mem0-falkordb 0.1.0

FalkorDB graph store plugin for Mem0

mem0-falkordb

FalkorDB graph store plugin for Mem0. Adds FalkorDB as a graph memory backend without modifying any Mem0 source code.

Installation

pip install mem0-falkordb

You also need Mem0 installed separately:

pip install mem0ai

Quick Start

from mem0_falkordb import register
register()

from mem0 import Memory

config = {
    "graph_store": {
        "provider": "falkordb",
        "config": {
            "host": "localhost",
            "port": 6379,
            "database": "mem0",
        },
    },
    # Add your LLM and embedder config as usual
    "llm": {
        "provider": "openai",
        "config": {"model": "gpt-4o-mini"},
    },
}

m = Memory.from_config(config)
m.add("I love pizza", user_id="alice")
results = m.search("what does alice like?", user_id="alice")

Configuration

Parameter	Type	Default	Description
host	str	localhost	FalkorDB server host
port	int	6379	FalkorDB server port
database	str	mem0	Graph name in FalkorDB
username	str	None	Authentication username (optional)
password	str	None	Authentication password (optional)
base_label	bool	True	Use __Entity__ base label

Running FalkorDB

Using Docker:

docker run --rm -p 6379:6379 falkordb/falkordb

How It Works

This plugin uses Python's runtime patching to register FalkorDB into Mem0's existing factory system:

1. GraphStoreFactory.provider_to_class gets a new "falkordb" entry
2. GraphStoreConfig is patched to accept FalkorDBConfig
3. A MemoryGraph class translates Mem0's graph operations to FalkorDB-compatible Cypher

Key Cypher Translations

Neo4j	FalkorDB
elementId(n)	id(n)
vector.similarity.cosine()	db.idx.vector.queryNodes() procedure
db.create.setNodeVectorProperty()	SET n.embedding = vecf32($vec)
CALL { ... UNION ... } subqueries	Separate outgoing + incoming queries

Development

git clone <repo>
cd mem0-falkordb
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pytest

License

Apache-2.0