agentg2v

An AI-assisted pipeline that converts RDF Turtle (.ttl) knowledge graphs into a ChromaDB vector database — for AI applications such as RAG and semantic search.

Status: early / pre-alpha. This is the initial project scaffold; the graph-to-vector pipeline described in goal.md hasn't been built yet.

Why

Organizations have knowledge stored in TTL/RDF format, but modern AI applications need vector databases. Traditional graph data migration moves the data but loses the semantic meaning — entity information, relationship context, and search capability. agentg2v aims to transform a TTL knowledge graph into an AI-ready vector database while preserving all of that.

Install

uv add agentg2v
pip install agentg2v

Usage

agentg2v about
agentg2v --version

Development

This project uses uv for dependency management.

uv sync --extra dev    # install package + dev deps into .venv
uv run pytest -q       # run tests
uv run agentg2v about  # run the CLI