Class: Anthropic::Resources::Messages

Inherits:
Object
  • Object
show all
Defined in:
lib/anthropic/resources/messages.rb,
lib/anthropic/resources/messages/batches.rb,
sig/anthropic/resources/messages.rbs,
sig/anthropic/resources/messages/batches.rbs

Defined Under Namespace

Classes: Batches

Constant Summary collapse

MODELS_TO_WARN_WITH_THINKING_ENABLED = 
["claude-opus-4-6", "claude-mythos-preview"].freeze

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(client:) ⇒ Messages

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Returns a new instance of Messages.

Parameters:



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# File 'lib/anthropic/resources/messages.rb', line 337

def initialize(client:)
  @client = client
  @batches = Anthropic::Resources::Messages::Batches.new(client: client)
end

Instance Attribute Details

#batches ⇒ Anthropic::Resources::Messages::Batches (readonly)

Returns:



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# File 'lib/anthropic/resources/messages.rb', line 9

def batches
  @batches
end

Instance Method Details

#count_tokens(messages:, model:, cache_control: nil, output_config: nil, system_: nil, thinking: nil, tool_choice: nil, tools: nil, user_profile_id: nil, request_options: {}) ⇒ Anthropic::Models::MessageTokensCount

Some parameter documentations has been truncated, see Models::MessageCountTokensParams for more details.

Count the number of tokens in a Message.

The Token Count API can be used to count the number of tokens in a Message, including tools, images, and documents, without creating it.

Learn more about token counting in our user guide

Parameters:

Returns:

See Also:



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# File 'lib/anthropic/resources/messages.rb', line 302

def count_tokens(params)
  parsed, options = Anthropic::MessageCountTokensParams.dump_request(params)
  Anthropic::Helpers::Messages.distill_input_schema_models!(parsed, strict: nil)
  header_params = {user_profile_id: "anthropic-user-profile-id"}
  @client.request(
    method: :post,
    path: "v1/messages/count_tokens",
    headers: parsed.slice(*header_params.keys).transform_keys(header_params),
    body: parsed.except(*header_params.keys),
    model: Anthropic::MessageTokensCount,
    options: options
  )
end

#create(max_tokens:, messages:, model:, cache_control: nil, container: nil, inference_geo: nil, metadata: nil, output_config: nil, service_tier: nil, stop_sequences: nil, system_: nil, temperature: nil, thinking: nil, tool_choice: nil, tools: nil, top_k: nil, top_p: nil, user_profile_id: nil, request_options: {}) ⇒ Anthropic::Models::Message Also known as: parse

See Anthropic::Resources::Messages#stream for streaming counterpart.

Some parameter documentations has been truncated, see Models::MessageCreateParams for more details.

Send a structured list of input messages with text and/or image content, and the model will generate the next message in the conversation.

The Messages API can be used for either single queries or stateless multi-turn conversations.

Learn more about the Messages API in our user guide

Parameters:

Returns:

See Also:



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# File 'lib/anthropic/resources/messages.rb', line 68

def create(params)
  parsed, options = Anthropic::MessageCreateParams.dump_request(params)
  if parsed[:stream]
    message = "Please use `#stream` for the streaming use case."
    raise ArgumentError.new(message)
  end

  warn_thinking_enabled(parsed)

  tools, models = Anthropic::Helpers::Messages.distill_input_schema_models!(parsed, strict: nil)

  unwrap = ->(raw) { Anthropic::Helpers::Messages.parse_input_schemas!(raw, tools:, models:) }

  if options.empty? && @client.timeout == Anthropic::Client::DEFAULT_TIMEOUT_IN_SECONDS
    model = parsed[:model]&.to_sym
    max_tokens = parsed[:max_tokens].to_i
    timeout = @client.calculate_nonstreaming_timeout(
      max_tokens,
      Anthropic::Client::MODEL_NONSTREAMING_TOKENS[model]
    )
    options = {timeout: timeout}
  else
    options = {timeout: 600, **options}
  end

  header_params = {user_profile_id: "anthropic-user-profile-id"}
  @client.request(
    method: :post,
    path: "v1/messages",
    headers: parsed.slice(*header_params.keys).transform_keys(header_params),
    body: parsed.except(*header_params.keys),
    model: Anthropic::Message,
    unwrap: unwrap,
    options: options
  )
end

#stream(max_tokens:, messages:, model:, metadata: nil, output_config: nil, service_tier: nil, stop_sequences: nil, system_: nil, temperature: nil, thinking: nil, tool_choice: nil, tools: nil, top_k: nil, top_p: nil, request_options: {}) ⇒ Anthropic::Streaming::MessageStream

See Anthropic::Resources::Messages#create for non-streaming counterpart.

Some parameter documentations has been truncated, see Models::MessageCreateParams for more details.

Send a structured list of input messages with text and/or image content, and the model will generate the next message in the conversation with streaming.

The Messages API can be used for either single queries or stateless multi-turn conversations.

Learn more about the Messages API in our user guide

Parameters:

Returns:

  • (Anthropic::Streaming::MessageStream)

See Also:



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# File 'lib/anthropic/resources/messages.rb', line 155

def stream(params)
  parsed, options = Anthropic::Models::MessageCreateParams.dump_request(params)
  unless parsed.fetch(:stream, true)
    message = "Please use `#create` for the non-streaming use case."
    raise ArgumentError.new(message)
  end
  parsed.store(:stream, true)

  warn_thinking_enabled(parsed)

  tools, models = Anthropic::Helpers::Messages.distill_input_schema_models!(parsed, strict: nil)

  header_params = {user_profile_id: "anthropic-user-profile-id"}
  raw_stream = @client.request(
    method: :post,
    path: "v1/messages",
    headers: stream_headers(
      "accept" => "text/event-stream",
      "accept-encoding" => "identity",
      **parsed.slice(*header_params.keys)
    ).transform_keys(header_params),
    body: parsed.except(*header_params.keys),
    stream: Anthropic::Internal::Stream,
    model: Anthropic::Models::RawMessageStreamEvent,
    options: options
  )
  Anthropic::Streaming::MessageStream.new(raw_stream:, tools:, models:)
end

#stream_raw(max_tokens:, messages:, model:, cache_control: nil, container: nil, inference_geo: nil, metadata: nil, output_config: nil, service_tier: nil, stop_sequences: nil, system_: nil, temperature: nil, thinking: nil, tool_choice: nil, tools: nil, top_k: nil, top_p: nil, user_profile_id: nil, request_options: {}) ⇒ Anthropic::Internal::Stream<Anthropic::Models::RawMessageStartEvent, Anthropic::Models::RawMessageDeltaEvent, Anthropic::Models::RawMessageStopEvent, Anthropic::Models::RawContentBlockStartEvent, Anthropic::Models::RawContentBlockDeltaEvent, Anthropic::Models::RawContentBlockStopEvent>

See Anthropic::Resources::Messages#create for non-streaming counterpart.

Some parameter documentations has been truncated, see Models::MessageCreateParams for more details.

Send a structured list of input messages with text and/or image content, and the model will generate the next message in the conversation.

The Messages API can be used for either single queries or stateless multi-turn conversations.

Learn more about the Messages API in our user guide

Parameters:

Returns:

See Also:



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# File 'lib/anthropic/resources/messages.rb', line 241

def stream_raw(params)
  parsed, options = Anthropic::MessageCreateParams.dump_request(params)
  unless parsed.fetch(:stream, true)
    message = "Please use `#create` for the non-streaming use case."
    raise ArgumentError.new(message)
  end
  parsed.store(:stream, true)
  Anthropic::Helpers::Messages.distill_input_schema_models!(parsed, strict: nil)

  header_params = {user_profile_id: "anthropic-user-profile-id"}
  @client.request(
    method: :post,
    path: "v1/messages",
    headers: stream_headers(
      "accept" => "text/event-stream",
      "accept-encoding" => "identity",
      **parsed.slice(*header_params.keys)
    ).transform_keys(header_params),
    body: parsed.except(*header_params.keys),
    stream: Anthropic::Internal::Stream,
    model: Anthropic::RawMessageStreamEvent,
    options: {timeout: 600, **options}
  )
end