Module: Legion::LLM::API::OpenAI::Responses

Extended by:
Legion::Logging::Helper
Defined in:
lib/legion/llm/api/openai/responses.rb

Class Method Summary collapse

Class Method Details

.build_handler ⇒ Object

rubocop:disable Metrics/MethodLength



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# File 'lib/legion/llm/api/openai/responses.rb', line 25

def self.build_handler # rubocop:disable Metrics/MethodLength
  proc do # rubocop:disable Metrics/BlockLength
    require_llm!
    body = parse_request_body
    request_id = "resp_#{SecureRandom.hex(16)}"

    input = body[:input]
    messages = case input
               when Array
                 Responses.normalize_input_array(input)
               when String
                 [{ role: 'user', content: input }]
               else
                 halt 400, { 'Content-Type' => 'application/json' },
                      Legion::JSON.dump({ error: { message: 'input is required (string or array)',
                                                   type: 'invalid_request_error', code: nil } })
               end

    messages = [{ role: 'system', content: body[:instructions].to_s }] + messages if body[:instructions]

    model = body[:model] || Legion::LLM::Settings.value(:default_model) || 'default'
    streaming = body[:stream] == true

    tool_declarations = Responses.build_tool_declarations(body[:tools])

    log.info(
      "[llm][api][openai][responses] action=accepted request_id=#{request_id} " \
      "model=#{model} stream=#{streaming} tools=#{tool_declarations.size}"
    )

    effective_caller = build_server_caller(source: 'openai_responses', path: request.path, env: env)

    require 'legion/llm/inference/request' unless defined?(Legion::LLM::Inference::Request)
    require 'legion/llm/inference/executor' unless defined?(Legion::LLM::Inference::Executor)

    inference_request = Legion::LLM::Inference::Request.build(
      id:       request_id,
      messages: messages,
      routing:  { model: model },
      tools:    tool_declarations,
      caller:   effective_caller,
      stream:   streaming,
      cache:    { strategy: :default, cacheable: true }
    )

    executor = Legion::LLM::Inference::Executor.new(inference_request)

    if streaming
      content_type 'text/event-stream'
      headers 'Cache-Control'     => 'no-cache',
              'Connection'        => 'keep-alive',
              'X-Accel-Buffering' => 'no'

      stream do |out|
        Responses.stream_response(out, executor, request_id: request_id, model: model, upstream_body: body)
      rescue StandardError => e
        handle_exception(e, level: :error, handled: false, operation: 'llm.api.openai.responses.stream', request_id: request_id)
        out << "event: error\ndata: #{Legion::JSON.dump({ type: 'server_error', message: e.message })}\n\n"
      end
    else
      pipeline_response = executor.call_responses(body: body, stream: false)
      response_body = Responses.format_response(pipeline_response, request_id: request_id, model: model)

      log.info("[llm][api][openai][responses] action=complete request_id=#{request_id} model=#{response_body[:model]}")
      content_type :json
      status 200
      Legion::JSON.dump(response_body)
    end
  rescue Legion::LLM::AuthError => e
    handle_exception(e, level: :error, handled: true, operation: 'llm.api.openai.responses.auth')
    halt 401, { 'Content-Type' => 'application/json' },
         Legion::JSON.dump({ error: { message: e.message, type: 'authentication_error' } })
  rescue Legion::LLM::RateLimitError => e
    handle_exception(e, level: :warn, handled: true, operation: 'llm.api.openai.responses.rate_limit')
    halt 429, { 'Content-Type' => 'application/json' },
         Legion::JSON.dump({ error: { message: e.message, type: 'rate_limit_error' } })
  rescue Legion::LLM::ProviderDown, Legion::LLM::ProviderError => e
    handle_exception(e, level: :error, handled: true, operation: 'llm.api.openai.responses.provider')
    halt 502, { 'Content-Type' => 'application/json' },
         Legion::JSON.dump({ error: { message: e.message, type: 'server_error' } })
  rescue StandardError => e
    handle_exception(e, level: :error, handled: false, operation: 'llm.api.openai.responses')
    halt 500, { 'Content-Type' => 'application/json' },
         Legion::JSON.dump({ error: { message: e.message, type: 'server_error' } })
  end
end

.build_output_tool_calls(pipeline_response) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 297

def self.build_output_tool_calls(pipeline_response)
  tools_data = pipeline_response.respond_to?(:tools) ? pipeline_response.tools : nil
  return [] unless tools_data.is_a?(Array) && !tools_data.empty?

  tools_data.filter_map do |tc|
    name = tc.respond_to?(:name) ? tc.name : (tc[:name] || tc['name'])
    args = tc.respond_to?(:arguments) ? tc.arguments : (tc[:arguments] || tc['arguments'] || {})
    tc_id = tc.respond_to?(:id) ? tc.id : (tc[:id] || tc['id'] || "call_#{SecureRandom.hex(8)}")
    next unless name

    {
      type:      'function_call',
      id:        "fc_#{SecureRandom.hex(12)}",
      call_id:   tc_id,
      name:      name.to_s,
      arguments: args.is_a?(String) ? args : Legion::JSON.dump(args),
      status:    'completed'
    }
  end
end

.build_tool_declarations(tools) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 130

def self.build_tool_declarations(tools)
  return [] if tools.nil? || !tools.is_a?(Array) || tools.empty?

  tools.filter_map do |tool|
    t = tool.respond_to?(:transform_keys) ? tool.transform_keys(&:to_sym) : tool
    fn = t[:function] || t
    fn = fn.transform_keys(&:to_sym) if fn.respond_to?(:transform_keys)
    next unless fn[:name].to_s.length.positive?

    Legion::LLM::Types::ToolDefinition.build(
      name:        fn[:name].to_s,
      description: fn[:description].to_s,
      parameters:  fn[:parameters] || {},
      source:      { type: :client, executable: true }
    )
  rescue StandardError => e
    handle_exception(e, level: :warn, handled: true, operation: 'llm.api.openai.responses.build_tool')
    nil
  end
end

.build_usage(tokens) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 341

def self.build_usage(tokens)
  input_tokens = extract_token(tokens, :input_tokens)
  output_tokens = extract_token(tokens, :output_tokens)

  {
    input_tokens:  input_tokens,
    output_tokens: output_tokens,
    total_tokens:  input_tokens + output_tokens
  }
end

.call_streaming_executor(executor, upstream_body: nil) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 285

def self.call_streaming_executor(executor, upstream_body: nil, &)
  if upstream_body && executor.respond_to?(:call_responses)
    executor.call_responses(body: upstream_body, stream: true, &)
  else
    executor.call_stream(&)
  end
end

.extract_token(tokens, key) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 318

def self.extract_token(tokens, key)
  return 0 if tokens.nil?

  aliases = token_aliases(key)

  if tokens.is_a?(Hash)
    aliases.each do |candidate|
      value = tokens[candidate]
      value = tokens[candidate.to_s] if value.nil?
      return value.to_i unless value.nil?
    end

    return 0
  end

  aliases.each do |candidate|
    method_name = token_method(candidate)
    return tokens.public_send(method_name).to_i if method_name && tokens.respond_to?(method_name)
  end

  0
end

.format_response(pipeline_response, request_id:, model:) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 151

def self.format_response(pipeline_response, request_id:, model:)
  routing = pipeline_response.routing || {}
  tokens = pipeline_response.tokens || {}
  raw_msg = pipeline_response.message
  content = raw_msg.is_a?(Hash) ? (raw_msg[:content] || raw_msg['content']).to_s : raw_msg.to_s
  resolved_model = (routing[:model] || routing['model'] || model).to_s

  output = []

  tool_calls = build_output_tool_calls(pipeline_response)
  output.concat(tool_calls)

  output << {
    type:    'message',
    id:      "msg_#{SecureRandom.hex(12)}",
    role:    'assistant',
    content: [{ type: 'output_text', text: content }],
    status:  'completed'
  }

  {
    id:         request_id,
    object:     'response',
    created_at: Time.now.to_i,
    model:      resolved_model,
    output:     output,
    usage:      build_usage(tokens),
    status:     'completed'
  }
end

.normalize_input_array(input) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 112

def self.normalize_input_array(input)
  input.filter_map do |item|
    item = item.transform_keys(&:to_sym) if item.respond_to?(:transform_keys)

    case item[:type]&.to_s
    when 'function_call_output'
      { role: 'tool', tool_call_id: item[:call_id], content: item[:output].to_s }
    else
      role = item[:role]&.to_s
      next unless role

      content = item[:content]
      content = content.to_s if content && !content.is_a?(Array)
      { role: role, content: content }.compact
    end
  end
end

.registered(app) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 14

def self.registered(app)
  log.debug('[llm][api][openai][responses] registering POST /v1/responses + /api/llm/inference/v1/responses')

  handler = build_handler

  app.post('/v1/responses') { instance_exec(&handler) }
  app.post('/api/llm/inference/v1/responses') { instance_exec(&handler) }

  log.debug('[llm][api][openai][responses] routes registered')
end

.sse_event(name, payload) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 293

def self.sse_event(name, payload)
  "event: #{name}\ndata: #{Legion::JSON.dump(payload)}\n\n"
end

.stream_response(out, executor, request_id:, model:, upstream_body: nil) ⇒ Object

rubocop:disable Metrics/MethodLength



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# File 'lib/legion/llm/api/openai/responses.rb', line 182

def self.stream_response(out, executor, request_id:, model:, upstream_body: nil) # rubocop:disable Metrics/MethodLength
  created_at = Time.now.to_i
  seq = 0
  in_progress_response = { id: request_id, object: 'response', created_at: created_at,
                           status: 'in_progress', model: model, output: [], usage: nil }

  # response.created — envelope matches gateway format: { type:, response:, sequence_number: }
  out << sse_event('response.created', {
                     type:            'response.created',
                     sequence_number: seq += 1,
                     response:        in_progress_response
                   })

  out << sse_event('response.in_progress', {
                     type:            'response.in_progress',
                     sequence_number: seq += 1,
                     response:        in_progress_response
                   })

  msg_id = "msg_#{SecureRandom.hex(12)}"
  out << sse_event('response.output_item.added', {
                     type:            'response.output_item.added',
                     sequence_number: seq += 1,
                     output_index:    0,
                     item:            { id: msg_id, type: 'message', role: 'assistant',
                       content: [], status: 'in_progress' }
                   })

  out << sse_event('response.content_part.added', {
                     type:            'response.content_part.added',
                     sequence_number: seq += 1,
                     output_index:    0,
                     content_index:   0,
                     item_id:         msg_id,
                     part:            { type: 'output_text', text: '', annotations: [] }
                   })

  full_text = +''

  pipeline_response = call_streaming_executor(executor, upstream_body: upstream_body) do |chunk|
    text = chunk.respond_to?(:content) ? chunk.content.to_s : chunk.to_s
    next if text.empty?

    full_text << text
    out << sse_event('response.output_text.delta', {
                       type:            'response.output_text.delta',
                       sequence_number: seq += 1,
                       output_index:    0,
                       content_index:   0,
                       item_id:         msg_id,
                       delta:           text
                     })
  end

  routing = pipeline_response.routing || {}
  tokens  = pipeline_response.tokens || {}
  resolved_model = (routing[:model] || routing['model'] || model).to_s
  usage = build_usage(tokens)

  out << sse_event('response.output_text.done', {
                     type:            'response.output_text.done',
                     sequence_number: seq += 1,
                     output_index:    0,
                     content_index:   0,
                     item_id:         msg_id,
                     text:            full_text
                   })

  out << sse_event('response.content_part.done', {
                     type:            'response.content_part.done',
                     sequence_number: seq += 1,
                     output_index:    0,
                     content_index:   0,
                     item_id:         msg_id,
                     part:            { type: 'output_text', text: full_text, annotations: [] }
                   })

  completed_item = { id: msg_id, type: 'message', role: 'assistant', status: 'completed',
                     content: [{ type: 'output_text', text: full_text, annotations: [] }] }
  out << sse_event('response.output_item.done', {
                     type:            'response.output_item.done',
                     sequence_number: seq += 1,
                     output_index:    0,
                     item:            completed_item
                   })

  out << sse_event('response.completed', {
                     type:            'response.completed',
                     sequence_number: seq + 1,
                     response:        {
                       id:         request_id,
                       object:     'response',
                       created_at: created_at,
                       status:     'completed',
                       model:      resolved_model,
                       output:     [completed_item],
                       usage:      usage
                     }
                   })

  log.info("[llm][api][openai][responses] action=stream_complete request_id=#{request_id} model=#{resolved_model}")
end

.token_aliases(key) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 352

def self.token_aliases(key)
  case key.to_sym
  when :input, :input_tokens
    %i[input_tokens input]
  when :output, :output_tokens
    %i[output_tokens output]
  else
    [key.to_sym]
  end
end

.token_method(key) ⇒ Object 



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# File 'lib/legion/llm/api/openai/responses.rb', line 363

def self.token_method(key)
  {
    input:         :input_tokens,
    input_tokens:  :input_tokens,
    output:        :output_tokens,
    output_tokens: :output_tokens
  }[key.to_sym]
end