AI-powered healthcare provider validation system using multi-agent architecture with LangGraph, Mistral AI, and vector embeddings for automated NPI verification and trust scoring
Vector Database Manager for VSCode/Cursor
Learnability Backend API
A backend utility service built with NestJS, featuring a 3-layer architecture for API management, worker processes, blockchain interactions, AI capabilities, and game services. Utilizes TypeScript, PostgreSQL, Redis, and Docker for scalability.
A RAG-driven image product search that showcases MERN, Milvus for vector indexing, Transformers, and a local Ollama Gemma LLM. Explore integrated embeddings, store vectors in Milvus, and manipulate queries with advanced language understanding.
A ChatGPT-powered QA system using OpenAI, LangChain, FastAPI, and a vector database. It retrieves answers based on stored data, enhancing responses with relevant source links. The project enables efficient knowledge retrieval, making it ideal for AI-driven chat applications that require accurate and reference-backed responses.
An agentic RAG-powered chatbot that ingests API documentation, answers user queries, validates API calls, and suggests fixes
A microservices architecture comprising a Python gRPC/REST API for managing embeddings in a Milvus vector database and a full-stack Next.js app with MySQL for user and file management, including OAuth and a chat interface.
A command-line tool that ingests documents and generates instant answers to your questions about those documents using ChatGPT, giving you the Sheldon Cooper you never had at your fingertips.
Milvus management GUI
This project uses Milvus and Bert to build a text search system.
This system contains the API server, neural models, and UI client, a neural search engine for the COVID-19 Open Research Dataset (CORD-19) , and is referred to covidex.
Converting chemical formulae to fingerprints and then compared for similarity in Milvus.
This project combines the model provided by Bert and Milvus to realize a question and answer (QA) system.
This project use VGG model to get image embeddings. Then Milvus is used to search the similarity images.
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