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Epistemic Graph

Run locally

Knuckles-Team/epistemic-graph

Run Epistemic Graph locally¶

The release wheel contains the Python package, the Rust server binary, and the in-process engine binding. Start with the embedded binding when you want to evaluate the graph API without configuring a service.

Install and create a graph¶

python -m pip install epistemic-graph
python - <<'PY'
import msgpack
from epistemic_graph.engine import Engine

engine = Engine(persist_dir=":memory:")
engine.create_graph("demo")
engine.add_node(
    "demo",
    "node:alice",
    msgpack.packb({"kind": "Person", "name": "Alice"}, use_bin_type=True),
)

properties = msgpack.unpackb(
    engine.get_node_properties("demo", "node:alice"),
    raw=False,
)
print(properties)
print("nodes:", engine.node_count("demo"))
PY

The command prints:

{'kind': 'Person', 'name': 'Alice'}
nodes: 1

persist_dir=":memory:" is an explicit ephemeral mode: the process owns the engine and its contents disappear when the process exits. It is the smallest way to verify the installed engine and learn the local API.

Choose the runtime shape¶

Need	Runtime shape	Next page
Explore the native API in one Python process	Embedded, in memory	This page
Run one durable database on a host	Server over a local Unix socket	Standalone deployment
Connect applications across hosts	Server over authenticated TLS	Deployment reference
Replicate and partition durable state	Cluster build	Cluster deployment

The service paths require explicit persistence, identity, policy, and request authority. Those settings belong in deployment configuration, so the local example stays short without weakening the network boundary.

Continue¶