Memgraph as Graph Memory

Prerequisites

1. Install Mem0 with Graph Memory support

To use Mem0 with Graph Memory support, install it using pip:

bash

pip install "mem0ai[graph]"

This command installs Mem0 along with the necessary dependencies for graph functionality.

2. Install Memgraph

To utilize Memgraph as Graph Memory, run it with Docker:

bash

docker run -p 7687:7687 memgraph/memgraph-mage:latest --schema-info-enabled=True

The --schema-info-enabled flag is set to True for more performant schema generation.

Additional information can be found on Memgraph documentation.

Configuration

Do all the imports and configure OpenAI (enter your OpenAI API key):

python

from mem0 import Memory

import os

os.environ["OPENAI_API_KEY"] = ""

Set up configuration to use the embedder model and Memgraph as a graph store:

python

config = {
    "embedder": {
        "provider": "openai",
        "config": {"model": "text-embedding-3-large", "embedding_dims": 1536},
    },
    "graph_store": {
        "provider": "memgraph",
        "config": {
            "url": "bolt://localhost:7687",
            "username": "memgraph",
            "password": "mem0graph",
        },
    },
}

Graph Memory initializiation

Initialize Memgraph as a Graph Memory store:

python

m = Memory.from_config(config_dict=config)

Store memories

Create memories:

python

messages = [
    {
        "role": "user",
        "content": "I'm planning to watch a movie tonight. Any recommendations?",
    },
    {
        "role": "assistant",
        "content": "How about a thriller movies? They can be quite engaging.",
    },
    {
        "role": "user",
        "content": "I'm not a big fan of thriller movies but I love sci-fi movies.",
    },
    {
        "role": "assistant",
        "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future.",
    },
]

Store memories in Memgraph:

python

# Store inferred memories (default behavior)
result = m.add(messages, user_id="alice", metadata={"category": "movie_recommendations"})

Search memories

python

for result in m.search("what does alice love?", user_id="alice")["results"]:
    print(result["memory"], result["score"])