Constructor Detail

Method Detail

• id

   final Message.Builder id(String id)

  Unique object identifier.

  The format and length of IDs may change over time.

• id

   final Message.Builder id(JsonField<String> id)

  Unique object identifier.

  The format and length of IDs may change over time.

• content

   final Message.Builder content(List<ContentBlock> content)

  Content generated by the model.

  This is an array of content blocks, each of which has a type that determines its shape.

  Example:

  [{ "type": "text", "text": "Hi, I'm Claude." }]

  If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.

  For example, if the input messages were:

  [
    {
      "role": "user",
      "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
    },
    { "role": "assistant", "content": "The best answer is (" }
  ]

  Then the response content might be:

  [{ "type": "text", "text": "B)" }]

• content

   final Message.Builder content(JsonField<List<ContentBlock>> content)

  Content generated by the model.

  This is an array of content blocks, each of which has a type that determines its shape.

  Example:

  [{ "type": "text", "text": "Hi, I'm Claude." }]

  If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.

  For example, if the input messages were:

  [
    {
      "role": "user",
      "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
    },
    { "role": "assistant", "content": "The best answer is (" }
  ]

  Then the response content might be:

  [{ "type": "text", "text": "B)" }]

• addContent

   final Message.Builder addContent(ContentBlock content)

  Content generated by the model.

  This is an array of content blocks, each of which has a type that determines its shape.

  Example:

  [{ "type": "text", "text": "Hi, I'm Claude." }]

  If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.

  For example, if the input messages were:

  [
    {
      "role": "user",
      "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
    },
    { "role": "assistant", "content": "The best answer is (" }
  ]

  Then the response content might be:

  [{ "type": "text", "text": "B)" }]

• addContent

   final Message.Builder addContent(TextBlock text)

  Content generated by the model.

  This is an array of content blocks, each of which has a type that determines its shape.

  Example:

  [{ "type": "text", "text": "Hi, I'm Claude." }]

  If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.

  For example, if the input messages were:

  [
    {
      "role": "user",
      "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
    },
    { "role": "assistant", "content": "The best answer is (" }
  ]

  Then the response content might be:

  [{ "type": "text", "text": "B)" }]

• addContent

   final Message.Builder addContent(ToolUseBlock toolUse)

  Content generated by the model.

  This is an array of content blocks, each of which has a type that determines its shape.

  Example:

  [{ "type": "text", "text": "Hi, I'm Claude." }]

  If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.

  For example, if the input messages were:

  [
    {
      "role": "user",
      "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
    },
    { "role": "assistant", "content": "The best answer is (" }
  ]

  Then the response content might be:

  [{ "type": "text", "text": "B)" }]

• addContent

   final Message.Builder addContent(ThinkingBlock thinking)

  Content generated by the model.

  This is an array of content blocks, each of which has a type that determines its shape.

  Example:

  [{ "type": "text", "text": "Hi, I'm Claude." }]

  If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.

  For example, if the input messages were:

  [
    {
      "role": "user",
      "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
    },
    { "role": "assistant", "content": "The best answer is (" }
  ]

  Then the response content might be:

  [{ "type": "text", "text": "B)" }]

• addContent

   final Message.Builder addContent(RedactedThinkingBlock redactedThinking)

  Content generated by the model.

  This is an array of content blocks, each of which has a type that determines its shape.

  Example:

  [{ "type": "text", "text": "Hi, I'm Claude." }]

  If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.

  For example, if the input messages were:

  [
    {
      "role": "user",
      "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
    },
    { "role": "assistant", "content": "The best answer is (" }
  ]

  Then the response content might be:

  [{ "type": "text", "text": "B)" }]

• addRedactedThinkingContent

   final Message.Builder addRedactedThinkingContent(String data)

  Content generated by the model.

  This is an array of content blocks, each of which has a type that determines its shape.

  Example:

  [{ "type": "text", "text": "Hi, I'm Claude." }]

  If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.

  For example, if the input messages were:

  [
    {
      "role": "user",
      "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"
    },
    { "role": "assistant", "content": "The best answer is (" }
  ]

  Then the response content might be:

  [{ "type": "text", "text": "B)" }]

• model

   final Message.Builder model(Model model)

  The model that will complete your prompt.\n\nSee models for additional details and options.

• model

   final Message.Builder model(JsonField<Model> model)

  The model that will complete your prompt.\n\nSee models for additional details and options.

• model

   final Message.Builder model(String value)

  The model that will complete your prompt.\n\nSee models for additional details and options.

• role

   final Message.Builder role(JsonValue role)

  Conversational role of the generated message.

  This will always be "assistant".

• stopReason

   final Message.Builder stopReason(Message.StopReason stopReason)

  The reason that we stopped.

  This may be one the following values:

  • "end_turn": the model reached a natural stopping point

  • "max_tokens": we exceeded the requested max_tokens or the model's maximum

  • "stop_sequence": one of your provided custom stop_sequences was generated

  • "tool_use": the model invoked one or more tools

  In non-streaming mode this value is always non-null. In streaming mode, it is null in the message_start event and non-null otherwise.

• stopReason

   final Message.Builder stopReason(Optional<Message.StopReason> stopReason)

  The reason that we stopped.

  This may be one the following values:

  • "end_turn": the model reached a natural stopping point

  • "max_tokens": we exceeded the requested max_tokens or the model's maximum

  • "stop_sequence": one of your provided custom stop_sequences was generated

  • "tool_use": the model invoked one or more tools

  In non-streaming mode this value is always non-null. In streaming mode, it is null in the message_start event and non-null otherwise.

• stopReason

   final Message.Builder stopReason(JsonField<Message.StopReason> stopReason)

  The reason that we stopped.

  This may be one the following values:

  • "end_turn": the model reached a natural stopping point

  • "max_tokens": we exceeded the requested max_tokens or the model's maximum

  • "stop_sequence": one of your provided custom stop_sequences was generated

  • "tool_use": the model invoked one or more tools

  In non-streaming mode this value is always non-null. In streaming mode, it is null in the message_start event and non-null otherwise.

• stopSequence

   final Message.Builder stopSequence(String stopSequence)

  Which custom stop sequence was generated, if any.

  This value will be a non-null string if one of your custom stop sequences was generated.

• stopSequence

   final Message.Builder stopSequence(Optional<String> stopSequence)

  Which custom stop sequence was generated, if any.

  This value will be a non-null string if one of your custom stop sequences was generated.

• stopSequence

   final Message.Builder stopSequence(JsonField<String> stopSequence)

  Which custom stop sequence was generated, if any.

  This value will be a non-null string if one of your custom stop sequences was generated.

• type

   final Message.Builder type(JsonValue type)

  Object type.

  For Messages, this is always "message".

• usage

   final Message.Builder usage(Usage usage)

  Billing and rate-limit usage.

  Anthropic's API bills and rate-limits by token counts, as tokens represent the underlying cost to our systems.

  Under the hood, the API transforms requests into a format suitable for the model. The model's output then goes through a parsing stage before becoming an API response. As a result, the token counts in usage will not match one-to-one with the exact visible content of an API request or response.

  For example, output_tokens will be non-zero, even for an empty string response from Claude.

  Total input tokens in a request is the summation of input_tokens, cache_creation_input_tokens, and cache_read_input_tokens.

• usage

   final Message.Builder usage(JsonField<Usage> usage)

  Billing and rate-limit usage.

  Anthropic's API bills and rate-limits by token counts, as tokens represent the underlying cost to our systems.

  Under the hood, the API transforms requests into a format suitable for the model. The model's output then goes through a parsing stage before becoming an API response. As a result, the token counts in usage will not match one-to-one with the exact visible content of an API request or response.

  For example, output_tokens will be non-zero, even for an empty string response from Claude.

  Total input tokens in a request is the summation of input_tokens, cache_creation_input_tokens, and cache_read_input_tokens.

• additionalProperties

   final Message.Builder additionalProperties(Map<String, JsonValue> additionalProperties)

• putAdditionalProperty

   final Message.Builder putAdditionalProperty(String key, JsonValue value)

• putAllAdditionalProperties

   final Message.Builder putAllAdditionalProperties(Map<String, JsonValue> additionalProperties)

• removeAdditionalProperty

   final Message.Builder removeAdditionalProperty(String key)

• removeAllAdditionalProperties

   final Message.Builder removeAllAdditionalProperties(Set<String> keys)

• build

   final Message build()