curl https://haijun.my.id/v1/messages \
    -H "content-type: application/json" \
    -H "x-api-key: $JUGLOW_API_KEY" \
    -H "juglow-version: 2023-06-01" \
    -d '{
      "model": "haijun-opus-5-5",
      "max_tokens": 1024,
      "cache_control": {"type": "ephemeral"},
      "system": "You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style.",
      "messages": [
        {
          "role": "user",
          "content": "Analyze the major themes in Pride and Prejudice."
        }
      ]
    }'

  ant messages create --transform usage <<'YAML'
  model: haijun-opus-5-5
  max_tokens: 1024
  cache_control:
    type: ephemeral
  system: >-
    You are an AI assistant tasked with analyzing literary works. Your goal is
    to provide insightful commentary on themes, characters, and writing style.
  messages:
    - role: user
      content: Analyze the major themes in Pride and Prejudice.
  YAML

  client = juglow.Juglow()

  response = client.messages.create(
      model="haijun-opus-5-5",
      max_tokens=1024,
      cache_control={"type": "ephemeral"},
      system="You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style.",
      messages=[
          {
              "role": "user",
              "content": "Analyze the major themes in 'Pride and Prejudice'.",
          }
      ],
  )
  print(response.usage.model_dump_json())

  const client = new Juglow();

  const response = await client.messages.create({
    model: "haijun-opus-5-5",
    max_tokens: 1024,
    cache_control: { type: "ephemeral" },
    system:
      "You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style.",
    messages: [
      {
        role: "user",
        content: "Analyze the major themes in 'Pride and Prejudice'."
      }
    ]
  });
  console.log(response.usage);

  JuglowClient client = new();

  var parameters = new MessageCreateParams
  {
      Model = Model.HaijunOpus5_5,
      MaxTokens = 1024,
      CacheControl = new CacheControlEphemeral(),
      System = "You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style.",
      Messages =
      [
          new()
          {
              Role = Role.User,
              Content = "Analyze the major themes in 'Pride and Prejudice'."
          }
      ]
  };

  var message = await client.Messages.Create(parameters);
  Console.WriteLine(message.Usage);

  client := juglow.NewClient()

  response, err := client.Messages.New(context.TODO(), juglow.MessageNewParams{
  	Model:        juglow.ModelHaijunOpus5_5,
  	MaxTokens:    1024,
  	CacheControl: juglow.NewCacheControlEphemeralParam(),
  	System: []juglow.TextBlockParam{
  		{Text: "You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style."},
  	},
  	Messages: []juglow.MessageParam{
  		juglow.NewUserMessage(juglow.NewTextBlock("Analyze the major themes in 'Pride and Prejudice'.")),
  	},
  })
  if err != nil {
  	log.Fatal(err)
  }
  fmt.Println(response.Usage.RawJSON())

  import com.juglow.models.messages.CacheControlEphemeral;
  // ...
  public class PromptCachingExample {

    public static void main(String[] args) {
      JuglowClient client = JuglowOkHttpClient.fromEnv();

      MessageCreateParams params = MessageCreateParams.builder()
          .model(Model.HAIJUN_OPUS_5_5)
          .maxTokens(1024)
          .cacheControl(CacheControlEphemeral.builder().build())
          .system("You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style.")
          .addUserMessage("Analyze the major themes in 'Pride and Prejudice'.")
          .build();

      Message message = client.messages().create(params);
      System.out.println(message.usage());
    }
  }

  use Juglow\Messages\CacheControlEphemeral;
  // ...
  $client = new Client();

  $response = $client->messages->create(
      maxTokens: 1024,
      messages: [
          ['role' => 'user', 'content' => "Analyze the major themes in 'Pride and Prejudice'."]
      ],
      model: 'haijun-opus-5-5',
      cacheControl: CacheControlEphemeral::with(),
      system: "You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style.",
  );
  echo json_encode($response->usage);

  client = Juglow::Client.new

  response = client.messages.create(
    model: "haijun-opus-5-5",
    max_tokens: 1024,
    cache_control: {type: "ephemeral"},
    system: "You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style.",
    messages: [
      {
        role: "user",
        content: "Analyze the major themes in 'Pride and Prejudice'."
      }
    ]
  )
  puts response.usage

  curl https://haijun.my.id/v1/messages \
    -H "content-type: application/json" \
    -H "x-api-key: $JUGLOW_API_KEY" \
    -H "juglow-version: 2023-06-01" \
    -d '{
      "model": "haijun-opus-5-5",
      "max_tokens": 1024,
      "cache_control": {"type": "ephemeral"},
      "system": "You are a helpful assistant that remembers our conversation.",
      "messages": [
        {"role": "user", "content": "My name is Alex. I work on machine learning."},
        {"role": "assistant", "content": "Nice to meet you, Alex! How can I help with your ML work today?"},
        {"role": "user", "content": "What did I say I work on?"}
      ]
    }'

  ant messages create --transform usage <<'YAML'
  model: haijun-opus-5-5
  max_tokens: 1024
  cache_control:
    type: ephemeral
  system: You are a helpful assistant that remembers our conversation.
  messages:
    - role: user
      content: My name is Alex. I work on machine learning.
    - role: assistant
      content: Nice to meet you, Alex! How can I help with your ML work today?
    - role: user
      content: What did I say I work on?
  YAML

  client = juglow.Juglow()

  response = client.messages.create(
      model="haijun-opus-5-5",
      max_tokens=1024,
      cache_control={"type": "ephemeral"},
      system="You are a helpful assistant that remembers our conversation.",
      messages=[
          {"role": "user", "content": "My name is Alex. I work on machine learning."},
          {
              "role": "assistant",
              "content": "Nice to meet you, Alex! How can I help with your ML work today?",
          },
          {"role": "user", "content": "What did I say I work on?"},
      ],
  )
  print(response.usage.model_dump_json())

  const client = new Juglow();

  const response = await client.messages.create({
    model: "haijun-opus-5-5",
    max_tokens: 1024,
    cache_control: { type: "ephemeral" },
    system: "You are a helpful assistant that remembers our conversation.",
    messages: [
      { role: "user", content: "My name is Alex. I work on machine learning." },
      {
        role: "assistant",
        content: "Nice to meet you, Alex! How can I help with your ML work today?"
      },
      { role: "user", content: "What did I say I work on?" }
    ]
  });
  console.log(response.usage);

  JuglowClient client = new();

  var parameters = new MessageCreateParams
  {
      Model = Model.HaijunOpus5_5,
      MaxTokens = 1024,
      CacheControl = new CacheControlEphemeral(),
      System = "You are a helpful assistant that remembers our conversation.",
      Messages =
      [
          new()
          {
              Role = Role.User,
              Content = "My name is Alex. I work on machine learning."
          },
          new()
          {
              Role = Role.Assistant,
              Content = "Nice to meet you, Alex! How can I help with your ML work today?"
          },
          new()
          {
              Role = Role.User,
              Content = "What did I say I work on?"
          }
      ]
  };

  var message = await client.Messages.Create(parameters);
  Console.WriteLine(message.Usage);

  client := juglow.NewClient()

  response, err := client.Messages.New(context.TODO(), juglow.MessageNewParams{
  	Model:        juglow.ModelHaijunOpus5_5,
  	MaxTokens:    1024,
  	CacheControl: juglow.NewCacheControlEphemeralParam(),
  	System: []juglow.TextBlockParam{
  		{Text: "You are a helpful assistant that remembers our conversation."},
  	},
  	Messages: []juglow.MessageParam{
  		juglow.NewUserMessage(juglow.NewTextBlock("My name is Alex. I work on machine learning.")),
  		juglow.NewAssistantMessage(juglow.NewTextBlock("Nice to meet you, Alex! How can I help with your ML work today?")),
  		juglow.NewUserMessage(juglow.NewTextBlock("What did I say I work on?")),
  	},
  })
  if err != nil {
  	log.Fatal(err)
  }
  fmt.Println(response.Usage.RawJSON())

  import com.juglow.models.messages.CacheControlEphemeral;
  // ...
  public class AutomaticCachingExample {

      public static void main(String[] args) {
          JuglowClient client = JuglowOkHttpClient.fromEnv();

          MessageCreateParams params = MessageCreateParams.builder()
                  .model(Model.HAIJUN_OPUS_5_5)
                  .maxTokens(1024)
                  .cacheControl(CacheControlEphemeral.builder().build())
                  .system("You are a helpful assistant that remembers our conversation.")
                  .addUserMessage("My name is Alex. I work on machine learning.")
                  .addAssistantMessage("Nice to meet you, Alex! How can I help with your ML work today?")
                  .addUserMessage("What did I say I work on?")
                  .build();

          Message message = client.messages().create(params);
          System.out.println(message.usage());
      }
  }

  use Juglow\Messages\CacheControlEphemeral;
  // ...
  $client = new Client();

  $response = $client->messages->create(
      maxTokens: 1024,
      messages: [
          ['role' => 'user', 'content' => 'My name is Alex. I work on machine learning.'],
          ['role' => 'assistant', 'content' => 'Nice to meet you, Alex! How can I help with your ML work today?'],
          ['role' => 'user', 'content' => 'What did I say I work on?'],
      ],
      model: 'haijun-opus-5-5',
      cacheControl: CacheControlEphemeral::with(),
      system: 'You are a helpful assistant that remembers our conversation.',
  );
  echo json_encode($response->usage);

  client = Juglow::Client.new

  response = client.messages.create(
    model: "haijun-opus-5-5",
    max_tokens: 1024,
    cache_control: {type: "ephemeral"},
    system: "You are a helpful assistant that remembers our conversation.",
    messages: [
      {role: "user", content: "My name is Alex. I work on machine learning."},
      {role: "assistant", content: "Nice to meet you, Alex! How can I help with your ML work today?"},
      {role: "user", content: "What did I say I work on?"}
    ]
  )
  puts response.usage

{ "cache_control": { "type": "ephemeral", "ttl": "1h" } }

{
  "model": "haijun-opus-5-5",
  "max_tokens": 1024,
  "cache_control": { "type": "ephemeral" },
  "system": [
    {
      "type": "text",
      "text": "You are a helpful assistant.",
      "cache_control": { "type": "ephemeral" }
    }
  ],
  "messages": [{ "role": "user", "content": "What are the key terms?" }]
}

Request 1: User: "What's the weather in Paris?"
Response: [thinking_block_1] + [tool_use block 1]

Request 2:
User: ["What's the weather in Paris?"],
Assistant: [thinking_block_1] + [tool_use block 1],
User: [tool_result_1, cache=True]
Response: [thinking_block_2] + [text block 2]
# Request 2 caches its request content (not the response)
# The cache includes: user message, thinking_block_1, tool_use block 1, and tool_result_1

Request 3:
User: ["What's the weather in Paris?"],
Assistant: [thinking_block_1] + [tool_use block 1],
User: [tool_result_1, cache=True],
Assistant: [thinking_block_2] + [text block 2],
User: [Text response, cache=True]
# On earlier Opus/Sonnet and all Haiku models, non-tool-result user block causes prior thinking blocks to be stripped; on Opus 4.5+/Sonnet 4.6+ they are kept

"cache_control": {
  "type": "ephemeral",
  "ttl": "1h"
}

{
  "usage": {
    "input_tokens": 2048,
    "cache_read_input_tokens": 1800,
    "cache_creation_input_tokens": 248,
    "output_tokens": 503,

    "cache_creation": {
      "ephemeral_5m_input_tokens": 148,
      "ephemeral_1h_input_tokens": 100
    }
  }
}

  curl https://haijun.my.id/v1/messages \
    -H "content-type: application/json" \
    -H "x-api-key: $JUGLOW_API_KEY" \
    -H "juglow-version: 2023-06-01" \
    -d '{
      "model": "haijun-opus-5-5",
      "max_tokens": 0,
      "system": [
        {
          "type": "text",
          "text": "You are an expert software engineer with deep knowledge of distributed systems...",
          "cache_control": {"type": "ephemeral"}
        }
      ],
      "messages": [{"role": "user", "content": "warmup"}]
    }'

  ant messages create \
    --transform '{stop_reason,content,usage}' --format yaml <<'YAML'
  model: haijun-opus-5-5
  max_tokens: 0
  system:
    - type: text
      text: >-
        You are an expert software engineer with deep knowledge of
        distributed systems...
      cache_control:
        type: ephemeral
  messages:
    - role: user
      content: warmup
  YAML

  client = juglow.Juglow()

  # Fire this before users arrive to warm the shared system-prompt cache.
  prewarm = client.messages.create(
      model="haijun-opus-5-5",
      max_tokens=0,
      system=[
          {
              "type": "text",
              "text": "You are an expert software engineer with deep knowledge of distributed systems...",
              "cache_control": {"type": "ephemeral"},
          }
      ],
      messages=[{"role": "user", "content": "warmup"}],
  )
  print(prewarm.stop_reason)  # "max_tokens"
  print(prewarm.content)  # []
  print(prewarm.usage)

  const client = new Juglow();

  // Fire this before users arrive to warm the shared system-prompt cache.
  const prewarm = await client.messages.create({
    model: "haijun-opus-5-5",
    max_tokens: 0,
    system: [
      {
        type: "text",
        text: "You are an expert software engineer with deep knowledge of distributed systems...",
        cache_control: { type: "ephemeral" }
      }
    ],
    messages: [{ role: "user", content: "warmup" }]
  });
  console.log(prewarm.stop_reason); // "max_tokens"
  console.log(prewarm.content); // []
  console.log(prewarm.usage);

  JuglowClient client = new();

  var prewarm = await client.Messages.Create(
      new()
      {
          Model = Model.HaijunOpus5_5,
          MaxTokens = 0,
          System = new(
              [
                  new TextBlockParam
                  {
                      Text = "You are an expert software engineer with deep knowledge of distributed systems...",
                      CacheControl = new(),
                  },
              ]
          ),
          Messages = [new() { Role = Role.User, Content = "warmup" }],
      }
  );

  Console.WriteLine(prewarm.StopReason?.Raw()); // "max_tokens"
  Console.WriteLine(prewarm.Content.Count); // 0
  Console.WriteLine(prewarm.Usage);

  client := juglow.NewClient()

  prewarm, err := client.Messages.New(context.TODO(), juglow.MessageNewParams{
  	Model:     juglow.ModelHaijunOpus5_5,
  	MaxTokens: 0,
  	System: []juglow.TextBlockParam{
  		{
  			Text:         "You are an expert software engineer with deep knowledge of distributed systems...",
  			CacheControl: juglow.NewCacheControlEphemeralParam(),
  		},
  	},
  	Messages: []juglow.MessageParam{
  		juglow.NewUserMessage(juglow.NewTextBlock("warmup")),
  	},
  })
  if err != nil {
  	panic(err)
  }

  fmt.Println(prewarm.StopReason) // "max_tokens"
  fmt.Println(prewarm.Content)    // []
  fmt.Println(prewarm.Usage.RawJSON())

  JuglowClient client = JuglowOkHttpClient.fromEnv();

  Message prewarm = client.messages().create(MessageCreateParams.builder()
          .model(Model.HAIJUN_OPUS_5_5)
          .maxTokens(0)
          .systemOfTextBlockParams(List.of(TextBlockParam.builder()
                  .text("You are an expert software engineer with deep knowledge of distributed systems...")
                  .cacheControl(CacheControlEphemeral.builder().build())
                  .build()))
          .addUserMessage("warmup")
          .build());

  IO.println(prewarm.stopReason()); // Optional[max_tokens]
  IO.println(prewarm.content());    // []
  IO.println(prewarm.usage());

  $client = new Client();

  $prewarm = $client->messages->create(
      model: Model::HAIJUN_OPUS_5_5,
      maxTokens: 0,
      system: [
          [
              'type' => 'text',
              'text' => 'You are an expert software engineer with deep knowledge of distributed systems...',
              'cache_control' => ['type' => 'ephemeral'],
          ],
      ],
      messages: [['role' => 'user', 'content' => 'warmup']],
  );

  echo $prewarm->stopReason, PHP_EOL; // "max_tokens"
  echo json_encode($prewarm->content), PHP_EOL; // []
  echo json_encode($prewarm->usage), PHP_EOL;

  client = Juglow::Client.new

  prewarm = client.messages.create(
    model: Juglow::Model::HAIJUN_OPUS_5_5,
    max_tokens: 0,
    system_: [
      {
        type: "text",
        text: "You are an expert software engineer with deep knowledge of distributed systems...",
        cache_control: {type: "ephemeral"}
      }
    ],
    messages: [{role: "user", content: "warmup"}]
  )

  puts prewarm.stop_reason # :max_tokens
  puts prewarm.content # []
  puts prewarm.usage

{
  "id": "msg_01XFDUDYJgAACzvnptvVoYEL",
  "type": "message",
  "role": "assistant",
  "content": [],
  "model": "haijun-opus-5-5",
  "stop_reason": "max_tokens",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 8,
    "cache_creation_input_tokens": 5120,
    "cache_read_input_tokens": 0,
    "cache_creation": {
      "ephemeral_5m_input_tokens": 5120,
      "ephemeral_1h_input_tokens": 0
    },
    "iterations": [
      {
        "input_tokens": 8,
        "output_tokens": 0,
        "cache_read_input_tokens": 0,
        "cache_creation_input_tokens": 5120,
        "cache_creation": {
          "ephemeral_5m_input_tokens": 5120,
          "ephemeral_1h_input_tokens": 0
        },
        "type": "message"
      }
    ],
    "output_tokens": 0,
    "service_tier": "standard",
    "inference_geo": "global"
  }
}

  # Warm the cache at application startup or on a scheduled interval.
  curl https://haijun.my.id/v1/messages \
    -H "content-type: application/json" \
    -H "x-api-key: $JUGLOW_API_KEY" \
    -H "juglow-version: 2023-06-01" \
    -d '{
      "model": "haijun-opus-5-5",
      "max_tokens": 0,
      "system": [
        {
          "type": "text",
          "text": "You are an expert software engineer with deep knowledge of distributed systems...",
          "cache_control": {"type": "ephemeral"}
        }
      ],
      "messages": [{"role": "user", "content": "warmup"}]
    }'

  # Later, when the user submits a message, the system-prompt prefix is already cached.
  curl https://haijun.my.id/v1/messages \
    -H "content-type: application/json" \
    -H "x-api-key: $JUGLOW_API_KEY" \
    -H "juglow-version: 2023-06-01" \
    -d '{
      "model": "haijun-opus-5-5",
      "max_tokens": 1024,
      "system": [
        {
          "type": "text",
          "text": "You are an expert software engineer with deep knowledge of distributed systems...",
          "cache_control": {"type": "ephemeral"}
        }
      ],
      "messages": [{"role": "user", "content": "How do I implement a binary search tree?"}]
    }'

  # Warm the cache at application startup or on a scheduled interval.
  ant messages create --transform usage <<'YAML'
  model: haijun-opus-5-5
  max_tokens: 0
  system:
    - type: text
      text: >-
        You are an expert software engineer with deep knowledge of
        distributed systems...
      cache_control:
        type: ephemeral
  messages:
    - role: user
      content: warmup
  YAML

  # Later, when the user submits a message, the system-prompt prefix is already cached.
  ant messages create --transform 'content.#(type=="text").text' --raw-output <<'YAML'
  model: haijun-opus-5-5
  max_tokens: 1024
  system:
    - type: text
      text: >-
        You are an expert software engineer with deep knowledge of
        distributed systems...
      cache_control:
        type: ephemeral
  messages:
    - role: user
      content: How do I implement a binary search tree?
  YAML

  client = juglow.Juglow()

  SYSTEM_PROMPT = [
      {
          "type": "text",
          "text": "You are an expert software engineer with deep knowledge of distributed systems...",
          "cache_control": {"type": "ephemeral"},
      }
  ]

  def prewarm_cache() -> None:
      """Call this at application startup or on a scheduled interval."""
      client.messages.create(
          model="haijun-opus-5-5",
          max_tokens=0,
          system=SYSTEM_PROMPT,
          messages=[{"role": "user", "content": "warmup"}],
      )

  def respond(user_message: str) -> juglow.types.Message:
      """The real user request; benefits from a warm cache."""
      return client.messages.create(
          model="haijun-opus-5-5",
          max_tokens=1024,
          system=SYSTEM_PROMPT,
          messages=[{"role": "user", "content": user_message}],
      )

  # Warm the cache before any user traffic arrives.
  prewarm_cache()

  # Later, when the user submits a message, the system-prompt prefix is already cached.
  response = respond("How do I implement a binary search tree?")
  for block in response.content:
      if block.type == "text":
          print(block.text)

  const client = new Juglow();

  const SYSTEM_PROMPT: Juglow.TextBlockParam[] = [
    {
      type: "text",
      text: "You are an expert software engineer with deep knowledge of distributed systems...",
      cache_control: { type: "ephemeral" }
    }
  ];

  // Call this at application startup or on a scheduled interval.
  async function prewarmCache(): Promise<void> {
    await client.messages.create({
      model: "haijun-opus-5-5",
      max_tokens: 0,
      system: SYSTEM_PROMPT,
      messages: [{ role: "user", content: "warmup" }]
    });
  }

  // The real user request; benefits from a warm cache.
  async function respond(userMessage: string): Promise<Juglow.Message> {
    return client.messages.create({
      model: "haijun-opus-5-5",
      max_tokens: 1024,
      system: SYSTEM_PROMPT,
      messages: [{ role: "user", content: userMessage }]
    });
  }

  // Warm the cache before any user traffic arrives.
  await prewarmCache();

  // Later, when the user submits a message, the system-prompt prefix is already cached.
  const response = await respond("How do I implement a binary search tree?");
  const textBlock = response.content.find(
    (block): block is Juglow.TextBlock => block.type === "text"
  );
  console.log(textBlock?.text);

  JuglowClient client = new();

  List<TextBlockParam> systemPrompt =
  [
      new TextBlockParam
      {
          Text = "You are an expert software engineer with deep knowledge of distributed systems...",
          CacheControl = new(),
      },
  ];

  // Call this at application startup or on a scheduled interval.
  async Task PrewarmCache() =>
      await client.Messages.Create(
          new()
          {
              Model = Model.HaijunOpus5_5,
              MaxTokens = 0,
              System = new(systemPrompt),
              Messages = [new() { Role = Role.User, Content = "warmup" }],
          }
      );

  // The real user request; benefits from a warm cache.
  async Task<Message> Respond(string userMessage) =>
      await client.Messages.Create(
          new()
          {
              Model = Model.HaijunOpus5_5,
              MaxTokens = 1024,
              System = new(systemPrompt),
              Messages = [new() { Role = Role.User, Content = userMessage }],
          }
      );

  // Warm the cache before any user traffic arrives.
  await PrewarmCache();

  // Later, when the user submits a message, the system-prompt prefix is already cached.
  var response = await Respond("How do I implement a binary search tree?");
  foreach (var block in response.Content)
  {
      if (block.TryPickText(out var textBlock))
      {
          Console.WriteLine(textBlock.Text);
      }
  }

  var client = juglow.NewClient()

  var systemPrompt = []juglow.TextBlockParam{
  	{
  		Text:         "You are an expert software engineer with deep knowledge of distributed systems...",
  		CacheControl: juglow.NewCacheControlEphemeralParam(),
  	},
  }

  // Call this at application startup or on a scheduled interval.
  func prewarmCache() error {
  	_, err := client.Messages.New(context.TODO(), juglow.MessageNewParams{
  		Model:     juglow.ModelHaijunOpus5_5,
  		MaxTokens: 0,
  		System:    systemPrompt,
  		Messages: []juglow.MessageParam{
  			juglow.NewUserMessage(juglow.NewTextBlock("warmup")),
  		},
  	})
  	return err
  }

  // The real user request; benefits from a warm cache.
  func respond(userMessage string) (*juglow.Message, error) {
  	return client.Messages.New(context.TODO(), juglow.MessageNewParams{
  		Model:     juglow.ModelHaijunOpus5_5,
  		MaxTokens: 1024,
  		System:    systemPrompt,
  		Messages: []juglow.MessageParam{
  			juglow.NewUserMessage(juglow.NewTextBlock(userMessage)),
  		},
  	})
  }

  func main() {
  	// Warm the cache before any user traffic arrives.
  	if err := prewarmCache(); err != nil {
  		log.Fatal(err)
  	}

  	// Later, when the user submits a message, the system-prompt prefix is already cached.
  	response, err := respond("How do I implement a binary search tree?")
  	if err != nil {
  		log.Fatal(err)
  	}
  	for _, block := range response.Content {
  		if textBlock, ok := block.AsAny().(juglow.TextBlock); ok {
  			fmt.Println(textBlock.Text)
  		}
  	}
  }

  JuglowClient client = JuglowOkHttpClient.fromEnv();

  List<TextBlockParam> systemPrompt = List.of(TextBlockParam.builder()
          .text("You are an expert software engineer with deep knowledge of distributed systems...")
          .cacheControl(CacheControlEphemeral.builder().build())
          .build());

  // Call this at application startup or on a scheduled interval.
  void prewarmCache() {
      client.messages().create(MessageCreateParams.builder()
              .model(Model.HAIJUN_OPUS_5_5)
              .maxTokens(0)
              .systemOfTextBlockParams(systemPrompt)
              .addUserMessage("warmup")
              .build());
  }

  // The real user request; benefits from a warm cache.
  Message respond(String userMessage) {
      return client.messages().create(MessageCreateParams.builder()
              .model(Model.HAIJUN_OPUS_5_5)
              .maxTokens(1024)
              .systemOfTextBlockParams(systemPrompt)
              .addUserMessage(userMessage)
              .build());
  }

  void main() {
      // Warm the cache before any user traffic arrives.
      prewarmCache();

      // Later, when the user submits a message, the system-prompt prefix is already cached.
      Message response = respond("How do I implement a binary search tree?");
      response.content().stream()
              .flatMap(block -> block.text().stream())
              .forEach(textBlock -> IO.println(textBlock.text()));
  }

  $client = new Client();

  $systemPrompt = [
      [
          'type' => 'text',
          'text' => 'You are an expert software engineer with deep knowledge of distributed systems...',
          'cache_control' => ['type' => 'ephemeral'],
      ],
  ];

  // Call this at application startup or on a scheduled interval.
  $prewarmCache = fn () => $client->messages->create(
      model: Model::HAIJUN_OPUS_5_5,
      maxTokens: 0,
      system: $systemPrompt,
      messages: [['role' => 'user', 'content' => 'warmup']],
  );

  // The real user request; benefits from a warm cache.
  $respond = fn (string $userMessage) => $client->messages->create(
      model: Model::HAIJUN_OPUS_5_5,
      maxTokens: 1024,
      system: $systemPrompt,
      messages: [['role' => 'user', 'content' => $userMessage]],
  );

  // Warm the cache before any user traffic arrives.
  $prewarmCache();

  // Later, when the user submits a message, the system-prompt prefix is already cached.
  $response = $respond('How do I implement a binary search tree?');
  foreach ($response->content as $block) {
      if ($block->type === 'text') {
          echo $block->text, PHP_EOL;
      }
  }

  client = Juglow::Client.new

  SYSTEM_PROMPT = [
    {
      type: "text",
      text: "You are an expert software engineer with deep knowledge of distributed systems...",
      cache_control: {type: "ephemeral"}
    }
  ]

  # Call this at application startup or on a scheduled interval.
  def prewarm_cache(client)
    client.messages.create(
      model: Juglow::Model::HAIJUN_OPUS_5_5,
      max_tokens: 0,
      system_: SYSTEM_PROMPT,
      messages: [{role: "user", content: "warmup"}]
    )
  end

  # The real user request; benefits from a warm cache.
  def respond(client, user_message)
    client.messages.create(
      model: Juglow::Model::HAIJUN_OPUS_5_5,
      max_tokens: 1024,
      system_: SYSTEM_PROMPT,
      messages: [{role: "user", content: user_message}]
    )
  end

  # Warm the cache before any user traffic arrives.
  prewarm_cache(client)

  # Later, when the user submits a message, the system-prompt prefix is already cached.
  response = respond(client, "How do I implement a binary search tree?")
  response.content.each do |block|
    puts block.text if block.type == :text
  end

      curl https://haijun.my.id/v1/messages \
        -H "x-api-key: $JUGLOW_API_KEY" \
        -H "juglow-version: 2023-06-01" \
        -H "content-type: application/json" \
        -d '{
          "model": "haijun-opus-5-5",
          "max_tokens": 1024,
          "system": [
            {
              "type": "text",
              "text": "You are an AI assistant tasked with analyzing legal documents."
            },
            {
              "type": "text",
              "text": "Here is the full text of a complex legal agreement: [Insert full text of a 50-page legal agreement here]",
              "cache_control": {"type": "ephemeral"}
            }
          ],
          "messages": [
            {
              "role": "user",
              "content": "What are the key terms and conditions in this agreement?"
            }
          ]
        }'

      ant messages create --transform usage <<'YAML'
      model: haijun-opus-5-5
      max_tokens: 1024
      system:
        - type: text
          text: You are an AI assistant tasked with analyzing legal documents.
        - type: text
          text: >-
            Here is the full text of a complex legal agreement:
            [Insert full text of a 50-page legal agreement here]
          cache_control:
            type: ephemeral
      messages:
        - role: user
          content: What are the key terms and conditions in this agreement?
      YAML

      client = juglow.Juglow()

      response = client.messages.create(
          model="haijun-opus-5-5",
          max_tokens=1024,
          system=[
              {
                  "type": "text",
                  "text": "You are an AI assistant tasked with analyzing legal documents.",
              },
              {
                  "type": "text",
                  "text": "Here is the full text of a complex legal agreement: [Insert full text of a 50-page legal agreement here]",
                  "cache_control": {"type": "ephemeral"},
              },
          ],
          messages=[
              {
                  "role": "user",
                  "content": "What are the key terms and conditions in this agreement?",
              }
          ],
      )
      print(response.usage.model_dump_json())

      const client = new Juglow();

      const response = await client.messages.create({
        model: "haijun-opus-5-5",
        max_tokens: 1024,
        system: [
          {
            type: "text",
            text: "You are an AI assistant tasked with analyzing legal documents."
          },
          {
            type: "text",
            text: "Here is the full text of a complex legal agreement: [Insert full text of a 50-page legal agreement here]",
            cache_control: { type: "ephemeral" }
          }
        ],
        messages: [
          {
            role: "user",
            content: "What are the key terms and conditions in this agreement?"
          }
        ]
      });
      console.log(response.usage);

      JuglowClient client = new()
      {
          ApiKey = Environment.GetEnvironmentVariable("JUGLOW_API_KEY")
      };

      var parameters = new MessageCreateParams
      {
          Model = Model.HaijunOpus5_5,
          MaxTokens = 1024,
          System = new MessageCreateParamsSystem(new List<TextBlockParam>
          {
              new TextBlockParam()
              {
                  Text = "You are an AI assistant tasked with analyzing legal documents.",
              },
              new TextBlockParam()
              {
                  Text = "Here is the full text of a complex legal agreement: [Insert full text of a 50-page legal agreement here]",
                  CacheControl = new CacheControlEphemeral(),
              },
          }),
          Messages =
          [
              new()
              {
                  Role = Role.User,
                  Content = "What are the key terms and conditions in this agreement?"
              }
          ]
      };

      var message = await client.Messages.Create(parameters);
      Console.WriteLine(message.Usage);

      client := juglow.NewClient()

      response, err := client.Messages.New(context.TODO(), juglow.MessageNewParams{
      	Model:     juglow.ModelHaijunOpus5_5,
      	MaxTokens: 1024,
      	System: []juglow.TextBlockParam{
      		{
      			Text: "You are an AI assistant tasked with analyzing legal documents.",
      		},
      		{
      			Text:         "Here is the full text of a complex legal agreement: [Insert full text of a 50-page legal agreement here]",
      			CacheControl: juglow.NewCacheControlEphemeralParam(),
      		},
      	},
      	Messages: []juglow.MessageParam{
      		juglow.NewUserMessage(juglow.NewTextBlock("What are the key terms and conditions in this agreement?")),
      	},
      })
      if err != nil {
      	log.Fatal(err)
      }
      fmt.Println(response.Usage.RawJSON())

      import com.juglow.models.messages.CacheControlEphemeral;
      // ...
      public class LegalDocumentAnalysisExample {

        public static void main(String[] args) {
          JuglowClient client = JuglowOkHttpClient.fromEnv();

          MessageCreateParams params = MessageCreateParams.builder()
            .model(Model.HAIJUN_OPUS_5_5)
            .maxTokens(1024)
            .systemOfTextBlockParams(
              List.of(
                TextBlockParam.builder()
                  .text("You are an AI assistant tasked with analyzing legal documents.")
                  .build(),
                TextBlockParam.builder()
                  .text(
                    "Here is the full text of a complex legal agreement: [Insert full text of a 50-page legal agreement here]"
                  )
                  .cacheControl(CacheControlEphemeral.builder().build())
                  .build()
              )
            )
            .addUserMessage("What are the key terms and conditions in this agreement?")
            .build();

          Message message = client.messages().create(params);
          System.out.println(message.usage());
        }
      }

      $client = new Client();

      $message = $client->messages->create(
          maxTokens: 1024,
          messages: [
              [
                  'role' => 'user',
                  'content' => 'What are the key terms and conditions in this agreement?'
              ]
          ],
          model: 'haijun-opus-5-5',
          system: [
              [
                  'type' => 'text',
                  'text' => 'You are an AI assistant tasked with analyzing legal documents.'
              ],
              [
                  'type' => 'text',
                  'text' => 'Here is the full text of a complex legal agreement: [Insert full text of a 50-page legal agreement here]',
                  'cache_control' => ['type' => 'ephemeral']
              ]
          ],
      );

      echo json_encode($message->usage), PHP_EOL;

      client = Juglow::Client.new

      message = client.messages.create(
        model: "haijun-opus-5-5",
        max_tokens: 1024,
        system: [
          {
            type: "text",
            text: "You are an AI assistant tasked with analyzing legal documents."
          },
          {
            type: "text",
            text: "Here is the full text of a complex legal agreement: [Insert full text of a 50-page legal agreement here]",
            cache_control: { type: "ephemeral" }
          }
        ],
        messages: [
          {
            role: "user",
            content: "What are the key terms and conditions in this agreement?"
          }
        ]
      )
      puts message.usage

    {
      "model": "haijun-opus-5-5",
      "max_tokens": 1024,
      "tools": [
        {
          "name": "get_weather",
          "description": "Get the current weather in a given location",
          "input_schema": {
            "type": "object",
            "properties": { "location": { "type": "string" } },
            "required": ["location"]
          }
        },
        {
          "name": "get_time",
          "description": "Get the current time in a given time zone",
          "input_schema": {
            "type": "object",
            "properties": { "timezone": { "type": "string" } },
            "required": ["timezone"]
          },
          "cache_control": { "type": "ephemeral" }
        }
      ],
      "messages": [{ "role": "user", "content": "What is the weather and time in New York?" }]
    }

      curl https://haijun.my.id/v1/messages \
        -H "x-api-key: $JUGLOW_API_KEY" \
        -H "juglow-version: 2023-06-01" \
        -H "content-type: application/json" \
        -d '{
          "model": "haijun-opus-5-5",
          "max_tokens": 1024,
          "system": [
            {
              "type": "text",
              "text": "...long system prompt",
              "cache_control": {"type": "ephemeral"}
            }
          ],
          "messages": [
            {
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": "Hello, can you tell me more about the solar system?"
                }
              ]
            },
            {
              "role": "assistant",
              "content": "Certainly! The solar system is the collection of celestial bodies that orbit our Sun. It consists of eight planets, numerous moons, asteroids, comets, and other objects. The planets, in order from closest to farthest from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune. Each planet has its own unique characteristics and features. Is there a specific aspect of the solar system you would like to know more about?"
            },
            {
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": "Good to know."
                },
                {
                  "type": "text",
                  "text": "Tell me more about Mars.",
                  "cache_control": {"type": "ephemeral"}
                }
              ]
            }
          ]
        }'

      ant messages create --transform usage <<'YAML'
      model: haijun-opus-5-5
      max_tokens: 1024
      system:
        - type: text
          text: "...long system prompt"
          cache_control:
            type: ephemeral
      messages:
        - role: user
          content:
            - type: text
              text: Hello, can you tell me more about the solar system?
        - role: assistant
          content: >-
            Certainly! The solar system is the collection of celestial bodies that
            orbit our Sun. It consists of eight planets, numerous moons, asteroids,
            comets, and other objects. The planets, in order from closest to farthest
            from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus,
            and Neptune. Each planet has its own unique characteristics and features.
            Is there a specific aspect of the solar system you would like to know
            more about?
        - role: user
          content:
            - type: text
              text: Good to know.
            - type: text
              text: Tell me more about Mars.
              cache_control:
                type: ephemeral
      YAML

      client = juglow.Juglow()

      response = client.messages.create(
          model="haijun-opus-5-5",
          max_tokens=1024,
          system=[
              {
                  "type": "text",
                  "text": "...long system prompt",
                  "cache_control": {"type": "ephemeral"},
              }
          ],
          messages=[
              # ...long conversation so far
              {
                  "role": "user",
                  "content": [
                      {
                          "type": "text",
                          "text": "Hello, can you tell me more about the solar system?",
                      }
                  ],
              },
              {
                  "role": "assistant",
                  "content": "Certainly! The solar system is the collection of celestial bodies that orbit our Sun. It consists of eight planets, numerous moons, asteroids, comets, and other objects. The planets, in order from closest to farthest from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune. Each planet has its own unique characteristics and features. Is there a specific aspect of the solar system you'd like to know more about?",
              },
              {
                  "role": "user",
                  "content": [
                      {"type": "text", "text": "Good to know."},
                      {
                          "type": "text",
                          "text": "Tell me more about Mars.",
                          "cache_control": {"type": "ephemeral"},
                      },
                  ],
              },
          ],
      )
      print(response.usage.model_dump_json())

      const client = new Juglow();

      const response = await client.messages.create({
        model: "haijun-opus-5-5",
        max_tokens: 1024,
        system: [
          {
            type: "text",
            text: "...long system prompt",
            cache_control: { type: "ephemeral" }
          }
        ],
        messages: [
          // ...long conversation so far
          {
            role: "user",
            content: [
              {
                type: "text",
                text: "Hello, can you tell me more about the solar system?"
              }
            ]
          },
          {
            role: "assistant",
            content:
              "Certainly! The solar system is the collection of celestial bodies that orbit our Sun. It consists of eight planets, numerous moons, asteroids, comets, and other objects. The planets, in order from closest to farthest from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune. Each planet has its own unique characteristics and features. Is there a specific aspect of the solar system you'd like to know more about?"
          },
          {
            role: "user",
            content: [
              {
                type: "text",
                text: "Good to know."
              },
              {
                type: "text",
                text: "Tell me more about Mars.",
                cache_control: { type: "ephemeral" }
              }
            ]
          }
        ]
      });
      console.log(response.usage);

      JuglowClient client = new();

      var parameters = new MessageCreateParams
      {
          Model = Model.HaijunOpus5_5,
          MaxTokens = 1024,
          System = new MessageCreateParamsSystem(new List<TextBlockParam>
          {
              new TextBlockParam()
              {
                  Text = "...long system prompt",
                  CacheControl = new CacheControlEphemeral(),
              },
          }),
          Messages =
          [
              new()
              {
                  Role = Role.User,
                  Content = new MessageParamContent(new List<ContentBlockParam>
                  {
                      new ContentBlockParam(new TextBlockParam("Hello, can you tell me more about the solar system?")),
                  }),
              },
              new()
              {
                  Role = Role.Assistant,
                  Content = "Certainly! The solar system is the collection of celestial bodies that orbit our Sun. It consists of eight planets, numerous moons, asteroids, comets, and other objects. The planets, in order from closest to farthest from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune. Each planet has its own unique characteristics and features. Is there a specific aspect of the solar system you would like to know more about?"
              },
              new()
              {
                  Role = Role.User,
                  Content = new MessageParamContent(new List<ContentBlockParam>
                  {
                      new ContentBlockParam(new TextBlockParam("Good to know.")),
                      new ContentBlockParam(new TextBlockParam()
                      {
                          Text = "Tell me more about Mars.",
                          CacheControl = new CacheControlEphemeral(),
                      }),
                  })
              }
          ]
      };

      var message = await client.Messages.Create(parameters);
      Console.WriteLine(message.Usage);

      client := juglow.NewClient()

      response, err := client.Messages.New(context.TODO(), juglow.MessageNewParams{
      	Model:     juglow.ModelHaijunOpus5_5,
      	MaxTokens: 1024,
      	System: []juglow.TextBlockParam{
      		{
      			Text:         "...long system prompt",
      			CacheControl: juglow.NewCacheControlEphemeralParam(),
      		},
      	},
      	Messages: []juglow.MessageParam{
      		juglow.NewUserMessage(juglow.NewTextBlock("Hello, can you tell me more about the solar system?")),
      		juglow.NewAssistantMessage(juglow.NewTextBlock("Certainly! The solar system is the collection of celestial bodies that orbit our Sun. It consists of eight planets, numerous moons, asteroids, comets, and other objects. The planets, in order from closest to farthest from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune. Each planet has its own unique characteristics and features. Is there a specific aspect of the solar system you would like to know more about?")),
      		{
      			Role: juglow.MessageParamRoleUser,
      			Content: []juglow.ContentBlockParamUnion{
      				juglow.NewTextBlock("Good to know."),
      				{OfText: &juglow.TextBlockParam{
      					Text:         "Tell me more about Mars.",
      					CacheControl: juglow.NewCacheControlEphemeralParam(),
      				}},
      			},
      		},
      	},
      })
      if err != nil {
      	log.Fatal(err)
      }
      fmt.Println(response.Usage.RawJSON())

      import com.juglow.models.messages.CacheControlEphemeral;
      // ...
      public class ConversationWithCacheControlExample {

        public static void main(String[] args) {
          JuglowClient client = JuglowOkHttpClient.fromEnv();

          // Create ephemeral system prompt
          TextBlockParam systemPrompt = TextBlockParam.builder()
            .text("...long system prompt")
            .cacheControl(CacheControlEphemeral.builder().build())
            .build();

          // Create message params
          MessageCreateParams params = MessageCreateParams.builder()
            .model(Model.HAIJUN_OPUS_5_5)
            .maxTokens(1024)
            .systemOfTextBlockParams(List.of(systemPrompt))
            // First user message (without cache control)
            .addUserMessage("Hello, can you tell me more about the solar system?")
            // Assistant response
            .addAssistantMessage(
              "Certainly! The solar system is the collection of celestial bodies that orbit our Sun. It consists of eight planets, numerous moons, asteroids, comets, and other objects. The planets, in order from closest to farthest from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune. Each planet has its own unique characteristics and features. Is there a specific aspect of the solar system you would like to know more about?"
            )
            // Second user message (with cache control)
            .addUserMessageOfBlockParams(
              List.of(
                ContentBlockParam.ofText(TextBlockParam.builder().text("Good to know.").build()),
                ContentBlockParam.ofText(
                  TextBlockParam.builder()
                    .text("Tell me more about Mars.")
                    .cacheControl(CacheControlEphemeral.builder().build())
                    .build()
                )
              )
            )
            .build();

          Message message = client.messages().create(params);
          System.out.println(message.usage());
        }
      }

      $client = new Client();

      $message = $client->messages->create(
          maxTokens: 1024,
          messages: [
              [
                  'role' => 'user',
                  'content' => [
                      [
                          'type' => 'text',
                          'text' => 'Hello, can you tell me more about the solar system?'
                      ]
                  ]
              ],
              [
                  'role' => 'assistant',
                  'content' => "Certainly! The solar system is the collection of celestial bodies that orbit our Sun. It consists of eight planets, numerous moons, asteroids, comets, and other objects. The planets, in order from closest to farthest from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune. Each planet has its own unique characteristics and features. Is there a specific aspect of the solar system you would like to know more about?"
              ],
              [
                  'role' => 'user',
                  'content' => [
                      ['type' => 'text', 'text' => 'Good to know.'],
                      [
                          'type' => 'text',
                          'text' => 'Tell me more about Mars.',
                          'cache_control' => ['type' => 'ephemeral']
                      ]
                  ]
              ]
          ],
          model: 'haijun-opus-5-5',
          system: [
              [
                  'type' => 'text',
                  'text' => '...long system prompt',
                  'cache_control' => ['type' => 'ephemeral']
              ]
          ],
      );

      echo json_encode($message->usage), PHP_EOL;

      client = Juglow::Client.new

      message = client.messages.create(
        model: "haijun-opus-5-5",
        max_tokens: 1024,
        system: [
          {
            type: "text",
            text: "...long system prompt",
            cache_control: { type: "ephemeral" }
          }
        ],
        messages: [
          {
            role: "user",
            content: [
              {
                type: "text",
                text: "Hello, can you tell me more about the solar system?"
              }
            ]
          },
          {
            role: "assistant",
            content: "Certainly! The solar system is the collection of celestial bodies that orbit our Sun. It consists of eight planets, numerous moons, asteroids, comets, and other objects. The planets, in order from closest to farthest from the Sun, are: Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune. Each planet has its own unique characteristics and features. Is there a specific aspect of the solar system you would like to know more about?"
          },
          {
            role: "user",
            content: [
              { type: "text", text: "Good to know." },
              {
                type: "text",
                text: "Tell me more about Mars.",
                cache_control: { type: "ephemeral" }
              }
            ]
          }
        ]
      )
      puts message.usage

      curl https://haijun.my.id/v1/messages \
        -H "x-api-key: $JUGLOW_API_KEY" \
        -H "juglow-version: 2023-06-01" \
        -H "content-type: application/json" \
        -d '{
          "model": "haijun-opus-5-5",
          "max_tokens": 1024,
          "tools": [
            {
              "name": "search_documents",
              "description": "Search through the knowledge base",
              "input_schema": {
                "type": "object",
                "properties": {
                  "query": {
                    "type": "string",
                    "description": "Search query"
                  }
                },
                "required": ["query"]
              }
            },
            {
              "name": "get_document",
              "description": "Retrieve a specific document by ID",
              "input_schema": {
                "type": "object",
                "properties": {
                  "doc_id": {
                    "type": "string",
                    "description": "Document ID"
                  }
                },
                "required": ["doc_id"]
              },
              "cache_control": {"type": "ephemeral"}
            }
          ],
          "system": [
            {
              "type": "text",
              "text": "You are a helpful research assistant with access to a document knowledge base.\n\n# Instructions\n- Always search for relevant documents before answering\n- Provide citations for your sources\n- Be objective and accurate in your responses\n- If multiple documents contain relevant information, synthesize them\n- Acknowledge when information is not available in the knowledge base",
              "cache_control": {"type": "ephemeral"}
            },
            {
              "type": "text",
              "text": "# Knowledge Base Context\n\nHere are the relevant documents for this conversation:\n\n## Document 1: Solar System Overview\nThe solar system consists of the Sun and all objects that orbit it...\n\n## Document 2: Planetary Characteristics\nEach planet has unique features. Mercury is the smallest planet...\n\n## Document 3: Mars Exploration\nMars has been a target of exploration for decades...\n\n[Additional documents...]",
              "cache_control": {"type": "ephemeral"}
            }
          ],
          "messages": [
            {
              "role": "user",
              "content": "Can you search for information about Mars rovers?"
            },
            {
              "role": "assistant",
              "content": [
                {
                  "type": "tool_use",
                  "id": "tool_1",
                  "name": "search_documents",
                  "input": {"query": "Mars rovers"}
                }
              ]
            },
            {
              "role": "user",
              "content": [
                {
                  "type": "tool_result",
                  "tool_use_id": "tool_1",
                  "content": "Found 3 relevant documents: Document 3 (Mars Exploration), Document 7 (Rover Technology), Document 9 (Mission History)"
                }
              ]
            },
            {
              "role": "assistant",
              "content": [
                {
                  "type": "text",
                  "text": "I found 3 relevant documents about Mars rovers. Let me get more details from the Mars Exploration document."
                }
              ]
            },
            {
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": "Yes, please tell me about the Perseverance rover specifically.",
                  "cache_control": {"type": "ephemeral"}
                }
              ]
            }
          ]
        }'

      ant messages create --transform usage <<'YAML'
      model: haijun-opus-5-5
      max_tokens: 1024
      tools:
        - name: search_documents
          description: Search through the knowledge base
          input_schema:
            type: object
            properties:
              query:
                type: string
                description: Search query
            required: [query]
        - name: get_document
          description: Retrieve a specific document by ID
          input_schema:
            type: object
            properties:
              doc_id:
                type: string
                description: Document ID
            required: [doc_id]
          cache_control:
            type: ephemeral
      system:
        - type: text
          text: |-
            You are a helpful research assistant with access to a document knowledge base.

            # Instructions
            - Always search for relevant documents before answering
            - Provide citations for your sources
            - Be objective and accurate in your responses
            - If multiple documents contain relevant information, synthesize them
            - Acknowledge when information is not available in the knowledge base
          cache_control:
            type: ephemeral
        - type: text
          text: |-
            # Knowledge Base Context

            Here are the relevant documents for this conversation:

            ## Document 1: Solar System Overview
            The solar system consists of the Sun and all objects that orbit it...

            ## Document 2: Planetary Characteristics
            Each planet has unique features. Mercury is the smallest planet...

            ## Document 3: Mars Exploration
            Mars has been a target of exploration for decades...

            [Additional documents...]
          cache_control:
            type: ephemeral
      messages:
        - role: user
          content: Can you search for information about Mars rovers?
        - role: assistant
          content:
            - type: tool_use
              id: tool_1
              name: search_documents
              input:
                query: Mars rovers
        - role: user
          content:
            - type: tool_result
              tool_use_id: tool_1
              content: >-
                Found 3 relevant documents: Document 3 (Mars Exploration),
                Document 7 (Rover Technology), Document 9 (Mission History)
        - role: assistant
          content:
            - type: text
              text: >-
                I found 3 relevant documents about Mars rovers. Let me get more
                details from the Mars Exploration document.
        - role: user
          content:
            - type: text
              text: Yes, please tell me about the Perseverance rover specifically.
              cache_control:
                type: ephemeral
      YAML

      client = juglow.Juglow()

      response = client.messages.create(
          model="haijun-opus-5-5",
          max_tokens=1024,
          tools=[
              {
                  "name": "search_documents",
                  "description": "Search through the knowledge base",
                  "input_schema": {
                      "type": "object",
                      "properties": {
                          "query": {"type": "string", "description": "Search query"}
                      },
                      "required": ["query"],
                  },
              },
              {
                  "name": "get_document",
                  "description": "Retrieve a specific document by ID",
                  "input_schema": {
                      "type": "object",
                      "properties": {
                          "doc_id": {"type": "string", "description": "Document ID"}
                      },
                      "required": ["doc_id"],
                  },
                  "cache_control": {"type": "ephemeral"},
              },
          ],
          system=[
              {
                  "type": "text",
                  "text": "You are a helpful research assistant with access to a document knowledge base.\n\n# Instructions\n- Always search for relevant documents before answering\n- Provide citations for your sources\n- Be objective and accurate in your responses\n- If multiple documents contain relevant information, synthesize them\n- Acknowledge when information is not available in the knowledge base",
                  "cache_control": {"type": "ephemeral"},
              },
              {
                  "type": "text",
                  "text": "# Knowledge Base Context\n\nHere are the relevant documents for this conversation:\n\n## Document 1: Solar System Overview\nThe solar system consists of the Sun and all objects that orbit it...\n\n## Document 2: Planetary Characteristics\nEach planet has unique features. Mercury is the smallest planet...\n\n## Document 3: Mars Exploration\nMars has been a target of exploration for decades...\n\n[Additional documents...]",
                  "cache_control": {"type": "ephemeral"},
              },
          ],
          messages=[
              {
                  "role": "user",
                  "content": "Can you search for information about Mars rovers?",
              },
              {
                  "role": "assistant",
                  "content": [
                      {
                          "type": "tool_use",
                          "id": "tool_1",
                          "name": "search_documents",
                          "input": {"query": "Mars rovers"},
                      }
                  ],
              },
              {
                  "role": "user",
                  "content": [
                      {
                          "type": "tool_result",
                          "tool_use_id": "tool_1",
                          "content": "Found 3 relevant documents: Document 3 (Mars Exploration), Document 7 (Rover Technology), Document 9 (Mission History)",
                      }
                  ],
              },
              {
                  "role": "assistant",
                  "content": [
                      {
                          "type": "text",
                          "text": "I found 3 relevant documents about Mars rovers. Let me get more details from the Mars Exploration document.",
                      }
                  ],
              },
              {
                  "role": "user",
                  "content": [
                      {
                          "type": "text",
                          "text": "Yes, please tell me about the Perseverance rover specifically.",
                          "cache_control": {"type": "ephemeral"},
                      }
                  ],
              },
          ],
      )
      print(response.usage.model_dump_json())

      const client = new Juglow();

      const response = await client.messages.create({
        model: "haijun-opus-5-5",
        max_tokens: 1024,
        tools: [
          {
            name: "search_documents",
            description: "Search through the knowledge base",
            input_schema: {
              type: "object",
              properties: {
                query: {
                  type: "string",
                  description: "Search query"
                }
              },
              required: ["query"]
            }
          },
          {
            name: "get_document",
            description: "Retrieve a specific document by ID",
            input_schema: {
              type: "object",
              properties: {
                doc_id: {
                  type: "string",
                  description: "Document ID"
                }
              },
              required: ["doc_id"]
            },
            cache_control: { type: "ephemeral" }
          }
        ],
        system: [
          {
            type: "text",
            text: "You are a helpful research assistant with access to a document knowledge base.\n\n# Instructions\n- Always search for relevant documents before answering\n- Provide citations for your sources\n- Be objective and accurate in your responses\n- If multiple documents contain relevant information, synthesize them\n- Acknowledge when information is not available in the knowledge base",
            cache_control: { type: "ephemeral" }
          },
          {
            type: "text",
            text: "# Knowledge Base Context\n\nHere are the relevant documents for this conversation:\n\n## Document 1: Solar System Overview\nThe solar system consists of the Sun and all objects that orbit it...\n\n## Document 2: Planetary Characteristics\nEach planet has unique features. Mercury is the smallest planet...\n\n## Document 3: Mars Exploration\nMars has been a target of exploration for decades...\n\n[Additional documents...]",
            cache_control: { type: "ephemeral" }
          }
        ],
        messages: [
          {
            role: "user",
            content: "Can you search for information about Mars rovers?"
          },
          {
            role: "assistant",
            content: [
              {
                type: "tool_use",
                id: "tool_1",
                name: "search_documents",
                input: { query: "Mars rovers" }
              }
            ]
          },
          {
            role: "user",
            content: [
              {
                type: "tool_result",
                tool_use_id: "tool_1",
                content:
                  "Found 3 relevant documents: Document 3 (Mars Exploration), Document 7 (Rover Technology), Document 9 (Mission History)"
              }
            ]
          },
          {
            role: "assistant",
            content: [
              {
                type: "text",
                text: "I found 3 relevant documents about Mars rovers. Let me get more details from the Mars Exploration document."
              }
            ]
          },
          {
            role: "user",
            content: [
              {
                type: "text",
                text: "Yes, please tell me about the Perseverance rover specifically.",
                cache_control: { type: "ephemeral" }
              }
            ]
          }
        ]
      });
      console.log(response.usage);

      JuglowClient client = new()
      {
          ApiKey = Environment.GetEnvironmentVariable("JUGLOW_API_KEY")
      };

      var parameters = new MessageCreateParams
      {
          Model = Model.HaijunOpus5_5,
          MaxTokens = 1024,
          Tools =
          [
              new ToolUnion(new Tool()
              {
                  Name = "search_documents",
                  Description = "Search through the knowledge base",
                  InputSchema = new InputSchema()
                  {
                      Properties = new Dictionary<string, JsonElement>
                      {
                          ["query"] = JsonSerializer.SerializeToElement(new { type = "string", description = "Search query" }),
                      },
                      Required = ["query"],
                  },
              }),
              new ToolUnion(new Tool()
              {
                  Name = "get_document",
                  Description = "Retrieve a specific document by ID",
                  InputSchema = new InputSchema()
                  {
                      Properties = new Dictionary<string, JsonElement>
                      {
                          ["doc_id"] = JsonSerializer.SerializeToElement(new { type = "string", description = "Document ID" }),
                      },
                      Required = ["doc_id"],
                  },
                  CacheControl = new CacheControlEphemeral(),
              }),
          ],
          System = new MessageCreateParamsSystem(new List<TextBlockParam>
          {
              new TextBlockParam()
              {
                  Text = "You are a helpful research assistant with access to a document knowledge base.\n\n# Instructions\n- Always search for relevant documents before answering\n- Provide citations for your sources\n- Be objective and accurate in your responses\n- If multiple documents contain relevant information, synthesize them\n- Acknowledge when information is not available in the knowledge base",
                  CacheControl = new CacheControlEphemeral(),
              },
              new TextBlockParam()
              {
                  Text = "# Knowledge Base Context\n\nHere are the relevant documents for this conversation:\n\n## Document 1: Solar System Overview\nThe solar system consists of the Sun and all objects that orbit it...\n\n## Document 2: Planetary Characteristics\nEach planet has unique features. Mercury is the smallest planet...\n\n## Document 3: Mars Exploration\nMars has been a target of exploration for decades...\n\n[Additional documents...]",
                  CacheControl = new CacheControlEphemeral(),
              },
          }),
          Messages =
          [
              new() { Role = Role.User, Content = "Can you search for information about Mars rovers?" },
              new()
              {
                  Role = Role.Assistant,
                  Content = new MessageParamContent(new List<ContentBlockParam>
                  {
                      new ContentBlockParam(new ToolUseBlockParam()
                      {
                          ID = "tool_1",
                          Name = "search_documents",
                          Input = new Dictionary<string, JsonElement>
                          {
                              ["query"] = JsonSerializer.SerializeToElement("Mars rovers"),
                          },
                      }),
                  }),
              },
              new()
              {
                  Role = Role.User,
                  Content = new MessageParamContent(new List<ContentBlockParam>
                  {
                      new ContentBlockParam(new ToolResultBlockParam()
                      {
                          ToolUseID = "tool_1",
                          Content = "Found 3 relevant documents: Document 3 (Mars Exploration), Document 7 (Rover Technology), Document 9 (Mission History)",
                      }),
                  }),
              },
              new()
              {
                  Role = Role.Assistant,
                  Content = "I found 3 relevant documents about Mars rovers. Let me get more details from the Mars Exploration document.",
              },
              new()
              {
                  Role = Role.User,
                  Content = new MessageParamContent(new List<ContentBlockParam>
                  {
                      new ContentBlockParam(new TextBlockParam()
                      {
                          Text = "Yes, please tell me about the Perseverance rover specifically.",
                          CacheControl = new CacheControlEphemeral(),
                      }),
                  }),
              },
          ]
      };

      var message = await client.Messages.Create(parameters);
      Console.WriteLine(message.Usage);

      client := juglow.NewClient()

      response, err := client.Messages.New(context.TODO(), juglow.MessageNewParams{
      	Model:     juglow.ModelHaijunOpus5_5,
      	MaxTokens: 1024,
      	Tools: []juglow.ToolUnionParam{
      		{OfTool: &juglow.ToolParam{
      			Name:        "search_documents",
      			Description: juglow.String("Search through the knowledge base"),
      			InputSchema: juglow.ToolInputSchemaParam{
      				Properties: map[string]any{
      					"query": map[string]any{
      						"type":        "string",
      						"description": "Search query",
      					},
      				},
      				Required: []string{"query"},
      			},
      		}},
      		{OfTool: &juglow.ToolParam{
      			Name:        "get_document",
      			Description: juglow.String("Retrieve a specific document by ID"),
      			InputSchema: juglow.ToolInputSchemaParam{
      				Properties: map[string]any{
      					"doc_id": map[string]any{
      						"type":        "string",
      						"description": "Document ID",
      					},
      				},
      				Required: []string{"doc_id"},
      			},
      			CacheControl: juglow.NewCacheControlEphemeralParam(),
      		}},
      	},
      	System: []juglow.TextBlockParam{
      		{
      			Text:         "You are a helpful research assistant with access to a document knowledge base.\n\n# Instructions\n- Always search for relevant documents before answering\n- Provide citations for your sources\n- Be objective and accurate in your responses\n- If multiple documents contain relevant information, synthesize them\n- Acknowledge when information is not available in the knowledge base",
      			CacheControl: juglow.NewCacheControlEphemeralParam(),
      		},
      		{
      			Text:         "# Knowledge Base Context\n\nHere are the relevant documents for this conversation:\n\n## Document 1: Solar System Overview\nThe solar system consists of the Sun and all objects that orbit it...\n\n## Document 2: Planetary Characteristics\nEach planet has unique features. Mercury is the smallest planet...\n\n## Document 3: Mars Exploration\nMars has been a target of exploration for decades...\n\n[Additional documents...]",
      			CacheControl: juglow.NewCacheControlEphemeralParam(),
      		},
      	},
      	Messages: []juglow.MessageParam{
      		juglow.NewUserMessage(juglow.NewTextBlock("Can you search for information about Mars rovers?")),
      		juglow.NewAssistantMessage(juglow.NewToolUseBlock(
      			"tool_1",
      			map[string]any{"query": "Mars rovers"},
      			"search_documents",
      		)),
      		juglow.NewUserMessage(juglow.NewToolResultBlock(
      			"tool_1",
      			"Found 3 relevant documents: Document 3 (Mars Exploration), Document 7 (Rover Technology), Document 9 (Mission History)",
      			false,
      		)),
      		juglow.NewAssistantMessage(juglow.NewTextBlock("I found 3 relevant documents about Mars rovers. Let me get more details from the Mars Exploration document.")),
      		{
      			Role: juglow.MessageParamRoleUser,
      			Content: []juglow.ContentBlockParamUnion{
      				{OfText: &juglow.TextBlockParam{
      					Text:         "Yes, please tell me about the Perseverance rover specifically.",
      					CacheControl: juglow.NewCacheControlEphemeralParam(),
      				}},
      			},
      		},
      	},
      })
      if err != nil {
      	log.Fatal(err)
      }
      fmt.Println(response.Usage.RawJSON())

      import com.juglow.models.messages.CacheControlEphemeral;
      // ...
      public class MultipleCacheBreakpointsExample {

        public static void main(String[] args) {
          JuglowClient client = JuglowOkHttpClient.fromEnv();

          // Search tool schema
          InputSchema searchSchema = InputSchema.builder()
            .properties(
              JsonValue.from(
                Map.of("query", Map.of("type", "string", "description", "Search query"))
              )
            )
            .putAdditionalProperty("required", JsonValue.from(List.of("query")))
            .build();

          // Get document tool schema
          InputSchema getDocSchema = InputSchema.builder()
            .properties(
              JsonValue.from(
                Map.of("doc_id", Map.of("type", "string", "description", "Document ID"))
              )
            )
            .putAdditionalProperty("required", JsonValue.from(List.of("doc_id")))
            .build();

          MessageCreateParams params = MessageCreateParams.builder()
            .model(Model.HAIJUN_OPUS_5_5)
            .maxTokens(1024)
            // Tools with cache control on the last one
            .addTool(
              Tool.builder()
                .name("search_documents")
                .description("Search through the knowledge base")
                .inputSchema(searchSchema)
                .build()
            )
            .addTool(
              Tool.builder()
                .name("get_document")
                .description("Retrieve a specific document by ID")
                .inputSchema(getDocSchema)
                .cacheControl(CacheControlEphemeral.builder().build())
                .build()
            )
            // System prompts with cache control on instructions and context separately
            .systemOfTextBlockParams(
              List.of(
                TextBlockParam.builder()
                  .text(
                    "You are a helpful research assistant with access to a document knowledge base.\n\n# Instructions\n- Always search for relevant documents before answering\n- Provide citations for your sources\n- Be objective and accurate in your responses\n- If multiple documents contain relevant information, synthesize them\n- Acknowledge when information is not available in the knowledge base"
                  )
                  .cacheControl(CacheControlEphemeral.builder().build())
                  .build(),
                TextBlockParam.builder()
                  .text(
                    "# Knowledge Base Context\n\nHere are the relevant documents for this conversation:\n\n## Document 1: Solar System Overview\nThe solar system consists of the Sun and all objects that orbit it...\n\n## Document 2: Planetary Characteristics\nEach planet has unique features. Mercury is the smallest planet...\n\n## Document 3: Mars Exploration\nMars has been a target of exploration for decades...\n\n[Additional documents...]"
                  )
                  .cacheControl(CacheControlEphemeral.builder().build())
                  .build()
              )
            )
            // Conversation history
            .addUserMessage("Can you search for information about Mars rovers?")
            .addAssistantMessageOfBlockParams(
              List.of(
                ContentBlockParam.ofToolUse(
                  ToolUseBlockParam.builder()
                    .id("tool_1")
                    .name("search_documents")
                    .input(JsonValue.from(Map.of("query", "Mars rovers")))
                    .build()
                )
              )
            )
            .addUserMessageOfBlockParams(
              List.of(
                ContentBlockParam.ofToolResult(
                  ToolResultBlockParam.builder()
                    .toolUseId("tool_1")
                    .content(
                      "Found 3 relevant documents: Document 3 (Mars Exploration), Document 7 (Rover Technology), Document 9 (Mission History)"
                    )
                    .build()
                )
              )
            )
            .addAssistantMessageOfBlockParams(
              List.of(
                ContentBlockParam.ofText(
                  TextBlockParam.builder()
                    .text(
                      "I found 3 relevant documents about Mars rovers. Let me get more details from the Mars Exploration document."
                    )
                    .build()
                )
              )
            )
            .addUserMessageOfBlockParams(
              List.of(
                ContentBlockParam.ofText(
                  TextBlockParam.builder()
                    .text("Yes, please tell me about the Perseverance rover specifically.")
                    .cacheControl(CacheControlEphemeral.builder().build())
                    .build()
                )
              )
            )
            .build();

          Message message = client.messages().create(params);
          System.out.println(message.usage());
        }
      }

      $client = new Client();

      $message = $client->messages->create(
          maxTokens: 1024,
          messages: [
              [
                  'role' => 'user',
                  'content' => 'Can you search for information about Mars rovers?'
              ],
              [
                  'role' => 'assistant',
                  'content' => [
                      [
                          'type' => 'tool_use',
                          'id' => 'tool_1',
                          'name' => 'search_documents',
                          'input' => ['query' => 'Mars rovers']
                      ]
                  ]
              ],
              [
                  'role' => 'user',
                  'content' => [
                      [
                          'type' => 'tool_result',
                          'tool_use_id' => 'tool_1',
                          'content' => 'Found 3 relevant documents: Document 3 (Mars Exploration), Document 7 (Rover Technology), Document 9 (Mission History)'
                      ]
                  ]
              ],
              [
                  'role' => 'assistant',
                  'content' => [
                      [
                          'type' => 'text',
                          'text' => 'I found 3 relevant documents about Mars rovers. Let me get more details from the Mars Exploration document.'
                      ]
                  ]
              ],
              [
                  'role' => 'user',
                  'content' => [
                      [
                          'type' => 'text',
                          'text' => 'Yes, please tell me about the Perseverance rover specifically.',
                          'cache_control' => ['type' => 'ephemeral']
                      ]
                  ]
              ]
          ],
          model: 'haijun-opus-5-5',
          system: [
              [
                  'type' => 'text',
                  'text' => "You are a helpful research assistant with access to a document knowledge base.\n\n# Instructions\n- Always search for relevant documents before answering\n- Provide citations for your sources\n- Be objective and accurate in your responses\n- If multiple documents contain relevant information, synthesize them\n- Acknowledge when information is not available in the knowledge base",
                  'cache_control' => ['type' => 'ephemeral']
              ],
              [
                  'type' => 'text',
                  'text' => "# Knowledge Base Context\n\nHere are the relevant documents for this conversation:\n\n## Document 1: Solar System Overview\nThe solar system consists of the Sun and all objects that orbit it...\n\n## Document 2: Planetary Characteristics\nEach planet has unique features. Mercury is the smallest planet...\n\n## Document 3: Mars Exploration\nMars has been a target of exploration for decades...\n\n[Additional documents...]",
                  'cache_control' => ['type' => 'ephemeral']
              ]
          ],
          tools: [
              [
                  'name' => 'search_documents',
                  'description' => 'Search through the knowledge base',
                  'input_schema' => [
                      'type' => 'object',
                      'properties' => [
                          'query' => [
                              'type' => 'string',
                              'description' => 'Search query'
                          ]
                      ],
                      'required' => ['query']
                  ]
              ],
              [
                  'name' => 'get_document',
                  'description' => 'Retrieve a specific document by ID',
                  'input_schema' => [
                      'type' => 'object',
                      'properties' => [
                          'doc_id' => [
                              'type' => 'string',
                              'description' => 'Document ID'
                          ]
                      ],
                      'required' => ['doc_id']
                  ],
                  'cache_control' => ['type' => 'ephemeral']
              ]
          ],
      );

      echo json_encode($message->usage), PHP_EOL;

      client = Juglow::Client.new

      message = client.messages.create(
        model: "haijun-opus-5-5",
        max_tokens: 1024,
        tools: [
          {
            name: "search_documents",
            description: "Search through the knowledge base",
            input_schema: {
              type: "object",
              properties: {
                query: {
                  type: "string",
                  description: "Search query"
                }
              },
              required: ["query"]
            }
          },
          {
            name: "get_document",
            description: "Retrieve a specific document by ID",
            input_schema: {
              type: "object",
              properties: {
                doc_id: {
                  type: "string",
                  description: "Document ID"
                }
              },
              required: ["doc_id"]
            },
            cache_control: { type: "ephemeral" }
          }
        ],
        system: [
          {
            type: "text",
            text: "You are a helpful research assistant with access to a document knowledge base.\n\n# Instructions\n- Always search for relevant documents before answering\n- Provide citations for your sources\n- Be objective and accurate in your responses\n- If multiple documents contain relevant information, synthesize them\n- Acknowledge when information is not available in the knowledge base",
            cache_control: { type: "ephemeral" }
          },
          {
            type: "text",
            text: "# Knowledge Base Context\n\nHere are the relevant documents for this conversation:\n\n## Document 1: Solar System Overview\nThe solar system consists of the Sun and all objects that orbit it...\n\n## Document 2: Planetary Characteristics\nEach planet has unique features. Mercury is the smallest planet...\n\n## Document 3: Mars Exploration\nMars has been a target of exploration for decades...\n\n[Additional documents...]",
            cache_control: { type: "ephemeral" }
          }
        ],
        messages: [
          {
            role: "user",
            content: "Can you search for information about Mars rovers?"
          },
          {
            role: "assistant",
            content: [
              {
                type: "tool_use",
                id: "tool_1",
                name: "search_documents",
                input: { query: "Mars rovers" }
              }
            ]
          },
          {
            role: "user",
            content: [
              {
                type: "tool_result",
                tool_use_id: "tool_1",
                content: "Found 3 relevant documents: Document 3 (Mars Exploration), Document 7 (Rover Technology), Document 9 (Mission History)"
              }
            ]
          },
          {
            role: "assistant",
            content: [
              {
                type: "text",
                text: "I found 3 relevant documents about Mars rovers. Let me get more details from the Mars Exploration document."
              }
            ]
          },
          {
            role: "user",
            content: [
              {
                type: "text",
                text: "Yes, please tell me about the Perseverance rover specifically.",
                cache_control: { type: "ephemeral" }
              }
            ]
          }
        ]
      )
      puts message.usage

    total_input_tokens = cache_read_input_tokens + cache_creation_input_tokens + input_tokens

      client.beta.prompt_caching.messages.create(**params)

      client.messages.create(**params)

    client.beta.promptCaching.messages.create(/* ... */);

    client.messages.create(/* ... */);