vector-database

Search on your images via text or image to image search. Uses OpenAI CLIP embedding and LanceDB

A terminal UI for browsing and inspecting vector databases

ToucanDB is a brand-new micro ML-first database engine 🦜

The notebooks & projects code for Generative for Backend Dev online bootcamp

An advanced AI-powered conversational agent leveraging the Llama 3.2 model and Phidata framework. Features include reasoning, natural language interaction, and tool integration for web searches and calculations. Designed for interactivity with enhanced logging, support for custom tools, and structured outputs.

A RAG implementation on Llama Index using Qdrant vector stores as storage. Take some pdfs, store them in the db, use LLM to inference.

Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.

PTIT's Major Project: Website Programming - This repo contains a chatbot for a clothing store. The chatbot acts as an employee with specific knowledge about clothing consultation, website support, and store information.

PostgreSQL TurboQuant Index for PGVector

Open-source persistent memory infrastructure for LLM applications.🐬

using mulimodal RAG to query texts, images and tables from pdf for QA

Web Vector Storage (WVS) is a lightweight and efficient vector database that stores document vectors in the browser's IndexedDB. It supports perform semantic similarity searches on text documents using vector embeddings. Embedding is enabled through use of OpenAI, Ollama or HuggingFace Transformer embedding models.

A Node.js RESTful server for a Retrieval-Augmented Generation (RAG) system using ChromaDB and Ollama!

A repository of curated use cases, articles, blogs, videos on how companies are using Artificial Intelligence and Machine Learning.

Multi-User Chatbot with Langchain and Pinecone in Next.JS

Persistent semantic memory for AI agents on Raspberry Pi 5 — local Qdrant + MCP, no cloud, ~3s per query

Practical GenAI-Eshop application using Semantic Kernel, multi-agent orchestrations, Mcp tools, A2A Agents, Semantic Search, Aspire and more.

Model Context Protocol (MCP) server implementation for semantic vector search and memory management using TxtAI. This server provides a robust API for storing, retrieving, and managing text-based memories with semantic vector database search capabilities. You can use Claude and Cline AI as well.

The Solidity Smart-Contract Advisor is a cutting-edge tool designed to extend the capabilities of traditional language models in understanding and advising on Solidity smart contracts

🧠 Enterprise AI-Enhanced Development Platform with GraphRAG, LlamaIndex, Multi-Tenant Architecture, and Advanced Security & Compliance. Transform your development workflow with persistent memory, intelligent automation, and 99.9% uptime.