groundloop 0.1.0

Trustworthy RAG with geometric memory — grounded, cited, byte-exact, abstaining. GMS-optional.

Beyond Chunk and Pray

Building trustworthy RAG with geometric memory.

Most RAG is "chunk and pray" — split the docs, embed them, retrieve the top-k by similarity, and pray the model grounds its answer instead of hallucinating. This is the open alternative. Retrieval is triple-mediated: questions are answered through a verified knowledge graph with provenance, not by a vector lookup the generator is trusted to use well. The dense index is distrusted — optional, off by default, flagged when used. Every answer is verifiable and cited, numbers are byte-exact, and the system abstains rather than guess when it can't ground a claim.

The baseline runs with no license and no GMS. For production-grade grounding — geometric retrieval, Exact Numerical Memory, contradiction detection, signed answers — the optional GMS backend (knowlytix) snaps in via a lazy seam. Clone it, run the baseline, see exactly where GMS lifts grounding and recall.

Part of the "Beyond … and Pray" series: governed agents · trustworthy RAG · test & validate · LLMs from scratch

Status: the open groundloop baseline (naive chunk→embed→top-k RAG, the deliberate "before") is implemented — numpy-only TF-IDF retrieval + a stuff-and-pray answerer that never abstains. On the Northwind cohort it scores ~20% answer accuracy and 0% abstention: the gap GEODE/GMS closes. Run python demos/naive_rag.py.

What's inside

• Grounded retrieval — answers mediated through a verified knowledge graph
• Provenance + citations — every claim traces to its source
• Byte-exact numbers — Exact Numerical Memory, not "close enough"
• Abstention — says "I can't ground that" instead of guessing
• Distrusted dense index — optional, flagged when used
• GMS-optional — baseline runs free; geometric guarantees via knowlytix

Install

pip install groundloop                # naive RAG baseline (the "before")
pip install "groundloop[ml]"          # + embedders / open-weight models
pip install "groundloop[gms]"         # + the licensed GMS backend (knowlytix)

The GMS upgrade (open-core)

groundloop runs fully without a license. GEODE-RAG — geometric retrieval, Exact Numerical Memory, provenance — requires the licensed knowlytix package, imported lazily:

import groundloop.gms as gms
gms.available()   # True if the licensed backend is installed

The production-grade, GMS-native edition is the Beyond Chunk and Pray, Pro Edition — see knowlytix.ai.

License

Apache-2.0. © 2026 Knowlytix.