An interactive flashcard-based learning platform that allows users to study, create, manage, and generate flashcards using AI. Built with Angular (frontend), FastAPI (Python backend), Qdrant (vector storage), and OpenAI GPT-4 (AI generation).

A full-stack hybrid book recommender system combining collaborative filtering (ALS), content-based similarity (SBERT), and machine learning ranking (CatBoost). Backend: FastAPI • Frontend: Streamlit • Vector DB: Qdrant • Model serving • Cold-start fallback • Book metadata display.

A complete facial recognition application system using InsightFace, optimized for Apple Silicon (ARM64) architecture. This system provides web-based face registration and real-time face recognition capabilities with a modern React frontend, FastAPI backend, and Qdrant vector database.

Test d'une stack IA/RAG auto‑hébergée : microservices Spring Boot (gateway, auth, documents, rag) avec PostgreSQL/Qdrant/Ollama, orchestrés par Docker Compose, et un frontend Angular pour chatter avec un LLM local, gérer documents et profils via JWT.

Frontend for NewsMate, a real-time news chatbot interface built with React, Vite, and Tailwind CSS. Supports session-based chat, markdown-rendered responses, and API integration with a RAG-powered backend using Gemini and Qdrant for intelligent news retrieval and conversation history.

A production-grade, AI-powered personal assistant that answers questions using your uploaded documents (PDFs, Markdown, JSON, etc.) with Retrieval-Augmented Generation (RAG). Built with Golang backend, Next.js frontend, Qdrant vector database, and AWS S3 storage. Fully Dockerized with LocalStack for local testing.

A full-stack RAG application combining a FastAPI/LangChain backend with a sleek Flutter frontend. Integrates Qdrant for vector search, Ollama for local embeddings, and GPT-4o for generation. Fully containerized with Docker Compose, offering a scalable, production-ready architecture for AI-powered document analysis and Q&A.

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Prototype of LLamaindex + Qdrant + NextJS frontend

frontend for obsidian semantic search

frontend for a rag based chatbot made suing n8n, ollama, qdrant

Tax Authority RAG demo — CRAG pipeline with FastAPI, LangGraph, Qdrant, and React frontend

POC project for semantic search using Elasticsearch, Qdrant and Typesense using streamlit as frontend.

RAG platform for educational use at DSV, Stockholm University. Rust/Axum backend, React frontend, Qdrant vector search.

PROYECTO FRONTEND DE PRUEBA - Validar Stack Completo Vamos a crear: API REST con FastAPI + PostgreSQL + Qdrant (RAG) + Ollama.

A full-stack movie recommendation system with a React frontend, Node.js backend, and Qdrant vector database for personalized suggestions.A full-stack movie recommendation system with a React frontend, Node.js backend, and Qdrant vector database for personalized suggestions.

Small AI Search Bar frontend. Connects to VPS that serves QDrant embeddings from LLM for product search on website.