override fun describeTo(description: Description) {
          description.appendText(platform)
        }

        override fun matches(item: Any?): Boolean = getPlatformSystemProperty() == platform
      }

    fun fromMajor(version: Int): Matcher<PlatformVersion> =
      object : TypeSafeMatcher<PlatformVersion>() {
        override fun describeTo(description: Description) {

    object : BaseMatcher<Long?>() {
      override fun describeTo(description: Description?) {
        description!!.appendText("> $value")
      }

      override fun matches(o: Any?): Boolean = (o as Long?)!! > value
    }

  private fun matchesProtocol(protocol: Protocol?): Matcher<Response?> =
    object : BaseMatcher<Response?>() {
      override fun describeTo(description: Description?) {

 the Maven Repository Metadata file contains 3 different sets of metadata:

 [[1]] in a "groupId" directory: a "groupId" directory may contain Maven plugins artifacts, which are described in metadata's <<<plugins>>> element,

 [[2]] in a "groupId/artifactId" directory: metadata describes <<<groupId>>>, <<<artifactId>>> and <<<versioning>>> element that
       gives data about available versions (<<<latest>>>, <<<release>>>, <<<versions>>> list and <<<lastUpdated>>>),

          <name>licenses</name>
          <version>3.0.0+</version>
          <description>
            <![CDATA[
            This element describes all the licenses for this project.
            Each license is described by a {@code license} element, which
            is then described by additional elements.
            Projects should only list the license(s) that applies to the project

# Using TensorFlow Securely

This document discusses the TensorFlow security model. It describes the security
risks to consider when using models, checkpoints or input data for training or
serving. We also provide guidelines on what constitutes a vulnerability in
TensorFlow and how to report them.

This document applies to other repositories in the TensorFlow organization,
covering security practices for the entirety of the TensorFlow ecosystem.

That extra info will be added as-is to the output **JSON Schema** for that model, and it will be used in the API docs.

You can use the attribute `model_config` that takes a `dict` as described in [Pydantic's docs: Configuration](https://docs.pydantic.dev/latest/api/config/).

	}
}

// minioCollector is the Custom Collector
type minioCollector struct {
	desc *prometheus.Desc
}

// Describe sends the super-set of all possible descriptors of metrics
func (c *minioCollector) Describe(ch chan<- *prometheus.Desc) {
	ch <- c.desc
}

// Collect is called by the Prometheus registry when collecting metrics.

  public static final MediaType HTML_UTF_8 = createConstantUtf8(TEXT_TYPE, "html");
  public static final MediaType I_CALENDAR_UTF_8 = createConstantUtf8(TEXT_TYPE, "calendar");

  /**
   * As described in <a href="https://www.rfc-editor.org/rfc/rfc7763.html">RFC 7763</a>, this
   * constant ({@code text/markdown}) is used for Markdown documents.
   *
   * @since 33.3.0
   */

    Form, and Modifications of such Source Code Form, in each case
    including portions thereof.

1.5. "Incompatible With Secondary Licenses"
    means

    (a) that the initial Contributor has attached the notice described
        in Exhibit B to the Covered Software; or

    (b) that the Covered Software was made available under the terms of
        version 1.1 or earlier of the License, but not also under the

      description: If so, how does this proposal differ?
      placeholder: |
       Yes or No

       If yes, 
        1. Mention the related proposals 
        2. then describe how this proposal differs       
    validations:
      required: true

  - type: textarea
    id: error-handling-proposal
    attributes:
      label: Does this affect error handling?