module RubyLLM::Providers::VertexAI::Embeddings

# File lib/ruby_llm/providers/vertexai/embeddings.rb, line 10
def embedding_url(model:)
  "projects/#{@config.vertexai_project_id}/locations/#{@config.vertexai_location}/publishers/google/models/#{model}:predict" # rubocop:disable Layout/LineLength
end

# File lib/ruby_llm/providers/vertexai/embeddings.rb, line 22
def parse_embedding_response(response, model:, text:)
  predictions = response.body['predictions']
  vectors = predictions&.map { |p| p.dig('embeddings', 'values') }
  vectors = vectors.first if vectors&.length == 1 && !text.is_a?(Array)

  Embedding.new(vectors:, model:, input_tokens: 0)
end

# File lib/ruby_llm/providers/vertexai/embeddings.rb, line 14
def render_embedding_payload(text, model:, dimensions:) # rubocop:disable Lint/UnusedMethodArgument
  {
    instances: [text].flatten.map { |t| { content: t.to_s } }
  }.tap do |payload|
    payload[:parameters] = { outputDimensionality: dimensions } if dimensions
  end
end