# Deterministic, cited knowledge graphs from your documents.

Local-first, with byte-level provenance on every edge. Deterministic by default — the same corpus always yields a byte-identical graph you can audit and re-verify — with opt-in LLM extraction, grounded answer synthesis, and semantic search layered on top, always quarantined so model output never poses as ground truth.

Open the interactive demo → GitHub PyPI Changelog

`pip install textgraph-kg`

### Every claim is cited

Each edge carries a re-verifiable `[doc:byte-span]` citation — re-hash it against the source and it still matches.

### Decisions & provenance

WHY/DECISION/ADR markers become a queryable causal chain; export a W3C PROV-O audit trail.

### Conflicts, never silent

Contradictory single-truth claims are surfaced for review, resolved only on an explicit, non-destructive policy.

### Bring your own scale

Optional GQL, vision retrieval, access control, and Graph-of-Thoughts reasoning — each an opt-in module.