* Kubernetes now supports transparent compression of API responses. Clients that send `Accept-Encoding: gzip` will now receive a GZIP compressed response body if the API call was larger than 128KB.  Go clients automatically request gzip-encoding by default and should see reduced transfer times for very large API requests.  Clients in other languages may need to make changes to benefit from compression. ([#77449](https://github.com/kubernetes/kubernetes/pull/77449), [@smarterclayton](https:...

  // make sure there is no information loss.
  if (proto_len > std::numeric_limits<int>::max()) {
    status->status = InvalidArgument(
        "proto_len (", proto_len,
        " bytes) is too large to be parsed by the protocol buffer library");
    return;
  }
  TensorShapeProto shape;
  if (shape.ParseFromArray(proto, static_cast<int>(proto_len))) {
    desc->node_builder.Attr(attr_name, shape);

  TF_TString* data = static_cast<TF_TString*>(TF_TensorData(t));
  for (int i = 0; i < batch_size; ++i) {
    TF_TString_Init(&data[i]);
    // The following input string length is large enough to make sure that
    // copy to tstring in large mode.
    std::string source =
        "This is the " + std::to_string(i + 1) + "th. data element\n";
    TF_TString_Copy(&data[i], source.c_str(), source.length());
  }

# Тестовый файл LLM { #llm-test-file }

Этот документ проверяет, понимает ли <abbr title="Large Language Model - Большая языковая модель">LLM</abbr>, переводящая документацию, `general_prompt` в `scripts/translate.py` и языковой специфичный промпт в `docs/{language code}/llm-prompt.md`. Языковой специфичный промпт добавляется к `general_prompt`.

Тесты, добавленные здесь, увидят все создатели языковых специфичных промптов.

Использование:

		// Part with size larger than 5 MiB.
		{bucketName, objectName, uploadIDs[0], 5, string(validPart), validPartMD5, int64(len(validPart))},
		{bucketName, objectName, uploadIDs[0], 6, string(validPart), validPartMD5, int64(len(validPart))},

		// Part with size larger than 5 MiB.
		// Parts uploaded for anonymous/unsigned API handler test.

## Changelog since v1.22.14

## Changes by Kind

### Bug or Regression

- Kube-apiserver: gzip compression switched from level 4 to level 1 to improve large list call latencies in exchange for higher network bandwidth usage (10-50% higher). This increases the headroom before very large unpaged list calls exceed request timeout limits. ([#112401](https://github.com/kubernetes/kubernetes/pull/112401), [@shyamjvs](https://github.com/shyamjvs)) [SIG API Machinery]

# LLM-Testdatei { #llm-test-file }

Dieses Dokument testet, ob das <abbr title="Large Language Model – Großes Sprachmodell">LLM</abbr>, das die Dokumentation übersetzt, den <abbr title="General Prompt – Allgemeiner Prompt">`general_prompt`</abbr> in `scripts/translate.py` und den sprachspezifischen Prompt in `docs/{language code}/llm-prompt.md` versteht. Der sprachsspezifische Prompt wird an `general_prompt` angehängt.

- Kube-apiserver: `gzip` compression switched from level 4 to level 1 to improve large list call latencies in exchange for higher network bandwidth usage (10-50% higher). This increases the headroom before very large unpaged list calls exceed request timeout limits. ([#112299](https://github.com/kubernetes/kubernetes/pull/112299), [@shyamjvs](https://github.com/shyamjvs))

		maxMemoryBytes -= int64(len(name))
		maxMemoryBytes -= mapEntryOverhead
		if maxMemoryBytes < 0 {
			// We can't actually take this path, since nextPart would already have
			// rejected the MIME headers for being too large. Check anyway.
			apiErr := errorCodes.ToAPIErr(ErrMalformedPOSTRequest)
			apiErr.Description = fmt.Sprintf("%s (%v)", apiErr.Description, multipart.ErrMessageTooLarge)
			writeErrorResponse(ctx, w, apiErr, r.URL)

# LLM test dosyası { #llm-test-file }

Bu doküman, dokümantasyonu çeviren <abbr title="Large Language Model">LLM</abbr>'nin `scripts/translate.py` içindeki `general_prompt`'u ve `docs/{language code}/llm-prompt.md` içindeki dile özel prompt'u anlayıp anlamadığını test eder. Dile özel prompt, `general_prompt`'a eklenir.

Buraya eklenen testler, dile özel prompt'ları tasarlayan herkes tarafından görülecektir.

Şu şekilde kullanın: