docs/components/vectordbs/dbs/neptune_analytics.mdx
Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds, including vector search.
pip install mem0ai[vector_stores]
config = {
"vector_store": {
"provider": "neptune",
"config": {
"collection_name": "mem0",
"endpoint": f"neptune-graph://my-graph-identifier",
},
},
}
m = Memory.from_config(config)
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."}
]
m.add(messages, user_id="alice", metadata={"category": "movies"})
Let's see the available parameters for the neptune config:
| Parameter | Description | Default Value |
|---|---|---|
collection_name | The name of the collection to store the vectors | mem0 |
endpoint | Connection URL for the Neptune Analytics service | neptune-graph://my-graph-identifier |