# OpenAPI Support

MLServer follows the Open Inference Protocol (previously known as the "V2 Protocol"). You can find the full OpenAPI spec for the Open Inference Protocol in the links below:

| Name                       | Description                                                                                          | OpenAPI Spec                                                                                 |
| -------------------------- | ---------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------- |
| Open Inference Protocol    | Main dataplane for inference, health and metadata                                                    | [dataplane.json](https://github.com/SeldonIO/mlserver/openapi/dataplane.json)                |
| Model Repository Extension | Extension to the protocol to provide a control plane which lets you load / unload models dynamically | [model\_repository.json](https://github.com/SeldonIO/mlserver/openapi/model_repository.json) |

## Swagger UI

On top of the OpenAPI spec above, MLServer also autogenerates a Swagger UI which can be used to interact dynamycally with the Open Inference Protocol.

The autogenerated Swagger UI can be accessed under the `/v2/docs` endpoint.

{% hint style="info" %}
Besides the Swagger UI, you can also access the *raw* OpenAPI spec through the `/v2/docs/dataplane.json` endpoint.
{% endhint %}

![](/files/uV7e3CeOF2e8YxAYw6p4)

## Model Swagger UI

Alongside the [general API documentation](#Swagger-UI), MLServer will also autogenerate a Swagger UI tailored to individual models, showing the endpoints available for each one.

The model-specific autogenerated Swagger UI can be accessed under the following endpoints:

* `/v2/models/{model_name}/docs`
* `/v2/models/{model_name}/versions/{model_version}/docs`

{% hint style="info" %}
Besides the Swagger UI, you can also access the model-specific *raw* OpenAPI spec through the following endpoints:

* `/v2/models/{model_name}/docs/dataplane.json`
* `/v2/models/{model_name}/versions/{model_version}/docs/dataplane.json`
  {% endhint %}

![](/files/kC0AFIjZ1qrhkGvBL5XM)


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# Agent Instructions: Querying This Documentation

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Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.seldon.ai/mlserver/user-guide/openapi.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.