Add Amazon Neptune Analytics graph_store configuration & integration (#2949)

docs/open-source/graph_memory/overview.mdx

@@ -232,6 +232,66 @@ m = Memory.from_config(config_dict=config)
 ```
 </CodeGroup>
 
+### 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.
+
+#### 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).
+- 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
+
+#### Attach Credentials
+
+ 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:
+  - neptune-graph:ReadDataViaQuery
+  - neptune-graph:WriteDataViaQuery
+  - neptune-graph:DeleteDataViaQuery
+
+#### Usage
+
+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).
+
+<CodeGroup>
+```python Python
+from mem0 import Memory
+
+# This example must connect to a neptune-graph instance with 1536 vector dimensions specified.
+config = {
+    "embedder": {
+        "provider": "openai",
+        "config": {"model": "text-embedding-3-large", "embedding_dims": 1536},
+    },
+    "graph_store": {
+        "provider": "neptune",
+        "config": {
+            "endpoint": "neptune-graph://<GRAPH_ID>",
+        },
+    },
+}
+
+m = Memory.from_config(config_dict=config)
+```
+</CodeGroup>
+
+#### 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 notebook](examples/graph-db-demo/neptune-analytics-example.ipynb).
+
 ## Graph Operations
 The Mem0's graph supports the following operations: