QuadTree Model for generating random road network

Determination of quadrants based on angle, coordinates and others

On-device Retrieval-Augmented Generation using Qdrant Edge, Qwen3 embeddings, and Gemma4.

This project is a Retrieval-Augmented Generation (RAG) orchestrator that routes user queries to the correct knowledge source before generating an answer. Instead of putting every document and dataset into one vector database, it keeps separate domain-specific vector stores and uses an intent router to decide which retrieval path should answer the q

MCP server for semantic code search using Qdrant vector embeddings

Run retrieval-augmented generation locally using Qdrant Edge, Qwen3 embeddings, and Gemma4 models.