kgmodule-utils
kgmodule-utils — Shared graph store, semantic index, pipeline base, and snapshot infrastructure for the KGModule SDK.
Author: Eric G. Suchanek, PhD
Flux-Frontiers, Liberty TWP, OH
Overview
kgmodule-utils is the shared SDK layer for the Flux-Frontiers knowledge-graph ecosystem. It provides everything a domain KG module needs — from type abstractions and SQLite graph storage through pluggable vector indexing (sqlite-vec by default, LanceDB optional) and a full build/query/pack pipeline — so domain authors implement only what is specific to their source domain.
Every KGModule implementation — PyCodeKG, DocKG, and others — subclasses KGModule from here and implements exactly three methods: make_extractor(), kind(), and analyze().
Features
kg_utils.specs—NodeSpec,EdgeSpec,BuildStats,QueryResult,SnippetPackdataclasseskg_utils.extractor—KGExtractorABC:extract(),node_kinds(),edge_kinds(),coverage_metric()kg_utils.store—GraphStore: SQLite-backed node/edge store with BFS expansion, symbol resolution, caller lookup, and provenance recordingkg_utils.semantic—SemanticIndex,SentenceTransformerEmbedder,SeedHit, model registry,resolve_model_path()kg_utils.vector_backend—VectorBackendprotocol withSqliteVecBackend(default, exact recall) andLanceDBBackend(legacy);make_backend(),resolve_backend_name()kg_utils.pipeline—KGModule: full build → query → pack pipeline base with hybrid semantic + lexical reranking and snippet extractionkg_utils.embedder—get_embedder(),wrap_embedder(),load_sentence_transformer()factory functionskg_utils.embed—Embedderprotocol,DEFAULT_MODEL,KNOWN_MODELS,resolve_model_path()kg_utils.snapshots—Snapshot,SnapshotManager,SnapshotManifestfor temporal metric trackingkg_utils.synthesis— Unified text + image synthesis: oMLX, Ollama, and OpenAI text backends; mflux-local, mflux-serve, and DALL-E image backends; all env-var configurablekg_utils.viz— Shared interactive-HTML graph rendering (vizextra):build_graph_html(),select_nodes(),GraphTheme,TooltipSpec— one renderer for code, document, and metabolic graphs, with domain differences supplied as datakg_utils.viz3d— Shared 3-D graph layout (viz3dextra):Layout3D,AlliumLayout,FunnelLayout,LayoutNode,LayoutEdge— coordinates only, no renderer, so each module keeps its own viewer and shares the spatial reasoningkg_utils.analysis— Read persisted centrality back out of SQLite:load_scores(),available_metrics(),ScoreSet(raw score, dense rank, percentile, range scaling); stdlib only
Installation
Requirements: Python ≥ 3.12, < 3.14
Core only (stdlib, no optional deps)
pip install kgmodule-utils
With semantic search (sqlite-vec + sentence-transformers)
pip install 'kgmodule-utils[semantic]'
With legacy LanceDB support (only for an un-migrated LanceDB store)
As of 0.10.0 lancedb is no longer part of [semantic]. Install it explicitly
only if you have a pre-existing, un-migrated LanceDB store on disk.
pip install 'kgmodule-utils[semantic,lancedb]'
With text + image synthesis (oMLX / Ollama / OpenAI / mflux-serve)
pip install 'kgmodule-utils[synthesis]'
With local mflux image generation (Apple Silicon, includes synthesis)
pip install 'kgmodule-utils[synthesis-mflux]'
With interactive graph rendering (pyvis / vis-network)
pip install 'kgmodule-utils[viz]'
With 3-D graph layout (numpy)
pip install 'kgmodule-utils[viz3d]'
In a Poetry project
[tool.poetry.dependencies]
kgmodule-utils = { version = ">=0.4.0", extras = ["semantic", "synthesis"] }
Quick Start
Build a domain KG module
from collections.abc import Iterator
from pathlib import Path
from kg_utils.extractor import KGExtractor
from kg_utils.pipeline import KGModule
from kg_utils.specs import EdgeSpec, NodeSpec
class MyExtractor(KGExtractor):
def node_kinds(self) -> list[str]:
return ["document", "section"]
def edge_kinds(self) -> list[str]:
return ["CONTAINS"]
def meaningful_node_kinds(self) -> list[str]:
return ["section"]
def extract(self) -> Iterator[NodeSpec | EdgeSpec]:
for doc in self.repo_path.glob("**/*.md"):
doc_id = f"document:{doc}"
yield NodeSpec(node_id=doc_id, kind="document",
name=doc.stem, qualname=doc.stem,
source_path=str(doc))
# … yield sections and CONTAINS edges
class MyKG(KGModule):
_default_dir = ".mykg"
def make_extractor(self) -> KGExtractor:
return MyExtractor(self.repo_root)
def kind(self) -> str:
return "my"
def analyze(self) -> str:
s = self.stats()
return f"# MyKG\nnodes={s['total_nodes']}"
# Build and query
kg = MyKG("/path/to/repo")
kg.build(wipe=True)
result = kg.query("authentication flow", k=8, hop=1)
pack = kg.pack("error handling", max_nodes=10)
print(pack.to_markdown())
Track metrics over time
from kg_utils.snapshots import SnapshotManager
mgr = SnapshotManager(".mykg/snapshots", package_name="my-kg")
snapshot = mgr.capture(
version="1.0.0",
branch="main",
graph_stats_dict=kg.stats(),
)
mgr.save_snapshot(snapshot)
snaps = mgr.list_snapshots(limit=5)
delta = mgr.diff_snapshots(snaps[-1]["key"], snaps[0]["key"])
API Reference
kg_utils.specs
| Class | Description |
|---|---|
NodeSpec |
Graph node: node_id, kind, name, qualname, source_path, lineno, end_lineno, docstring, metadata |
EdgeSpec |
Graph edge: source_id, target_id, relation, weight, metadata |
BuildStats |
Build result: node/edge counts, indexed rows, embedding dim |
QueryResult |
Query result: nodes, edges, seeds, hop, relevance metadata |
SnippetPack |
Pack result: nodes with snippets, to_markdown(), to_json(), save() |
kg_utils.extractor
| Class | Description |
|---|---|
KGExtractor |
ABC — implement node_kinds(), edge_kinds(), extract() |
kg_utils.store
| Class | Description |
|---|---|
GraphStore |
SQLite persistence: write(), expand(), query_nodes(), resolve_symbols(), callers_of(), stats() |
kg_utils.semantic
| Class / function | Description |
|---|---|
SemanticIndex |
Vector index over a pluggable backend (sqlite-vec default, LanceDB optional): build(), search() |
SentenceTransformerEmbedder |
Local embedding via sentence-transformers |
resolve_model_path() |
Resolve model name / alias to local cache path |
suppress_ingestion_logging() |
Silence verbose HF / tqdm output during ingestion |
kg_utils.pipeline
| Class | Description |
|---|---|
KGModule |
Concrete base — implement make_extractor(), kind(), analyze(); get build(), query(), pack(), stats() for free |
kg_utils.snapshots
| Class | Description |
|---|---|
Snapshot |
Temporal snapshot keyed by git tree hash with metrics and deltas |
SnapshotManager |
Capture, persist, load, list, diff, and prune snapshots |
SnapshotManifest |
Fast-lookup index with format versioning |
kg_utils.synthesis
Full reference: docs/synthesis.md
| Class / function | Description |
|---|---|
TextBackend |
Enum: omlx | ollama | openai |
ImageBackend |
Enum: mflux-local | mflux-serve | openai |
TextConfig |
Backend config dataclass with resolved_endpoint() / resolved_model() |
ImageConfig |
Backend config dataclass with resolved_server_url() / resolved_model() |
TextSynthesizer |
list_models(), synthesize_rag(), rewrite_for_image() |
ImageSynthesizer |
generate() → PIL Image, generate_b64() → base64 PNG |
text_config_from_env() |
Build TextConfig from SYNTH_* env vars |
image_config_from_env() |
Build ImageConfig from IMAGE_* env vars |
text_synthesizer_from_env() |
Convenience: config + synthesizer in one call |
image_synthesizer_from_env() |
Convenience: config + synthesizer in one call |
kg_utils.viz
Requires the
vizextra.
| Class / function | Description |
|---|---|
build_graph_html() |
Render nodes + edges to a self-contained interactive HTML page (vis-network inlined) |
select_nodes() |
Cap a display graph while keeping it connected — seed on central nodes, expand to neighbours |
GraphTheme |
Names a domain's node kinds and edge relations (KindStyle, with_alpha()) |
TooltipSpec |
Names the node fields worth showing in a tooltip (TooltipRow) |
kg_utils.viz3d
Requires the
viz3dextra.
A layout maps nodes and edges onto {node_id: [x, y, z]} and draws nothing, so the
same layout feeds a PyVista desktop viewer, an off-screen light-field renderer, or a
plain scatter plot. Which kind is a root, which relation means containment, and which
kind sits on which Z level are all constructor arguments — one engine, every domain.
| Class / function | Description |
|---|---|
Layout3D |
ABC for layout strategies: compute(nodes, edges) -> {id: [x, y, z]} |
AlliumLayout |
Each root node becomes a Giant Allium — a stem with a Fibonacci-sphere head of its children (root_kind, contains_rel) |
FunnelLayout |
Node kind picks the Z layer, golden-angle disc spiral within each layer (zlevels, level_sizes, default_level) |
LayoutNode / LayoutEdge |
Domain-neutral node and edge DTOs (from_dict()) |
fibonacci_sphere() / fibonacci_annulus() / golden_spiral_2d() |
Even point distributions for building your own layout |
from kg_utils.viz3d import FunnelLayout, LayoutEdge, LayoutNode
layout = FunnelLayout(
layer_gap=12.0,
zlevels={"document": 0, "section": 1, "chunk": 2},
level_sizes={0: 1.8, 1: 0.9, 2: 0.28},
)
positions = layout.compute(nodes, edges) # {node_id: np.array([x, y, z])}
kg_utils.analysis
| Class / function | Description |
|---|---|
load_scores() |
Read a centrality metric back out of SQLite into a ScoreSet |
available_metrics() |
List the centrality metrics persisted in a graph store (MetricRef) |
ScoreSet |
Per-node raw score, dense rank, percentile, and range scaling (Scaler) |
Project Structure
KG_utils/
├── pyproject.toml
├── docs/
│ └── synthesis.md # Synthesis sub-package reference
├── src/
│ └── kg_utils/
│ ├── __init__.py
│ ├── specs.py # NodeSpec, EdgeSpec, BuildStats, QueryResult, SnippetPack
│ ├── extractor.py # KGExtractor ABC
│ ├── store.py # GraphStore (SQLite)
│ ├── semantic.py # SemanticIndex, SentenceTransformerEmbedder, SeedHit
│ ├── vector_backend.py # VectorBackend protocol, SqliteVecBackend (default), LanceDBBackend
│ ├── pipeline.py # KGModule concrete base class
│ ├── module.py # Re-export shim
│ ├── embed.py # Embedder protocol, model registry
│ ├── embedder.py # SentenceTransformerEmbedder factory functions
│ ├── corpus_embedder.py # CorpusEmbedder / EmbeddingCache: multi-worker corpus embedding
│ ├── retrieval/ # Serialize + enrich KG hits (hit_to_dict, attach_content_by_sqlite)
│ │ ├── __init__.py
│ │ └── hits.py
│ ├── worker/ # RunPod /runsync client (WorkerClient, decode/handle helpers)
│ │ ├── __init__.py
│ │ ├── client.py
│ │ └── ops.py
│ ├── snapshots/
│ │ ├── __init__.py
│ │ ├── models.py # Snapshot, SnapshotManifest, PruneResult
│ │ └── manager.py # SnapshotManager
│ ├── synthesis/
│ │ ├── __init__.py # Public API + factory functions
│ │ ├── _config.py # TextBackend, ImageBackend, TextConfig, ImageConfig, env factories
│ │ ├── _text.py # TextSynthesizer
│ │ ├── _image.py # ImageSynthesizer
│ │ └── factory.py # Per-request backend override helpers
│ ├── viz/ # Shared graph rendering (viz extra)
│ │ ├── __init__.py # build_graph_html, select_nodes, GraphTheme, TooltipSpec
│ │ ├── graph_html.py # Interactive HTML renderer (vis-network inlined)
│ │ ├── theme.py # GraphTheme, KindStyle, with_alpha
│ │ └── tooltip.py # TooltipSpec, TooltipRow
│ ├── viz3d/ # Shared 3-D graph layout (viz3d extra)
│ │ ├── __init__.py # Layout3D, AlliumLayout, FunnelLayout, LayoutNode, LayoutEdge
│ │ └── layout.py # Layout engine + Fibonacci point distributions
│ └── analysis/
│ ├── __init__.py # load_scores, available_metrics, ScoreSet
│ └── scores.py # Read persisted centrality out of SQLite
└── tests/
├── test_store.py # GraphStore unit tests
├── test_pipeline_utils.py # Pipeline utility function tests
├── test_pipeline_module.py # End-to-end integration tests (--integration)
├── test_types.py # Spec dataclass and KGExtractor tests
├── test_snapshots.py # Snapshot lifecycle tests
├── test_integration.py # Cross-module integration tests
├── test_synthesis_config.py # Config defaults and env-var priority chains (44 tests)
├── test_synthesis_text.py # TextSynthesizer with mocked openai client (38 tests)
└── test_synthesis_image.py # ImageSynthesizer with mocked backends (34 tests)
Development
git clone https://github.com/Flux-Frontiers/KG_utils.git
cd KG_utils
poetry install --with dev
Run the fast test suite (no model downloads):
poetry run pytest -m "not integration"
Run all tests including semantic/integration (requires [semantic] extra):
poetry run pytest
Citation
If you use kgmodule-utils in research or a project, please cite it:
APA
Suchanek, E. G. (2026). kgmodule-utils: Shared SDK for the KGModule Knowledge-Graph Ecosystem (Version 0.11.0) [Software]. Flux-Frontiers. https://doi.org/10.5281/zenodo.21387077
BibTeX
@software{suchanek_kgmodule_utils,
author = {Suchanek, Eric G.},
title = {{kgmodule-utils}: Shared SDK for the KGModule Knowledge-Graph Ecosystem},
version = {0.11.0},
year = {2026},
publisher = {Flux-Frontiers},
url = {https://github.com/Flux-Frontiers/KG_utils},
doi = {10.5281/zenodo.21387077},
}
Citation metadata is also available in CITATION.cff.
License
Elastic License 2.0 — see LICENSE.
Free to use, modify, and distribute. You may not offer the software as a hosted or managed service to third parties. Commercial use internally is permitted.
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