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3b13aaa003
Refresh several AI model presets to newer provider versions and adjust pricing/capacity metadata accordingly. Also add support for the new `xhigh` effort level across Anthropic and Bedrock request handling and update the LLM admin UI/specs to match the renamed presets.
109 lines
3.3 KiB
Ruby
Vendored
109 lines
3.3 KiB
Ruby
Vendored
# frozen_string_literal: true
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module DiscourseAi
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module Completions
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module Endpoints
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class Anthropic < Base
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include AnthropicPromptCache
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include AnthropicShared
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def self.can_contact?(llm_model)
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llm_model.provider == "anthropic"
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end
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def default_options(dialect)
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mapped_model =
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case llm_model.name
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when "claude-2"
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"claude-2.1"
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when "claude-instant-1"
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"claude-instant-1.2"
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when "claude-3-haiku"
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"claude-3-haiku-20240307"
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when "claude-3-sonnet"
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"claude-3-sonnet-20240229"
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when "claude-3-opus"
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"claude-3-opus-20240229"
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when "claude-3-5-sonnet"
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"claude-3-5-sonnet-latest"
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when "claude-3-7-sonnet"
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"claude-3-7-sonnet-latest"
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when "claude-4-opus"
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"claude-4-opus-20250514"
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when "claude-4-sonnet"
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"claude-4-sonnet-20250514"
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else
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llm_model.name
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end
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# Note: Anthropic requires this param
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max_tokens = 4096
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# 3.5 and 3.7 models have a higher token limit
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max_tokens = 8192 if mapped_model.match?(/3.[57]/)
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options = { model: mapped_model, max_tokens: max_tokens }
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if llm_model.lookup_custom_param("adaptive_thinking")
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options[:thinking] = { type: "adaptive" }
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options[:max_tokens] = 32_000
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elsif llm_model.lookup_custom_param("enable_reasoning")
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reasoning_tokens =
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llm_model.lookup_custom_param("reasoning_tokens").to_i.clamp(1024, 32_768)
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# this allows for lots of tokens beyond reasoning
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options[:max_tokens] = reasoning_tokens + 30_000
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options[:thinking] = { type: "enabled", budget_tokens: reasoning_tokens }
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end
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options[:stop_sequences] = ["</function_calls>"] if !dialect.native_tool_support? &&
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dialect.prompt.has_tools?
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# effort parameter
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effort = llm_model.lookup_custom_param("effort")
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options[:output_config] = { effort: effort } if AnthropicShared::EFFORT_VALUES.include?(
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effort,
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)
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options
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end
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private
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def model_uri
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URI(llm_model.url)
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end
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def prepare_payload(prompt, model_params, dialect)
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payload = prepare_claude_payload(prompt, model_params, dialect)
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payload[:stream] = true if @streaming_mode
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payload
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end
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def prepare_request(payload)
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headers = {
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"anthropic-version" => "2023-06-01",
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"x-api-key" => llm_model.api_key,
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"content-type" => "application/json",
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}
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Net::HTTP::Post.new(model_uri, headers).tap { |r| r.body = payload }
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end
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def decode_chunk(partial_data)
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@decoder ||= JsonStreamDecoder.new
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(@decoder << partial_data)
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.map { |parsed_json| processor.process_streamed_message(parsed_json) }
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.compact
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end
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def processor
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claude_processor
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end
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def final_log_update(log)
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update_log_from_claude_processor(log)
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end
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end
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end
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end
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end
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