> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/gym/llms.txt.
> For full documentation content, see https://docs.nvidia.com/nemo/gym/llms-full.txt.

# CLI Commands

This page documents all available NeMo Gym CLI commands.

<Note>
  Each command has both a short form (such as `ng_run`) and a full form (such as `nemo_gym_run`). They are functionally identical.
</Note>

## Quick Reference

```bash
# Display help
ng_help

# Get detailed help for any command
ng_run +help=true
ng_test +h=true
```

***

## Server Management

Commands for running, testing, and managing NeMo Gym servers.

### `ng_run` / `nemo_gym_run`

Start NeMo Gym servers for agents, models, and resources.

This command reads configuration from YAML files specified via `+config_paths` and starts all configured servers. The configuration files should define server instances with their entrypoints and settings.

**Configuration Parameter**

| Parameter      | Type       | Description                                                                                       |
| -------------- | ---------- | ------------------------------------------------------------------------------------------------- |
| `config_paths` | List\[str] | Paths to YAML configuration files. Specify using Hydra: `+config_paths="[file1.yaml,file2.yaml]"` |

**Example**

```bash
# Start servers with specific configs
config_paths="resources_servers/example_single_tool_call/configs/example_single_tool_call.yaml,\
responses_api_models/openai_model/configs/openai_model.yaml"
ng_run "+config_paths=[${config_paths}]"
```

***

### `ng_test` / `nemo_gym_test`

Test a specific server module by running its pytest suite and optionally validating example data.

**Parameters**

| Parameter              | Type | Description                                                                                                        |
| ---------------------- | ---- | ------------------------------------------------------------------------------------------------------------------ |
| `entrypoint`           | str  | Entrypoint for this command. Must be a relative path with two parts (such as `responses_api_agents/simple_agent`). |
| `should_validate_data` | bool | Whether to validate the example data (examples, metrics, rollouts, and so on) for this server. Default: `False`.   |

**Example**

```bash
ng_test +entrypoint=resources_servers/example_single_tool_call
```

***

### `ng_test_all` / `nemo_gym_test_all`

Run tests for all server modules in the project.

**Parameters**

| Parameter                         | Type | Description                                                                                  |
| --------------------------------- | ---- | -------------------------------------------------------------------------------------------- |
| `fail_on_total_and_test_mismatch` | bool | Fail if the number of server modules does not match the number with tests. Default: `False`. |

**Example**

```bash
ng_test_all
```

***

### `ng_dev_test` / `nemo_gym_dev_test`

Run core NeMo Gym tests with coverage reporting. Runs pytest with the `--cov` flag.

**Example**

```bash
ng_dev_test
```

***

### `ng_init_resources_server` / `nemo_gym_init_resources_server`

Initialize a new resources server with template files and directory structure.

**Example**

```bash
ng_init_resources_server +entrypoint=resources_servers/my_server
```

***

## Data Collection

Commands for collecting verified rollouts for RL training.

### `ng_collect_rollouts` / `nemo_gym_collect_rollouts`

Perform a batch of rollout collection.

**Parameters**

| Parameter                 | Type           | Description                                                                                                              |
| ------------------------- | -------------- | ------------------------------------------------------------------------------------------------------------------------ |
| `agent_name`              | str            | The agent to collect rollouts from.                                                                                      |
| `input_jsonl_fpath`       | str            | The input data source to use to collect rollouts, in the form of a file path to a JSONL file.                            |
| `output_jsonl_fpath`      | str            | The output data JSONL file path.                                                                                         |
| `limit`                   | Optional\[int] | Maximum number of examples to load and take from the input dataset.                                                      |
| `num_repeats`             | Optional\[int] | The number of times to repeat each example to run. Useful if you want to calculate mean\@k, such as mean\@4 or mean\@16. |
| `num_repeats_add_seed`    | bool           | When num\_repeats >1, add a "seed" parameter on the Responses create params.                                             |
| `num_samples_in_parallel` | Optional\[int] | Limit the number of concurrent samples running at once.                                                                  |
| `responses_create_params` | Dict           | Overrides for the `responses_create_params`, such as `temperature` and `max_output_tokens`.                              |

**Example**

```bash
ng_collect_rollouts \
    +agent_name=example_single_tool_call_simple_agent \
    +input_jsonl_fpath=weather_query.jsonl \
    +output_jsonl_fpath=weather_rollouts.jsonl \
    +limit=100 \
    +num_repeats=4 \
    +num_samples_in_parallel=10
```

### `ng_e2e_collect_rollouts` / `nemo_gym_e2e_collect_rollouts`

Spin up all necessary servers and perform a batch of rollout collection using each dataset inside the provided configs.

**Parameters**

| Parameter                 | Type           | Description                                                                                 |
| ------------------------- | -------------- | ------------------------------------------------------------------------------------------- |
| `output_jsonl_fpath`      | str            | The output data JSONL file path.                                                            |
| `num_samples_in_parallel` | Optional\[int] | Limit the number of concurrent samples running at once.                                     |
| `responses_create_params` | Dict           | Overrides for the `responses_create_params`, such as `temperature` and `max_output_tokens`. |

**Examples**

```bash
ng_e2e_collect_rollouts \
    +output_jsonl_fpath=weather_rollouts.jsonl \
    +num_samples_in_parallel=10
```

```bash
config_paths="responses_api_models/openai_model/configs/openai_model.yaml,\
resources_servers/math_with_judge/configs/math_with_judge.yaml"
ng_e2e_collect_rollouts \
    "+config_paths=[${config_paths}]" \
    ++wandb_project= \
    ++wandb_name= \
    ++wandb_dir= \
    ++output_jsonl_fpath=results/test_e2e_rollout_collection/aime24.jsonl \
    ++split=validation
```

Example using GPT-OSS 120B remote vLLM endpoint

```bash
experiment_name=rollouts/test_001
config_paths="responses_api_models/openai_model/configs/openai_model.yaml,\
resources_servers/math_with_judge/configs/math_with_judge.yaml"
ng_e2e_collect_rollouts \
    "+config_paths=[${config_paths}]" \
    +skip_venv_if_present=true \
    +wandb_project=gym-dev \
    +wandb_name=$(date +%Y%m%d)/$experiment_name \
    ++output_jsonl_fpath=results/$experiment_name.jsonl \
    ++overwrite_metrics_conflicts=true \
    ++split=validation \
    ++policy_model_name=openai/gpt-oss-120b \
    ++policy_api_key=dummy_key \
    ++policy_base_url=http://0.0.0.0:10240/v1 \
    ++responses_create_params.reasoning.effort=low \
    ++responses_create_params.temperature=1.0 \
    ++responses_create_params.top_p=1.0 &> eval_gptoss120b.log &
```

***

### `ng_reward_profile` / `nemo_gym_reward_profile`

Computes statistics on rewards and task difficulty for rollouts collected with `ng_collect_rollouts` with `num_repeats` >1. This outputs a new "reward profiled" dataset, where each task in the dataset has metrics like the average reward, standard deviation, min/max, and pass rate. This is useful in filtering tasks before training for difficulty, variance, or creating a curriculum.

**Parameters**

| Parameter              | Type             | Description                                                                                      |
| ---------------------- | ---------------- | ------------------------------------------------------------------------------------------------ |
| `input_jsonl_fpath`    | str              | Path to the original task dataset JSONL file.                                                    |
| `rollouts_jsonl_fpath` | str              | Path to the rollouts file from `ng_collect_rollouts` (must have been run with `num_repeats` >1). |
| `output_jsonl_fpath`   | str              | Output file path for the reward profiled dataset.                                                |
| `pass_threshold`       | Optional\[float] | Reward threshold for computing pass rate. If not specified, pass rate metrics are not included.  |

**Output Fields**

Each output row contains all original task fields plus:

* `avg_reward`: Average reward across all rollouts
* `std_reward`: Standard deviation of rewards
* `min_reward`: Minimum reward observed
* `max_reward`: Maximum reward observed
* `total_samples`: Number of rollout samples
* `pass_rate`, `pass_rate_total`, `pass_rate_passed`, `pass_threshold`: (Only if `pass_threshold` is specified)

**Example**

```bash
ng_reward_profile \
    +input_jsonl_fpath=tasks.jsonl \
    +rollouts_jsonl_fpath=rollouts.jsonl \
    +output_jsonl_fpath=profiled_tasks.jsonl \
    +pass_threshold=1.0
```

***

## Data Management

Commands for preparing and viewing training data.

### `ng_prepare_data` / `nemo_gym_prepare_data`

Prepare and validate training data, generating metrics and statistics for datasets.

**Parameters**

| Parameter                     | Type                                                  | Description                                                                                                                                                         |
| ----------------------------- | ----------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `output_dirpath`              | str                                                   | Directory path where processed datasets and metrics will be saved.                                                                                                  |
| `mode`                        | Literal\["train\_preparation", "example\_validation"] | Processing mode. Use `train_preparation` to prepare train and validation datasets for training, or `example_validation` to validate example data for PR submission. |
| `should_download`             | bool                                                  | Whether to automatically download missing datasets from remote registries. Default: `False`.                                                                        |
| `overwrite_metrics_conflicts` | bool                                                  | Whether or not to overwrite metrics conflicts. Default: `False`.                                                                                                    |

**Example**

```bash
config_paths="resources_servers/example_multi_step/configs/example_multi_step.yaml,\
responses_api_models/openai_model/configs/openai_model.yaml"
ng_prepare_data "+config_paths=[${config_paths}]" \
    +output_dirpath=data/example_multi_step \
    +mode=example_validation
```

***

## Dataset Registry - GitLab

Commands for uploading, downloading, and managing datasets in GitLab Model Registry.

### `ng_upload_dataset_to_gitlab` / `nemo_gym_upload_dataset_to_gitlab`

Upload a local JSONL dataset artifact to GitLab.

**Parameters**

| Parameter           | Type | Description                                                 |
| ------------------- | ---- | ----------------------------------------------------------- |
| `dataset_name`      | str  | The dataset name.                                           |
| `version`           | str  | The version of this dataset. Must be in the format `x.x.x`. |
| `input_jsonl_fpath` | str  | Path to the JSONL file to upload.                           |

**Example**

```bash
ng_upload_dataset_to_gitlab \
    +dataset_name=example_multi_step \
    +version=0.0.1 \
    +input_jsonl_fpath=data/train.jsonl
```

***

### `ng_download_dataset_from_gitlab` / `nemo_gym_download_dataset_from_gitlab`

Download a JSONL dataset from GitLab Model Registry.

**Parameters**

| Parameter        | Type | Description                                                 |
| ---------------- | ---- | ----------------------------------------------------------- |
| `dataset_name`   | str  | The dataset name.                                           |
| `version`        | str  | The version of this dataset. Must be in the format `x.x.x`. |
| `artifact_fpath` | str  | The filepath to the artifact to download.                   |
| `output_fpath`   | str  | Path where the downloaded dataset will be saved.            |

**Example**

```bash
ng_download_dataset_from_gitlab \
    +dataset_name=example_multi_step \
    +version=0.0.1 \
    +artifact_fpath=train.jsonl \
    +output_fpath=data/train.jsonl
```

***

### `ng_delete_dataset_from_gitlab` / `nemo_gym_delete_dataset_from_gitlab`

Delete a dataset from GitLab Model Registry. Prompts for confirmation.

**Parameters**

| Parameter      | Type | Description                                |
| -------------- | ---- | ------------------------------------------ |
| `dataset_name` | str  | Name of the dataset to delete from GitLab. |

**Example**

```bash
ng_delete_dataset_from_gitlab +dataset_name=old_dataset
```

***

## Dataset Registry - HuggingFace

Commands for uploading and downloading datasets to/from HuggingFace Hub.

### `ng_upload_dataset_to_hf` / `nemo_gym_upload_dataset_to_hf`

Upload a JSONL dataset to HuggingFace Hub with optional GitLab deletion after successful upload.

**Parameters**

| Parameter              | Type            | Description                                                                              |
| ---------------------- | --------------- | ---------------------------------------------------------------------------------------- |
| `hf_token`             | str             | HuggingFace API token for authentication.                                                |
| `hf_organization`      | str             | HuggingFace organization name where the dataset will be uploaded.                        |
| `hf_collection_name`   | str             | HuggingFace collection name for organizing datasets.                                     |
| `hf_collection_slug`   | str             | Alphanumeric collection slug found at the end of the collection URI.                     |
| `dataset_name`         | str             | Name of the dataset. Will be combined with domain and resources server name.             |
| `input_jsonl_fpath`    | str             | Path to the local JSONL file to upload.                                                  |
| `resource_config_path` | str             | Path to resources server config file. Used to extract domain for naming convention.      |
| `hf_dataset_prefix`    | str             | Prefix prepended to dataset name. Default: `NeMo-Gym`.                                   |
| `delete_from_gitlab`   | Optional\[bool] | Delete the dataset from GitLab after successful upload to HuggingFace. Default: `False`. |

**Example**

```bash
resource_config_path="resources_servers/example_multi_step/configs/example_multi_step.yaml"
ng_upload_dataset_to_hf \
    +dataset_name=my_dataset \
    +input_jsonl_fpath=data/train.jsonl \
    +resource_config_path=${resource_config_path} \
    +delete_from_gitlab=true
```

***

### `ng_download_dataset_from_hf` / `nemo_gym_download_dataset_from_hf`

Download a JSONL dataset from HuggingFace Hub to local filesystem.

**Parameters**

| Parameter        | Type | Description                                                      |
| ---------------- | ---- | ---------------------------------------------------------------- |
| `output_fpath`   | str  | Local file path where the downloaded dataset will be saved.      |
| `hf_token`       | str  | HuggingFace API token for authentication.                        |
| `artifact_fpath` | str  | Name of the artifact file to download from the repository.       |
| `repo_id`        | str  | HuggingFace repository ID in format `organization/dataset-name`. |

**Example**

```bash
ng_download_dataset_from_hf \
    +repo_id=NVIDIA/NeMo-Gym-Math-example_multi_step-v1 \
    +artifact_fpath=train.jsonl \
    +output_fpath=data/train.jsonl
```

***

### `ng_gitlab_to_hf_dataset` / `nemo_gym_gitlab_to_hf_dataset`

Upload a JSONL dataset to HuggingFace Hub and automatically delete from GitLab after successful upload.

This command always deletes the dataset from GitLab after uploading to HuggingFace. Use `ng_upload_dataset_to_hf` if you want optional deletion control.

**Parameters**

Same as `ng_upload_dataset_to_hf` but `delete_from_gitlab` is not available. This command always deletes.

**Example**

```bash
resource_config_path="resources_servers/example_multi_step/configs/example_multi_step.yaml"
ng_gitlab_to_hf_dataset \
    +dataset_name=my_dataset \
    +input_jsonl_fpath=data/train.jsonl \
    +resource_config_path=${resource_config_path}
```

***

## Configuration & Help

Commands for debugging configuration and getting help.

### `ng_dump_config` / `nemo_gym_dump_config`

Display the resolved Hydra configuration for debugging purposes.

**Example**

```bash
ng_dump_config "+config_paths=[<config1>,<config2>]"
```

***

### `ng_help` / `nemo_gym_help`

Display a list of available NeMo Gym CLI commands.

**Example**

```bash
ng_help
```

***

### `ng_version` / `nemo_gym_version`

Display NeMo Gym version and system information.

**Parameters**

| Parameter     | Type | Description                                                                                       |
| ------------- | ---- | ------------------------------------------------------------------------------------------------- |
| `json_format` | bool | Output in JSON format for programmatic use. Default: `False`. Can be specified with `+json=true`. |

**Example**

```bash
# Display version information
ng_version

# Output as JSON
ng_version +json=true
```

***

### `ng_pip_list` / `nemo_gym_pip_list`

Each server has its own isolated virtual environment. To inspect the packages:

**Parameters**

| Parameter    | Type           | Description                                                                                  |
| ------------ | -------------- | -------------------------------------------------------------------------------------------- |
| `entrypoint` | str            | The relative entrypoint path to the server directory                                         |
| `format`     | Optional\[str] | Output format for pip list. Options: 'columns' (default), 'freeze', 'json'. Default: `None`. |
| `outdated`   | bool           | List outdated packages. Default: `False`.                                                    |

**Examples**

```bash
# List all packages
ng_pip_list +entrypoint=resources_servers/example_single_tool_call

# Output as JSON
ng_pip_list +entrypoint=resources_servers/example_single_tool_call +format=json

# Check for outdated packages
ng_pip_list +entrypoint=resources_servers/example_single_tool_call +outdated=true
```

***

### `ng_status` / `nemo_gym_status`

View all currently running NeMo Gym servers and their health status.

**Example**

```bash
ng_status

NeMo Gym Server Status:

[1] ✓ example_single_tool_call (resources_servers/example_single_tool_call)
{
    'server_type': 'resources_servers',
    'name': 'example_single_tool_call',
    'port': 58117,
    'pid': 89904,
    'uptime_seconds': '0d 0h 0m 41.5s',
}
[2] ✓ example_single_tool_call_simple_agent (responses_api_agents/simple_agent)
{
    'server_type': 'responses_api_agents',
    'name': 'simple_agent',
    'port': 58118,
    'pid': 89905,
    'uptime_seconds': '0d 0h 0m 41.5s',
}
[3] ✓ policy_model (responses_api_models/openai_model)
{
    'server_type': 'responses_api_models',
    'name': 'openai_model',
    'port': 58119,
    'pid': 89907,
    'uptime_seconds': '0d 0h 0m 41.5s',
}

3 servers found (3 healthy, 0 unhealthy)

```

***

## Getting Help

For detailed help on any command, run it with `+help=true` or `+h=true`:

```bash
ng_run +help=true
ng_collect_rollouts +h=true
```

This will display all available configuration parameters and their descriptions.

***

## Re-install Gym and dependencies

```bash
ng_reinstall
```

This will re-install Gym and its dependencies into the currently activated Python virtual environment.