Use the Hermes Agent Adapter | NVIDIA NeMo Fabric

The NVIDIA NeMo Fabric nvidia.fabric.hermes adapter runs Hermes Agent through its Python SDK. The adapter maps normalized NeMo Fabric configuration into Hermes Agent models, tools, skills, Model Context Protocol (MCP) servers, sessions, and telemetry.

Install the Adapter

Hermes Agent and the adapter support Python 3.11 through 3.13.

To install the NeMo Fabric runtime, Hermes Agent adapter, and supported Hermes Agent dependencies in one environment:

$ pip install "nemo-fabric[hermes-agent]"

To install the adapter and supported Hermes Agent without the NeMo Fabric runtime, use the adapter package’s harness extra:

$ pip install "nemo-fabric-adapters-hermes[harness]"

The adapter package also provides relay and full extras. Use relay when the environment already manages Hermes Agent. Use full to install Hermes Agent and the NeMo Relay Python package together.

If the environment already manages a compatible Hermes Agent, install only the adapter:

$ pip install nemo-fabric-adapters-hermes

The bare adapter package does not install the NeMo Fabric runtime or Hermes Agent. Use hermes-agent>=0.17.0, the constraint supported by this release.

If the existing compatible Hermes Agent and NeMo Fabric runtime share an environment, install the runtime and bare adapter together:

$ pip install nemo-fabric nemo-fabric-adapters-hermes

For separate environments, set ADAPTER_PYTHON in the runtime environment to the adapter environment’s Python interpreter. Use matching NeMo Fabric release versions for the runtime and adapter package unless a different pairing has been explicitly validated.

Configure the Adapter

Select the Hermes Agent harness integration in HarnessConfig:

1 from nemo_fabric import HarnessConfig
2 
3 harness = HarnessConfig(adapter_id="nvidia.fabric.hermes")

Use normalized FabricConfig fields to configure the model, workspace, skills, MCP servers, instructions, turn limit, native tool selectors, and telemetry.

The Hermes descriptor validates the following harness.settings fields:

Setting	Type	Default	Description
`reasoning_config`	object	`{"effort": "none"}`	Configures Hermes model reasoning. The closed object accepts an optional `enabled` boolean and an optional `effort` value of `none`, `minimal`, `low`, `medium`, `high`, or `xhigh`.
`plugins_enabled`	array of nonempty strings	`[]`	Enables Hermes plugins by identifier. NeMo Fabric adds `observability/nemo_relay` when Relay telemetry is enabled.
`save_trajectories`	boolean	`false`	Enables Hermes-native JSONL conversation trajectory saving. This is separate from normalized NeMo Fabric telemetry.
`max_tokens`	positive integer	`512`	Limits the number of tokens in each Hermes model response.
`terminal_timeout`	positive number	`60`	Limits a Hermes terminal operation in seconds.

For example:

1 from nemo_fabric import HarnessConfig
2 
3 harness = HarnessConfig(
4     adapter_id="nvidia.fabric.hermes",
5     settings={
6         "reasoning_config": {"enabled": True, "effort": "medium"},
7         "plugins_enabled": ["disk-cleanup"],
8         "save_trajectories": True,
9         "max_tokens": 1024,
10         "terminal_timeout": 90,
11     },
12 )

Use runtime.max_turns to set the Hermes agent-loop budget. The adapter maps that normalized field to AIAgent.max_iterations; max_iterations is not a Hermes harness setting.

Understand the Runtime Lifecycle

Each NeMo Fabric runtime creates one Hermes Agent AIAgent and one SessionDB. Ordered invocations reuse those objects and the conversation history until the runtime stops. When NeMo Relay telemetry is enabled, the adapter finalizes Agent Trajectory Observability Format (ATOF) and Agent Trajectory Interchange Format (ATIF) artifacts after each invocation.

For the complete configuration and lifecycle reference, refer to the Hermes Agent adapter guide.