# Custom Arguments

You can use vLLM *custom arguments* to pass in arguments which are not part of the vLLM `SamplingParams` and REST API specifications. Adding or removing a vLLM custom argument does not require recompiling vLLM, since the custom arguments are passed in as a dictionary.

Custom arguments can be useful if, for example, you want to use a [custom logits processor](./custom_logitsprocs.md) without modifying the vLLM source code.

!!! note
    Make sure your custom logits processor have implemented `validate_params` for custom arguments. Otherwise invalid custom arguments can cause unexpected behaviour.

## Offline Custom Arguments

Custom arguments passed to `SamplingParams.extra_args` as a `dict` will be visible to any code which has access to `SamplingParams`:

``` python
SamplingParams(extra_args={"your_custom_arg_name": 67})
```

This allows arguments which are not already part of `SamplingParams` to be passed into `LLM` as part of a request.

## Online Custom Arguments

The vLLM REST API allows custom arguments to be passed to the vLLM server via `vllm_xargs`. The example below integrates custom arguments into a vLLM REST API request:

``` bash
curl http://localhost:8000/v1/completions \
    -H "Content-Type: application/json" \
    -d '{
        "model": "Qwen/Qwen2.5-1.5B-Instruct",
        ...
        "vllm_xargs": {"your_custom_arg": 67}
    }'
```

Furthermore, OpenAI SDK users can access `vllm_xargs` via the `extra_body` argument:

``` python
batch = await client.completions.create(
    model="Qwen/Qwen2.5-1.5B-Instruct",
    ...,
    extra_body={
        "vllm_xargs": {
            "your_custom_arg": 67
        }
    }
)
```

!!! note
    `vllm_xargs` is assigned to `SamplingParams.extra_args` under the hood, so code which uses `SamplingParams.extra_args` is compatible with both offline and online scenarios.