Document that MemMachine integration is Experimental (#1854)

**Summary**
This PR marks the MemMachine integration as Experimental across runtime behavior, package metadata, and user-facing documentation to discourage production adoption until the integration is stabilized. The feature will be tested in v1.7.0 at which point the experimental markers can be dropped.

**What changed**
- Added runtime experimental warning for MemMachine memory registration:
  - Applied @experimental(feature_name="MemMachine") to memmachine_memory_client.
- Added explicit Experimental warning text in MemMachine package docs:
  - packages/nvidia_nat_memmachine/README.md
  - packages/nvidia_nat_memmachine/src/nat/meta/pypi.md
- Added package maturity classifier:
  - packages/nvidia_nat_memmachine/pyproject.toml
  - Added Development Status :: 3 - Alpha.
- Updated toolkit docs to label MemMachine as Experimental:
  - docs/source/get-started/installation.md
  - docs/source/build-workflows/memory.md
  - docs/source/build-workflows/workflow-configuration.md
  - docs/source/components/agents/auto-memory-wrapper/auto-memory-wrapper.md

## By Submitting this PR I confirm:
- I am familiar with the [Contributing Guidelines](https://github.com/NVIDIA/NeMo-Agent-Toolkit/blob/develop/docs/source/resources/contributing/index.md).
- We require that all contributors "sign-off" on their commits. This certifies that the contribution is your original work, or you have rights to submit it under the same license, or a compatible license.
  - Any contribution which contains commits that are not Signed-Off will not be accepted.
- When the PR is ready for review, new or existing tests cover these changes.
- When the PR is ready for review, the documentation is up to date with these changes.



## Summary by CodeRabbit

* **Documentation**
  * Marked the MemMachine memory backend as Experimental across docs, README, and PyPI/subpackage notes.
  * Added warnings that the backend is not recommended for production and that behavior/APIs may change without notice.

* **Chores**
  * Updated package metadata/classifiers to reflect alpha/experimental development status.

Authors:
  - Anuradha Karuppiah (https://github.com/AnuradhaKaruppiah)

Approvers:
  - Will Killian (https://github.com/willkill07)

URL: #1854

Author: AnuradhaKaruppiah

docs/source/build-workflows/memory.md

@@ -24,7 +24,7 @@ The memory module is designed to be extensible, allowing developers to create cu
 ## Included Memory Modules
 The NeMo Agent Toolkit includes four memory module providers, all of which are available as plugins:
 * [Mem0](https://mem0.ai/) which is provided by the [`nvidia-nat-mem0ai`](https://pypi.org/project/nvidia-nat-mem0ai/) plugin.
-* [MemMachine](https://memmachine.ai/) which is provided by the [`nvidia-nat-memmachine`](https://pypi.org/project/nvidia-nat-memmachine/) plugin.
+* [MemMachine](https://memmachine.ai/) which is provided by the [`nvidia-nat-memmachine`](https://pypi.org/project/nvidia-nat-memmachine/) plugin (**Experimental; not recommended for production use**).
 * [Redis](https://redis.io/) which is provided by the [`nvidia-nat-redis`](https://pypi.org/project/nvidia-nat-redis/) plugin.
 * [Zep](https://www.getzep.com/) which is provided by the [`nvidia-nat-zep-cloud`](https://pypi.org/project/nvidia-nat-zep-cloud/) plugin ([Zep NVIDIA NeMo documentation](https://help.getzep.com/nvidia-nemo)).
 

docs/source/build-workflows/workflow-configuration.md

@@ -112,7 +112,7 @@ This section contains the evaluation settings for the workflow. Refer to [Evalua
 
 ### `memory`
 
-This section configures long-term memory backends such as [Mem0](https://mem0.ai/) or [MemMachine](https://memmachine.ai/). It follows the same format as the `llms` section. Refer to the [Memory Module](./memory.md) document for supported providers and examples.
+This section configures long-term memory backends such as [Mem0](https://mem0.ai/) or [MemMachine](https://memmachine.ai/) (note: MemMachine is experimental and is not recommended for production use). It follows the same format as the `llms` section. Refer to the [Memory Module](./memory.md) document for supported providers and examples.
 
 ### `retrievers`
 

docs/source/components/agents/auto-memory-wrapper/auto-memory-wrapper.md

@@ -25,7 +25,7 @@ The automatic memory wrapper agent works with any memory backend that implements
 
 - [`nvidia-nat-zep-cloud`](https://pypi.org/project/nvidia-nat-zep-cloud/) - Zep Cloud memory backend ([Zep NVIDIA NeMo documentation](https://help.getzep.com/nvidia-nemo))
 - [`nvidia-nat-mem0ai`](https://pypi.org/project/nvidia-nat-mem0ai/) - Mem0 memory backend
-- [`nvidia-nat-memmachine`](https://pypi.org/project/nvidia-nat-memmachine/) - MemMachine memory backend ([MemMachine documentation](https://docs.memmachine.ai/))
+- [`nvidia-nat-memmachine`](https://pypi.org/project/nvidia-nat-memmachine/) - MemMachine memory backend (**Experimental; not recommended for production use**) ([MemMachine documentation](https://docs.memmachine.ai/))
 - [`nvidia-nat-redis`](https://pypi.org/project/nvidia-nat-redis/) - Redis memory backend
 
 ## Configuration

docs/source/get-started/installation.md

@@ -44,7 +44,7 @@ To install these first-party plugin libraries, you can use the full distribution
 - `nvidia-nat[llama-index]` or `nvidia-nat-llama-index` - [LlamaIndex](https://www.llamaindex.ai/)
 - `nvidia-nat[mcp]` or `nvidia-nat-mcp` - [Model Context Protocol (MCP)](https://modelcontextprotocol.io/)
 - `nvidia-nat[mem0ai]` or `nvidia-nat-mem0ai` - [Mem0](https://mem0.ai/)
-- `nvidia-nat[memmachine]` or `nvidia-nat-memmachine` - [MemMachine](https://memmachine.ai/)
+- `nvidia-nat[memmachine]` or `nvidia-nat-memmachine` - [MemMachine](https://memmachine.ai/) (**Experimental; not recommended for production use**)
 - `nvidia-nat[mysql]` or `nvidia-nat-mysql` - [MySQL](https://www.mysql.com/)
 - `nvidia-nat[config-optimizer]` or `nvidia-nat-config-optimizer` - Parameter and prompt optimizer (required for `nat optimize`)
 - `nvidia-nat[openpipe-art]` or `nvidia-nat-openpipe-art` - [Agent Reinforcement Trainer](https://art.openpipe.ai/getting-started/about) Conflicts with `nvidia-nat[adk]` and `nvidia-nat[crewai]`.

packages/nvidia_nat_memmachine/README.md

@@ -19,6 +19,9 @@ limitations under the License.
 
 This package provides integration with MemMachine for memory management in NeMo Agent toolkit.
 
+> [!WARNING]
+> **Experimental**: The `nvidia-nat-memmachine` plugin is Experimental and is not recommended for production use. Behavior may change without notice.
+
 ## Overview
 
 MemMachine is a unified memory management system that supports both episodic and semantic memory through a single interface. This integration allows you to use MemMachine as a memory backend for your NeMo Agent toolkit workflows.

packages/nvidia_nat_memmachine/pyproject.toml

@@ -40,6 +40,7 @@ license = { text = "Apache-2.0" }
 authors = [{ name = "NVIDIA Corporation" }]
 maintainers = [{ name = "NVIDIA Corporation" }]
 classifiers = [
+  "Development Status :: 3 - Alpha",
   "Programming Language :: Python",
   "Programming Language :: Python :: 3.11",
   "Programming Language :: Python :: 3.12",

packages/nvidia_nat_memmachine/src/nat/meta/pypi.md

@@ -20,5 +20,8 @@ limitations under the License.
 # NVIDIA NeMo Agent toolkit Subpackage
 This is a subpackage for MemMachine memory integration in NeMo Agent toolkit.
 
+> [!WARNING]
+> **Experimental**: The `nvidia-nat-memmachine` plugin is Experimental and is not recommended for production use. Behavior may change without notice.
+
 For more information about the NVIDIA NeMo Agent toolkit, please visit the [NeMo Agent toolkit GitHub Repo](https://github.com/NVIDIA/NeMo-Agent-Toolkit).
 

packages/nvidia_nat_memmachine/src/nat/plugins/memmachine/memory.py

@@ -20,6 +20,7 @@
 from nat.cli.register_workflow import register_memory
 from nat.data_models.memory import MemoryBaseConfig
 from nat.data_models.retry_mixin import RetryMixin
+from nat.experimental.decorators.experimental_warning_decorator import experimental
 from nat.memory.interfaces import MemoryEditor
 from nat.utils.exception_handlers.automatic_retries import patch_with_retry
 
@@ -45,6 +46,7 @@ class MemMachineMemoryClientConfig(MemoryBaseConfig, RetryMixin, name="memmachin
 
 
 @register_memory(config_type=MemMachineMemoryClientConfig)
+@experimental(feature_name="MemMachine")
 async def memmachine_memory_client(
         config: MemMachineMemoryClientConfig,
         _builder: Builder,  # Required by @register_memory contract