coordinode-python

Python SDK for CoordiNode — the graph-native hybrid retrieval engine for AI and GraphRAG.

Graph + Vector + Full-Text in a single transactional engine. One client, one query.

Packages

Package	PyPI	Description
coordinode		Core gRPC client — sync + async
langchain-coordinode		LangChain GraphStore + GraphCypherQAChain
llama-index-graph-stores-coordinode		LlamaIndex PropertyGraphStore

Quick Start

# Start CoordiNode
docker compose up -d

# Install
pip install coordinode
# or
uv add coordinode

from coordinode import CoordinodeClient

with CoordinodeClient("localhost:7080") as db:
    # Cypher query — returns List[Dict[str, Any]]
    rows = db.cypher(
        "MATCH (n:Concept {name: $name})-[:RELATED_TO*1..2]->(m) RETURN m.name AS name",
        params={"name": "machine learning"},
    )
    for row in rows:
        print(row["name"])

LangChain — GraphRAG Pipeline

from langchain_coordinode import CoordinodeGraph
from langchain.chains import GraphCypherQAChain
from langchain_openai import ChatOpenAI

graph = CoordinodeGraph("localhost:7080")
chain = GraphCypherQAChain.from_llm(
    ChatOpenAI(model="gpt-4o-mini"),
    graph=graph,
    verbose=True,
)
result = chain.invoke({"query": "What concepts are related to transformers?"})
print(result["result"])

LlamaIndex — Knowledge Graph Index

from llama_index.core import PropertyGraphIndex
from llama_index.graph_stores.coordinode import CoordinodePropertyGraphStore

store = CoordinodePropertyGraphStore("localhost:7080")
index = PropertyGraphIndex.from_documents(docs, property_graph_store=store)
engine = index.as_query_engine(include_text=True)
response = engine.query("Explain attention mechanisms")

Development Setup

Using uv (recommended)

git clone --recurse-submodules https://github.com/structured-world/coordinode-python
cd coordinode-python
uv sync          # installs all packages + dev deps from uv.lock
make proto       # generate gRPC stubs from proto submodule
uv run pytest tests/unit/ -v

Using pip

git clone --recurse-submodules https://github.com/structured-world/coordinode-python
cd coordinode-python
pip install grpcio-tools
make install-pip # generates proto stubs + installs all packages in editable mode
pytest tests/unit/ -v

Running integration tests

Integration tests require a running CoordiNode instance:

docker compose up -d
COORDINODE_ADDR=localhost:7080 pytest tests/integration/ -v --timeout=30

Versioning

SDK versions track the server: coordinode 0.3.x is compatible with coordinode-server 0.3.x.

License

Apache-2.0 — see LICENSE.

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Support the Project

If you believe graph + vector + full-text retrieval should live in one engine under a genuine open-source license, consider sponsoring:

• GitHub Sponsors
• Open Collective

USDT (TRC-20): TFDsezHa1cBkoeZT5q2T49Wp66K8t2DmdA

Sponsorship accelerates: vector search integration, Bolt protocol compatibility, and the Enterprise Edition for horizontal scaling.