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Add Neptune-DB graph store with vector store (#3443)

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Signed-off-by: Andrew Carbonetto <andrew.carbonetto@improving.com>
Co-authored-by: Siddhartha Sahu <dev@sdht.in>
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Andrew Carbonetto
2025-09-18 14:24:33 -07:00
committed by GitHub
parent d4e98dba38
commit a015e2ff4a
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docs/open-source/graph_memory/overview.mdx
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## Initialize Graph Memory
To initialize Graph Memory you'll need to set up your configuration with graph
store providers. Currently, we support [Neo4j](#initialize-neo4j), [Memgraph](#initialize-memgraph), [Neptune Analytics](#initialize-neptune-analytics), and [Kuzu](#initialize-kuzu) as graph store providers.
store providers. Currently, we support [Neo4j](#initialize-neo4j), [Memgraph](#initialize-memgraph), [Neptune Analytics](#initialize-neptune-analytics), [Neptune DB Cluster](#initialize-neptune-db),and [Kuzu](#initialize-kuzu) as graph store providers.
### Initialize Neo4j
@@ -231,35 +231,27 @@ m = Memory.from_config(config_dict=config)
### Initialize Neptune Analytics
Mem0 now supports Amazon Neptune Analytics as a graph store provider. This integration allows you to use Neptune Analytics for storing and querying graph-based memories.
Note: You can use Neptune Analytics as part of an Amazon tech stack [Setup AWS Bedrock, AOSS, and Neptune](https://docs.mem0.ai/examples/aws_example#aws-bedrock-and-aoss)
You can use Neptune Analytics as part of an Amazon tech stack [Setup AWS Bedrock, AOSS, and Neptune](https://docs.mem0.ai/examples/aws_example#aws-bedrock-and-aoss)
#### Instance Setup
Create an Amazon Neptune Analytics instance in your AWS account following the [AWS documentation](https://docs.aws.amazon.com/neptune-analytics/latest/userguide/get-started.html).
Create an instance of Amazon Neptune Analytics in your AWS account following the [AWS documentation](https://docs.aws.amazon.com/neptune-analytics/latest/userguide/get-started.html).
- Public connectivity is not enabled by default, and if accessing from outside a VPC, it needs to be enabled.
- Once the Amazon Neptune Analytics instance is available, you will need the graph-identifier to connect.
- The Neptune Analytics instance must be created using the same vector dimensions as the embedding model creates. See: https://docs.aws.amazon.com/neptune-analytics/latest/userguide/vector-index.html
- The Neptune Analytics instance must be created using the same vector dimensions as the embedding model creates. See: [Vector indexing in Neptune Analytics](https://docs.aws.amazon.com/neptune-analytics/latest/userguide/vector-index.html).
#### Attach Credentials
Ensure that you attach your AWS credentials with access to your Amazon Neptune Analytics resources by following the [Configuration and credentials precedence](https://docs.aws.amazon.com/cli/v1/userguide/cli-chap-configure.html#configure-precedence).
Configure your AWS credentials with access to your Amazon Neptune Analytics resources by following the [Configuration and credentials precedence](https://docs.aws.amazon.com/cli/v1/userguide/cli-chap-configure.html#configure-precedence).
- For example, add your SSH access key session token via environment variables:
```bash
export AWS_ACCESS_KEY_ID=your-access-key
export AWS_SECRET_ACCESS_KEY=your-secret-key
export AWS_SESSION_TOKEN=your-session-token
export AWS_DEFAULT_REGION=your-region
```
- The IAM user or role making the request must have a policy attached that allows one of the following IAM actions in that neptune-graph:
The IAM user or role making the request must have a policy attached that allows one of the following IAM actions in that neptune-graph:
- neptune-graph:ReadDataViaQuery
- neptune-graph:WriteDataViaQuery
- neptune-graph:DeleteDataViaQuery
#### Usage
User can also customize the LLM for Graph Memory from the [Supported LLM list](https://docs.mem0.ai/components/llms/overview) with three levels of configuration:
The Neptune memory store uses AWS LangChain Python API to connect to Neptune instances. For additional configuration options for connecting to your Amazon Neptune Analytics instance see [AWS LangChain API documentation](https://python.langchain.com/api_reference/aws/graphs/langchain_aws.graphs.neptune_graph.NeptuneAnalyticsGraph.html).
1. **Main Configuration**: If `llm` is set in the main config, it will be used for all graph operations.
2. **Graph Store Configuration**: If `llm` is set in the graph_store config, it will override the main config `llm` and be used specifically for graph operations.
3. **Default Configuration**: If no custom LLM is set, the default LLM (`gpt-4o-2024-08-06`) will be used for all graph operations.
Here's how you can do it:
<CodeGroup>
```python Python
@@ -279,13 +271,61 @@ m = Memory.from_config(config_dict=config)
```
</CodeGroup>
#### Troubleshooting
Troubleshooting:
- For issues connecting to Amazon Neptune Analytics, please refer to the [Connecting to a graph guide](https://docs.aws.amazon.com/neptune-analytics/latest/userguide/gettingStarted-connecting.html).
- For issues related to authentication, refer to the [boto3 client configuration options](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html).
- For more details on how to connect, configure, and use the graph_memory graph store, see the Neptune Analytics example in our [AWS example guide](/examples/aws_example#aws-bedrock-and-aoss).
- The Neptune memory store uses AWS LangChain Python API to connect to Neptune instances. For additional configuration options for connecting to your Amazon Neptune Analytics instance, see [AWS LangChain API documentation](https://python.langchain.com/api_reference/aws/graphs/langchain_aws.graphs.neptune_graph.NeptuneAnalyticsGraph.html).
### Initialize Neptune DB
Note that Neptune DB does not support vectors, and this graph store provider requires a collection in the vector store to save entity vectors.
Create a cluster of Amazon DB instances in your AWS account following the [AWS documentation](https://docs.aws.amazon.com/neptune/latest/userguide/graph-get-started.html).
- Public connectivity is not enabled by default. To access the instance from outside a VPC, public connectivity needs to be enabled on the Neptune DB instance by following [Neptune Public Endpoints](https://docs.aws.amazon.com/neptune/latest/userguide/neptune-public-endpoints.html).
- Once the Amazon Neptune Cluster instance is available, you will need the graph host endpoint to connect.
- Neptune DB doesn't support vectors. The `collection_name` config field can be used to specify the vector store collection used to store vectors for the Neptune entities.
Ensure that you attach your AWS credentials with access to your Amazon Neptune Analytics resources by following the [Configuration and credentials precedence](https://docs.aws.amazon.com/cli/v1/userguide/cli-chap-configure.html#configure-precedence).
The IAM user or role making the request must have a policy attached that allows one of the following IAM actions in that neptune-db:
- neptune-db:ReadDataViaQuery
- neptune-db:WriteDataViaQuery
- neptune-db:DeleteDataViaQuery
User can also customize the LLM for Graph Memory from the [Supported LLM list](https://docs.mem0.ai/components/llms/overview) with three levels of configuration:
1. **Main Configuration**: If `llm` is set in the main config, it will be used for all graph operations.
2. **Graph Store Configuration**: If `llm` is set in the graph_store config, it will override the main config `llm` and be used specifically for graph operations.
3. **Default Configuration**: If no custom LLM is set, the default LLM (`gpt-4o-2024-08-06`) will be used for all graph operations.
Here's how you can do it:
<CodeGroup>
```python Python
from mem0 import Memory
config = {
"graph_store": {
"provider": "neptunedb",
"config": {
"collection_name": "<VECTOR_COLLECTION_NAME>",
"endpoint": "neptune-graph://<HOST_ENDPOINT>",
},
},
}
m = Memory.from_config(config_dict=config)
```
</CodeGroup>
Troubleshooting:
- For issues connecting to Amazon Neptune Analytics, please refer to the [Accessing graph data in Amazon Neptune](https://docs.aws.amazon.com/neptune/latest/userguide/get-started-access-graph.html).
- For issues related to authentication, refer to the [boto3 client configuration options](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html).
- For more details on how to connect, configure, and use the graph_memory graph store, see the [Neptune DB example notebook](examples/graph-db-demo/neptune-example.ipynb).
- The Neptune memory store uses AWS LangChain Python API to connect to Neptune instances. For additional configuration options for connecting to your Amazon Neptune Analytics instance, see [AWS LangChain API documentation](https://python.langchain.com/api_reference/aws/graphs/langchain_aws.graphs.neptune_graph.NeptuneGraph.html).
### Initialize Kuzu