Class: DSPy::Anthropic::LM::Adapters::AnthropicAdapter

Inherits:
LM::Adapter
  • Object
show all
Defined in:
lib/dspy/anthropic/lm/adapters/anthropic_adapter.rb

Instance Method Summary collapse

Constructor Details

#initialize(model:, api_key:, structured_outputs: true) ⇒ AnthropicAdapter

Returns a new instance of AnthropicAdapter.



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# File 'lib/dspy/anthropic/lm/adapters/anthropic_adapter.rb', line 15

def initialize(model:, api_key:, structured_outputs: true)
  super(model: model, api_key: api_key)
  validate_api_key!(api_key, 'anthropic')
  @client = ::Anthropic::Client.new(api_key: api_key)
  @structured_outputs_enabled = structured_outputs
end

Instance Method Details

#chat(messages:, signature: nil, **extra_params, &block) ⇒ Object 



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# File 'lib/dspy/anthropic/lm/adapters/anthropic_adapter.rb', line 22

def chat(messages:, signature: nil, **extra_params, &block)
  normalized_messages = normalize_messages(messages)

  # Validate vision support if images are present
  if contains_images?(normalized_messages)
    DSPy::LM::VisionModels.validate_vision_support!('anthropic', model)
    # Convert messages to Anthropic format with proper image handling
    normalized_messages = format_multimodal_messages(normalized_messages)
  end

  # Anthropic requires system message to be separate from messages
  system_message, user_messages = extract_system_message(normalized_messages)

  # Check if this is a tool use request
  has_tools = extra_params.key?(:tools) && !extra_params[:tools].empty?

  # Apply JSON prefilling if needed for better Claude JSON compliance (but not for tool use)
  unless has_tools || contains_images?(normalized_messages)
    user_messages = prepare_messages_for_json(user_messages, system_message)
  end

  request_params = {
    model: model,
    messages: user_messages,
    max_tokens: 4096, # Required for Anthropic
    temperature: 0.0 # DSPy default for deterministic responses
  }.merge(extra_params)

  # Add system message if present
  request_params[:system] = system_message if system_message

  # Add streaming if block provided
  if block_given?
    request_params[:stream] = true
  end

  begin
    if block_given?
      content = ""
      @client.messages.stream(**request_params) do |chunk|
        if chunk.respond_to?(:delta) && chunk.delta.respond_to?(:text)
          chunk_text = chunk.delta.text
          content += chunk_text
          block.call(chunk)
        end
      end

      # Create typed metadata for streaming response
      metadata = DSPy::LM::ResponseMetadataFactory.create('anthropic', {
        model: model,
        streaming: true
      })

      DSPy::LM::Response.new(
        content: content,
        usage: nil, # Usage not available in streaming
        metadata: metadata
      )
    else
      response = @client.messages.create(**request_params)

      if response.respond_to?(:error) && response.error
        raise DSPy::LM::AdapterError, "Anthropic API error: #{response.error}"
      end

      # Handle both text content and tool use
      content = ""
      tool_calls = []

      if response.content.is_a?(Array)
        response.content.each do |content_block|
          case content_block.type.to_s
          when "text"
            content += content_block.text
          when "tool_use"
            tool_calls << {
              id: content_block.id,
              name: content_block.name,
              input: content_block.input
            }
          end
        end
      end

      usage = response.usage

      # Convert usage data to typed struct
      usage_struct = DSPy::LM::UsageFactory.create('anthropic', usage)

      metadata = {
        provider: 'anthropic',
        model: model,
        response_id: response.id,
        role: response.role
      }

      # Add tool calls to metadata if present
      metadata[:tool_calls] = tool_calls unless tool_calls.empty?

      # Create typed metadata
      typed_metadata = DSPy::LM::ResponseMetadataFactory.create('anthropic', metadata)

      DSPy::LM::Response.new(
        content: content,
        usage: usage_struct,
        metadata: typed_metadata
      )
    end
  rescue => e
    # Check for specific image-related errors in the message
    error_msg = e.message.to_s

    if error_msg.include?('Could not process image')
      raise DSPy::LM::AdapterError, "Image processing failed: #{error_msg}. Ensure your image is a valid PNG, JPEG, GIF, or WebP format, properly base64-encoded, and under 5MB."
    elsif error_msg.include?('image')
      raise DSPy::LM::AdapterError, "Image error: #{error_msg}. Anthropic requires base64-encoded images (URLs are not supported)."
    elsif error_msg.include?('rate')
      raise DSPy::LM::AdapterError, "Anthropic rate limit exceeded: #{error_msg}. Please wait and try again."
    elsif error_msg.include?('authentication') || error_msg.include?('API key')
      raise DSPy::LM::AdapterError, "Anthropic authentication failed: #{error_msg}. Check your API key."
    else
      # Generic error handling
      raise DSPy::LM::AdapterError, "Anthropic adapter error: #{e.message}"
    end
  end
end