module RubyLLM::Providers::OpenAI::Embeddings

# File lib/ruby_llm/providers/openai/embeddings.rb, line 10
def embedding_url(...)
  'embeddings'
end

# File lib/ruby_llm/providers/openai/embeddings.rb, line 22
def parse_embedding_response(response, model:, text:)
  data = response.body
  input_tokens = data.dig('usage', 'prompt_tokens') || 0
  vectors = data['data'].map { |d| d['embedding'] }
  vectors = vectors.first if vectors.length == 1 && !text.is_a?(Array)

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

# File lib/ruby_llm/providers/openai/embeddings.rb, line 14
def render_embedding_payload(text, model:, dimensions:)
  {
    model: model,
    input: text,
    dimensions: dimensions
  }.compact
end