# frozen_string_literal: true
module Anthropic
module Models
# @see Anthropic::Resources::Messages#create
#
# @see Anthropic::Resources::Messages#stream_raw
class MessageCreateParams < Anthropic::Internal::Type::BaseModel
# @!parse
# extend Anthropic::Internal::Type::RequestParameters::Converter
include Anthropic::Internal::Type::RequestParameters
# @!attribute max_tokens
# The maximum number of tokens to generate before stopping.
#
# Note that our models may stop _before_ reaching this maximum. This parameter
# only specifies the absolute maximum number of tokens to generate.
#
# Different models have different maximum values for this parameter. See
# [models](https://docs.anthropic.com/en/docs/models-overview) for details.
#
# @return [Integer]
required :max_tokens, Integer
# @!attribute messages
# 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" }] }
# ```
#
# Starting with Claude 3 models, you can also send image content blocks:
#
# ```json
# {
# "role": "user",
# "content": [
# {
# "type": "image",
# "source": {
# "type": "base64",
# "media_type": "image/jpeg",
# "data": "/9j/4AAQSkZJRg..."
# }
# },
# { "type": "text", "text": "What is in this image?" }
# ]
# }
# ```
#
# We currently support the `base64` source type for images, and the `image/jpeg`,
# `image/png`, `image/gif`, and `image/webp` media types.
#
# See [examples](https://docs.anthropic.com/en/api/messages-examples#vision) for
# more input examples.
#
# Note that if you want to include a
# [system prompt](https://docs.anthropic.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.
#
# @return [Array<Anthropic::Models::MessageParam>]
required :messages, -> { Anthropic::Internal::Type::ArrayOf[Anthropic::Models::MessageParam] }
# @!attribute model
# The model that will complete your prompt.\n\nSee
# [models](https://docs.anthropic.com/en/docs/models-overview) for additional
# details and options.
#
# @return [Symbol, String, Anthropic::Models::Model]
required :model, union: -> { Anthropic::Models::Model }
# @!attribute [r] metadata
# An object describing metadata about the request.
#
# @return [Anthropic::Models::Metadata, nil]
optional :metadata, -> { Anthropic::Models::Metadata }
# @!parse
# # @return [Anthropic::Models::Metadata]
# attr_writer :metadata
# @!attribute [r] stop_sequences
# Custom text sequences that will cause the model to stop generating.
#
# Our models will normally stop when they have naturally completed their turn,
# which will result in a response `stop_reason` of `"end_turn"`.
#
# If you want the model to stop generating when it encounters custom strings of
# text, you can use the `stop_sequences` parameter. If the model encounters one of
# the custom sequences, the response `stop_reason` value will be `"stop_sequence"`
# and the response `stop_sequence` value will contain the matched stop sequence.
#
# @return [Array<String>, nil]
optional :stop_sequences, Anthropic::Internal::Type::ArrayOf[String]
# @!parse
# # @return [Array<String>]
# attr_writer :stop_sequences
# @!attribute [r] system_
# 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](https://docs.anthropic.com/en/docs/system-prompts).
#
# @return [String, Array<Anthropic::Models::TextBlockParam>, nil]
optional :system_, union: -> { Anthropic::Models::MessageCreateParams::System }, api_name: :system
# @!parse
# # @return [String, Array<Anthropic::Models::TextBlockParam>]
# attr_writer :system_
# @!attribute [r] temperature
# Amount of randomness injected into the response.
#
# Defaults to `1.0`. Ranges from `0.0` to `1.0`. Use `temperature` closer to `0.0`
# for analytical / multiple choice, and closer to `1.0` for creative and
# generative tasks.
#
# Note that even with `temperature` of `0.0`, the results will not be fully
# deterministic.
#
# @return [Float, nil]
optional :temperature, Float
# @!parse
# # @return [Float]
# attr_writer :temperature
# @!attribute [r] thinking
# 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](https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking)
# for details.
#
# @return [Anthropic::Models::ThinkingConfigEnabled, Anthropic::Models::ThinkingConfigDisabled, nil]
optional :thinking, union: -> { Anthropic::Models::ThinkingConfigParam }
# @!parse
# # @return [Anthropic::Models::ThinkingConfigEnabled, Anthropic::Models::ThinkingConfigDisabled]
# attr_writer :thinking
# @!attribute [r] tool_choice
# 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.
#
# @return [Anthropic::Models::ToolChoiceAuto, Anthropic::Models::ToolChoiceAny, Anthropic::Models::ToolChoiceTool, Anthropic::Models::ToolChoiceNone, nil]
optional :tool_choice, union: -> { Anthropic::Models::ToolChoice }
# @!parse
# # @return [Anthropic::Models::ToolChoiceAuto, Anthropic::Models::ToolChoiceAny, Anthropic::Models::ToolChoiceTool, Anthropic::Models::ToolChoiceNone]
# attr_writer :tool_choice
# @!attribute [r] tools
# 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.
#
# Each tool definition includes:
#
# - `name`: Name of the tool.
# - `description`: Optional, but strongly-recommended description of the tool.
# - `input_schema`: [JSON schema](https://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 `{"ticker": "^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](https://docs.anthropic.com/en/docs/tool-use) for more details.
#
# @return [Array<Anthropic::Models::Tool, Anthropic::Models::ToolBash20250124, Anthropic::Models::ToolTextEditor20250124>, nil]
optional :tools, -> { Anthropic::Internal::Type::ArrayOf[union: Anthropic::Models::ToolUnion] }
# @!parse
# # @return [Array<Anthropic::Models::Tool, Anthropic::Models::ToolBash20250124, Anthropic::Models::ToolTextEditor20250124>]
# attr_writer :tools
# @!attribute [r] top_k
# Only sample from the top K options for each subsequent token.
#
# Used to remove "long tail" low probability responses.
# [Learn more technical details here](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277).
#
# Recommended for advanced use cases only. You usually only need to use
# `temperature`.
#
# @return [Integer, nil]
optional :top_k, Integer
# @!parse
# # @return [Integer]
# attr_writer :top_k
# @!attribute [r] top_p
# Use nucleus sampling.
#
# In nucleus sampling, we compute the cumulative distribution over all the options
# for each subsequent token in decreasing probability order and cut it off once it
# reaches a particular probability specified by `top_p`. You should either alter
# `temperature` or `top_p`, but not both.
#
# Recommended for advanced use cases only. You usually only need to use
# `temperature`.
#
# @return [Float, nil]
optional :top_p, Float
# @!parse
# # @return [Float]
# attr_writer :top_p
# @!parse
# # @param max_tokens [Integer]
# # @param messages [Array<Anthropic::Models::MessageParam>]
# # @param model [Symbol, String, Anthropic::Models::Model]
# # @param metadata [Anthropic::Models::Metadata]
# # @param stop_sequences [Array<String>]
# # @param system_ [String, Array<Anthropic::Models::TextBlockParam>]
# # @param temperature [Float]
# # @param thinking [Anthropic::Models::ThinkingConfigEnabled, Anthropic::Models::ThinkingConfigDisabled]
# # @param tool_choice [Anthropic::Models::ToolChoiceAuto, Anthropic::Models::ToolChoiceAny, Anthropic::Models::ToolChoiceTool, Anthropic::Models::ToolChoiceNone]
# # @param tools [Array<Anthropic::Models::Tool, Anthropic::Models::ToolBash20250124, Anthropic::Models::ToolTextEditor20250124>]
# # @param top_k [Integer]
# # @param top_p [Float]
# # @param request_options [Anthropic::RequestOptions, Hash{Symbol=>Object}]
# #
# def initialize(
# max_tokens:,
# messages:,
# model:,
# metadata: nil,
# stop_sequences: nil,
# system_: nil,
# temperature: nil,
# thinking: nil,
# tool_choice: nil,
# tools: nil,
# top_k: nil,
# top_p: nil,
# request_options: {},
# **
# )
# super
# end
# def initialize: (Hash | Anthropic::Internal::Type::BaseModel) -> void
# 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](https://docs.anthropic.com/en/docs/system-prompts).
module System
extend Anthropic::Internal::Type::Union
variant String
variant -> { Anthropic::Models::MessageCreateParams::System::TextBlockParamArray }
# @!parse
# # @return [Array(String, Array<Anthropic::Models::TextBlockParam>)]
# def self.variants; end
TextBlockParamArray = Anthropic::Internal::Type::ArrayOf[-> { Anthropic::Models::TextBlockParam }]
end
end
end
end