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NVIDIA NeMo Fabric

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Diagram showing NeMo Fabric connecting applications, evaluations, and reinforcement learning rollouts to Hermes, Codex, Claude, and Deep Agents, with results, artifacts, and telemetry as outputs.

NeMo Fabric gives users one configurable, observable way to run applications across multiple agent harnesses. It standardizes configuration, lifecycle management, and results without requiring a separate integration for every harness.

NeMo Fabric lets you change harnesses without rebuilding each integration, isolate conflicting runtime dependencies, and manage harness configuration, execution, and observability consistently. Every run returns normalized results, artifacts, and telemetry for downstream systems to consume.

It provides:

  • a versioned, typed configuration contract;
  • ordinary Python composition for experiment variants;
  • adapter integrations for harness-specific launch and control;
  • a Python SDK backed by the Rust core;
  • normalized run results, artifact manifests, and telemetry references.

Supported Harnesses

NeMo Fabric provides the following harness integrations. The package expressions install the components shown in each column:

Agent Harness Runtime, Adapter, and Harness Adapter and Harness Adapter Only
Claude Code nemo-fabric[claude] nemo-fabric-adapters-claude[harness] nemo-fabric-adapters-claude
Codex nemo-fabric[codex] nemo-fabric-adapters-codex[harness] nemo-fabric-adapters-codex
Hermes Agent nemo-fabric[hermes-agent] nemo-fabric-adapters-hermes[harness] nemo-fabric-adapters-hermes
LangChain Deep Agents nemo-fabric[deepagents] nemo-fabric-adapters-deepagents[harness] nemo-fabric-adapters-deepagents

The nemo-fabric package always installs the runtime, and each root harness extra adds the corresponding adapter and supported harness. Use the adapter-package forms for split environments or environments that already manage the harness. For harness, full, and Relay behavior, refer to the installation guide.

Capabilities vary by harness. Review the compatibility matrix and use plan() and doctor() before relying on optional capabilities such as MCP, skills, blocked tools, subagents, or telemetry.

Supported Platforms

NeMo Fabric supports the following platforms:

  • Linux (x86_64, arm64)
  • macOS (arm64)
  • Windows (x86_64)

Quick Start

The following example runs NeMo Fabric, the Hermes Agent adapter, and Hermes Agent in one Python environment.

Install NeMo Fabric and Hermes Agent

Hermes Agent supports Python 3.11 through 3.13. With a supported Python version, create and activate a virtual environment, then install the required packages:

python -m venv .venv
source .venv/bin/activate
pip install "nemo-fabric[hermes-agent]"

Set the API Key

Create an API key in the NVIDIA API Catalog, then set the NVIDIA_API_KEY environment variable:

export NVIDIA_API_KEY="<your-api-key>"

Run Hermes Agent

Run the following Python example:

import asyncio

from nemo_fabric import (
    Fabric,
    FabricConfig,
    HarnessConfig,
    MetadataConfig,
    ModelConfig,
    RuntimeConfig,
)

config = FabricConfig(
    metadata=MetadataConfig(name="quickstart-agent"),
    harness=HarnessConfig(adapter_id="nvidia.fabric.hermes"),
    runtime=RuntimeConfig(max_turns=1),
    models={
        "default": ModelConfig(
            provider="nvidia",
            model="nvidia/nemotron-3-nano-omni-30b-a3b-reasoning",
            api_key_env="NVIDIA_API_KEY",
            base_url="https://integrate.api.nvidia.com/v1",
        )
    },
)

result = asyncio.run(Fabric().run(config, input="Who are you?"))
print(result.output.response)

HarnessConfig.adapter_id selects the Hermes Agent adapter. To use another supported harness, install its package extra and set the corresponding adapter ID. Pass harness-specific options through HarnessConfig.settings only when the selected adapter descriptor declares them in settings_schema. Adapters that expose selectable executables can accept FabricConfig.workflow; the descriptor's workflow_schema defines and validates that adapter-owned block.

For a guided version of this example, refer to the 01_quickstart.ipynb notebook. The example notebooks overview describes the other available notebooks.

Deployment Scenarios

Scenario 1: Runtime and Harness in the Same Environment

This is the simplest deployment. The nemo-fabric package, selected adapter, and supported harness share one Python environment. The quick start above uses this model with nemo-fabric[hermes-agent].

Scenario 2: Isolated Sandbox for Task Execution

This is the Harbor deployment model. The Harbor host constructs and serializes the final typed FabricConfig. Harbor then installs and runs NeMo Fabric, the selected adapter, and the harness inside an isolated task environment such as a Docker container or Daytona sandbox. Adapter discovery and task-path resolution occur inside that sandbox.

Install nemo-fabric[harbor]==0.2.0 in the host environment. Install a complete harness composition such as nemo-fabric[claude]==0.2.0 or nemo-fabric[hermes-agent,relay]==0.2.0 in the task environment. For Claude or Codex Relay streaming, also provision the external NeMo Relay CLI in the task environment. Refer to the Harbor execution model for details.

Scenario 3: Runtime and Harness in Separate Python Environments

NeMo Fabric can run the runtime and agent harness in separate, locally accessible Python environments. This setup isolates their Python dependencies while the runtime launches the adapter through the adapter environment's interpreter.

Create an environment for the NeMo Fabric runtime:

python -m venv .venv-fabric
source .venv-fabric/bin/activate
pip install nemo-fabric==0.2.0

Create another environment for the adapter and harness. For example, install the Hermes Agent integration:

python -m venv .venv-hermes
source .venv-hermes/bin/activate
pip install "nemo-fabric-adapters-hermes[harness]==0.2.0"

The adapter package keeps this environment independent from the nemo-fabric distribution. Its harness extra installs the compatible Hermes Agent dependency alongside the adapter. Use matching NeMo Fabric release versions for the runtime and adapter package unless a different pairing has been explicitly validated.

Run NeMo Fabric from its environment and set ADAPTER_PYTHON to the interpreter that contains the adapter and harness:

source .venv-fabric/bin/activate
export ADAPTER_PYTHON="$PWD/.venv-hermes/bin/python"

For package options and platform-specific instructions, refer to the installation guide.

Execution Flow

The following diagram shows how configuration moves through the core and selected adapter to the harness, normalized results, artifacts, and telemetry:

flowchart TB
  Consumer["Consumer\nDeployment Platform | Evaluation Harnesses"]
  Config["Typed configuration\nFabricConfig"]
  Core["NeMo Fabric Rust core\nresolve | plan | create | invoke | destroy"]
  Adapter["Selected NeMo Fabric adapter"]
  Harness["Agent harness runtime\nHermes Agent | Codex | Claude Code | LangChain Deep Agents | custom"]
  Artifacts["Normalized results and artifacts\nresponse | logs | patches | telemetry refs"]
  Relay["NVIDIA NeMo Relay\nATOF | ATIF | OTel | OpenInference when enabled"]

  Consumer --> Core
  Config --> Core
  Core --> Adapter
  Adapter --> Harness
  Harness --> Artifacts
  Core --> Artifacts
  Artifacts --> Consumer
  Core -. telemetry config .-> Relay
  Harness -. harness telemetry .-> Relay
Loading

Next Steps

Learn and Experiment

Use the following resources to learn about NeMo Fabric:

  • Example Notebooks provide a guided tour of the Python SDK.
  • Python SDK guide: typed configuration, planning, diagnostics, requests, multi-turn runtimes, NeMo Relay streaming, parallelism, results, and errors.
  • Experimentation CLI: presets, maintained examples, editable application scaffolds, and explicit non-goals.
  • Getting Started overview: interface selection and the end-to-end NeMo Fabric workflow.

Consumer Integrations

Consumer integrations are northbound: they connect applications, evaluation systems, and platforms to NeMo Fabric through its public interfaces. Use the following resources to build or validate a consumer integration:

  • Consumer integration skills provide repository-local coding-agent workflows for integrating NeMo Fabric into an application through the Python SDK.
  • The Harbor integration explains how to validate the integration with a deterministic, credential-free calculator verification test. You can also run the same task with Hermes Agent or Claude and evaluate coding tasks with SWE-Bench.

Harness Integrations

Harness integrations are southbound: they connect NeMo Fabric to agent harnesses through adapters. Use the following reference to compare the integrations:

Roadmap

  • Custom harnesses: Publish the NeMo Fabric adapter contract so third-party developers can build integrations that are compatible with NeMo Fabric. Support integrations maintained by NeMo Fabric and compatible third-party integrations.
  • Custom agents: Support custom agents built on maintained or third-party harness integrations without requiring an additional, agent-specific adapter. Preserve the normalized NeMo Fabric lifecycle, results, artifacts, and telemetry.

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