Local Knowledge Graph

Ask a local model a question, watch it reason step by step, and see the steps drawn as a graph where the edges are how similar the steps are to each other.

The run starts by breaking the question into angles worth checking, then works through them — about eight steps, each with a named job rather than a quota to fill. Any arithmetic a step relies on is handed over as an expression and evaluated exactly, in fractions, by mpeqs. Those sums are shown above the graph: they are the one part of a run the model did not decide, and you can check 20-13.5 = 6.5 at a glance in a way you cannot check a paragraph of reasoning.

Everything runs on your machine. Nothing is uploaded anywhere.

Run it

pip install mpe-lkg
mpe-lkg

Then open http://localhost:5100.

It needs a local model, which it reaches through Ollama. You do not need to work that out from here — start it and it will tell you what it found, what is missing, and the one command that fixes it. mpe-lkg doctor reports the same thing without starting the server, and exits non-zero, so it works in a script.

Python 3.10 or newer. The wheel is py3-none-any, so nothing is compiled and the same artefact serves Linux, macOS and Windows — all three tested on every push.

git clone https://github.com/punnerud/Local_Knowledge_Graph
cd Local_Knowledge_Graph
python3 -m venv .venv && .venv/bin/pip install -e .
.venv/bin/mpe-lkg

from mpe_lkg import create_app, health

print(health())
create_app().run(port=5100)

More

Licence

The mpedb License 1.0 — the same licence as mpedb and MPEqs, byte for byte.

Free of charge for every person and every organization, with one exception: a group whose revenue or valuation exceeds five billion dollars owes a one-time fee of seven US cents per device. Not an OSI-approved licence.

_{Published to PyPI as mpe-lkg — Morten Punnerud-Engelstad Local Knowledge Graph.}