Class: Anthropic::Models::Beta::MessageCountTokensParams

Inherits:
Internal::Type::BaseModel show all
Extended by:
Internal::Type::RequestParameters::Converter
Includes:
Internal::Type::RequestParameters
Defined in:
lib/anthropic/models/beta/message_count_tokens_params.rb

Overview

See Also:

Defined Under Namespace

Modules: System, Tool

Instance Attribute Summary collapse

Attributes included from Internal::Type::RequestParameters

#request_options

Instance Method Summary collapse

Methods included from Internal::Type::RequestParameters::Converter

dump_request

Methods included from Internal::Type::RequestParameters

included

Methods inherited from Internal::Type::BaseModel

==, #==, #[], coerce, #deconstruct_keys, #deep_to_h, dump, fields, hash, #hash, inherited, inspect, #inspect, known_fields, optional, recursively_to_h, required, #to_h, #to_json, #to_s, to_sorbet_type, #to_yaml

Methods included from Internal::Type::Converter

#coerce, coerce, #dump, dump, inspect, #inspect, meta_info, new_coerce_state, type_info

Methods included from Internal::Util::SorbetRuntimeSupport

#const_missing, #define_sorbet_constant!, #sorbet_constant_defined?, #to_sorbet_type, to_sorbet_type

Constructor Details

#initialize(messages: , model: , context_management: nil, mcp_servers: nil, system_: nil, thinking: nil, tool_choice: nil, tools: nil, betas: nil, request_options: {}) ⇒ Object

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

Parameters:




# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 223

Instance Attribute Details

#betas ⇒ Array<String, Symbol, Anthropic::Models::AnthropicBeta>?

Optional header to specify the beta version(s) you want to use.

Returns:



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# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 221

optional :betas, -> { Anthropic::Internal::Type::ArrayOf[union: Anthropic::AnthropicBeta] }

#context_management ⇒ Anthropic::Models::Beta::BetaContextManagementConfig?

Context management configuration.

This allows you to control how Claude manages context across multiple requests, such as whether to clear function results or not.

Returns:



96
 
# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 96

optional :context_management, -> { Anthropic::Beta::BetaContextManagementConfig }, nil?: true

#mcp_servers ⇒ Array<Anthropic::Models::Beta::BetaRequestMCPServerURLDefinition>?

MCP servers to be utilized in this request

Returns:



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# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 102

optional :mcp_servers,
-> { Anthropic::Internal::Type::ArrayOf[Anthropic::Beta::BetaRequestMCPServerURLDefinition] }

#messages ⇒ Array<Anthropic::Models::Beta::BetaMessageParam>

Input messages.

Our models are trained to operate on alternating ‘user` and `assistant` conversational turns. When creating a new `Message`, you specify the prior conversational turns with the `messages` parameter, and the model then generates the next `Message` in the conversation. Consecutive `user` or `assistant` turns in your request will be combined into a single turn.

Each input message must be an object with a ‘role` and `content`. You can specify a single `user`-role message, or you can include multiple `user` and `assistant` messages.

If the final message uses the ‘assistant` role, the response content will continue immediately from the content in that message. This can be used to constrain part of the model’s response.

Example with a single ‘user` message:

“‘json

{ “role”: “user”, “content”: “Hello, Claude” }

“‘

Example with multiple conversational turns:

“‘json [

{ "role": "user", "content": "Hello there." },
{ "role": "assistant", "content": "Hi, I'm Claude. How can I help you?" },
{ "role": "user", "content": "Can you explain LLMs in plain English?" }

] “‘

Example with a partially-filled response from Claude:

“‘json [

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

] “‘

Each input message ‘content` may be either a single `string` or an array of content blocks, where each block has a specific `type`. Using a `string` for `content` is shorthand for an array of one content block of type `“text”`. The following input messages are equivalent:

“‘json { “role”: “user”, “content”: “Hello, Claude” } “`

“‘json { “role”: “user”, “content”: [{ “type”: “text”, “text”: “Hello, Claude” }] } “`

See [input examples](docs.claude.com/en/api/messages-examples).

Note that if you want to include a [system prompt](docs.claude.com/en/docs/system-prompts), you can use the top-level ‘system` parameter — there is no `“system”` role for input messages in the Messages API.

There is a limit of 100,000 messages in a single request.

Returns:



79
 
# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 79

required :messages, -> { Anthropic::Internal::Type::ArrayOf[Anthropic::Beta::BetaMessageParam] }

#model ⇒ Symbol, ...

The model that will complete your prompt.nnSee [models](docs.anthropic.com/en/docs/models-overview) for additional details and options.

Returns:



87
 
# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 87

required :model, union: -> { Anthropic::Model }

#system_ ⇒ String, ...

System prompt.

A system prompt is a way of providing context and instructions to Claude, such as specifying a particular goal or role. See our [guide to system prompts](docs.claude.com/en/docs/system-prompts).

Returns:



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# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 113

optional :system_, union: -> { Anthropic::Beta::MessageCountTokensParams::System }, api_name: :system

#thinking ⇒ Anthropic::Models::Beta::BetaThinkingConfigEnabled, ...

Configuration for enabling Claude’s extended thinking.

When enabled, responses include ‘thinking` content blocks showing Claude’s thinking process before the final answer. Requires a minimum budget of 1,024 tokens and counts towards your ‘max_tokens` limit.

See [extended thinking](docs.claude.com/en/docs/build-with-claude/extended-thinking) for details.

Returns:



127
 
# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 127

optional :thinking, union: -> { Anthropic::Beta::BetaThinkingConfigParam }

#tool_choice ⇒ Anthropic::Models::Beta::BetaToolChoiceAuto, ...

How the model should use the provided tools. The model can use a specific tool, any available tool, decide by itself, or not use tools at all.

Returns:



134
 
# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 134

optional :tool_choice, union: -> { Anthropic::Beta::BetaToolChoice }

#tools ⇒ Array<Anthropic::Models::Beta::BetaTool, Anthropic::Models::Beta::BetaToolBash20241022, Anthropic::Models::Beta::BetaToolBash20250124, Anthropic::Models::Beta::BetaCodeExecutionTool20250522, Anthropic::Models::Beta::BetaCodeExecutionTool20250825, Anthropic::Models::Beta::BetaToolComputerUse20241022, Anthropic::Models::Beta::BetaMemoryTool20250818, Anthropic::Models::Beta::BetaToolComputerUse20250124, Anthropic::Models::Beta::BetaToolTextEditor20241022, Anthropic::Models::Beta::BetaToolTextEditor20250124, Anthropic::Models::Beta::BetaToolTextEditor20250429, Anthropic::Models::Beta::BetaToolTextEditor20250728, Anthropic::Models::Beta::BetaWebSearchTool20250305, Anthropic::Models::Beta::BetaWebFetchTool20250910>?

Definitions of tools that the model may use.

If you include ‘tools` in your API request, the model may return `tool_use` content blocks that represent the model’s use of those tools. You can then run those tools using the tool input generated by the model and then optionally return results back to the model using ‘tool_result` content blocks.

There are two types of tools: **client tools** and **server tools**. The behavior described below applies to client tools. For [server tools](docs.claude.com/en/docs/agents-and-tools/tool-use/overview#server-tools), see their individual documentation as each has its own behavior (e.g., the [web search tool](docs.claude.com/en/docs/agents-and-tools/tool-use/web-search-tool)).

Each tool definition includes:

  • ‘name`: Name of the tool.

  • ‘description`: Optional, but strongly-recommended description of the tool.

  • ‘input_schema`: [JSON schema](json-schema.org/draft/2020-12) for the tool `input` shape that the model will produce in `tool_use` output content blocks.

For example, if you defined ‘tools` as:

“‘json [

{
  "name": "get_stock_price",
  "description": "Get the current stock price for a given ticker symbol.",
  "input_schema": {
    "type": "object",
    "properties": {
      "ticker": {
        "type": "string",
        "description": "The stock ticker symbol, e.g. AAPL for Apple Inc."
      }
    },
    "required": ["ticker"]
  }
}

] “‘

And then asked the model “What’s the S&P 500 at today?”, the model might produce ‘tool_use` content blocks in the response like this:

“‘json [

{
  "type": "tool_use",
  "id": "toolu_01D7FLrfh4GYq7yT1ULFeyMV",
  "name": "get_stock_price",
  "input": { "ticker": "^GSPC" }
}

] “‘

You might then run your ‘get_stock_price` tool with `“^GSPC”` as an input, and return the following back to the model in a subsequent `user` message:

“‘json [

{
  "type": "tool_result",
  "tool_use_id": "toolu_01D7FLrfh4GYq7yT1ULFeyMV",
  "content": "259.75 USD"
}

] “‘

Tools can be used for workflows that include running client-side tools and functions, or more generally whenever you want the model to produce a particular JSON structure of output.

See our [guide](docs.claude.com/en/docs/tool-use) for more details.

Returns:



214
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# File 'lib/anthropic/models/beta/message_count_tokens_params.rb', line 214

optional :tools,
-> { Anthropic::Internal::Type::ArrayOf[union: Anthropic::Beta::MessageCountTokensParams::Tool] }