Class: Legion::LLM::API::ClientTranslators::OpenAIChat

Inherits:
Object
  • Object
show all
Extended by:
Legion::Logging::Helper
Includes:
SharedExtractors, Legion::Logging::Helper
Defined in:
lib/legion/llm/api/client_translators/openai_chat.rb

Overview

OpenAI /v1/chat/completions client translator.

Per Phase 5: parse_request → Canonical::Request, format_response →chat.completion shape, format_error, events emitter for the chat completion SSE format (data: chunknn + data: [DONE]).

Defined Under Namespace

Classes: Events

Constant Summary collapse

Canonical = 
Legion::Extensions::Llm::Canonical
FINISH_REASON_MAP = 
{
  end_turn:       'stop',
  tool_use:       'tool_calls',
  max_tokens:     'length',
  stop_sequence:  'stop',
  content_filter: 'content_filter',
  error:          'stop',
  pause_turn:     'tool_calls'
}.freeze

Instance Method Summary collapse

Methods included from SharedExtractors

#args_as_json_string, #args_as_object, #extract_content_text, #extract_thinking_text, #legion_routing_explicit_from_env, #legion_routing_from_env, #text_content_type?, #token_value

Instance Method Details

#build_inference_request(canonical_request, request_id:, server_caller:, modality: nil) ⇒ Object 



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# File 'lib/legion/llm/api/client_translators/openai_chat.rb', line 77

def build_inference_request(canonical_request, request_id:, server_caller:, modality: nil)
  tool_defs = build_tool_definitions(canonical_request.tools)

  extra = {}
  tier = canonical_request.metadata[:tier]
  cwd = canonical_request.metadata[:cwd]
  extra[:tier] = tier.to_sym if tier
  extra[:cwd] = cwd if cwd
  routing_explicit = canonical_request.metadata[:routing_explicit]
  extra[:routing_explicit] = routing_explicit if routing_explicit

  metadata = { requested_tools: canonical_request.metadata[:requested_tools] || [] }
  metadata[:client_tool_passthrough] = canonical_request.metadata[:client_tool_passthrough] unless canonical_request.metadata[:client_tool_passthrough].nil?
  metadata[:client_tool_request_count] = canonical_request.tools&.size if canonical_request.tools&.any?

  messages = inference_messages(canonical_request.messages)

  Legion::LLM::Inference::Request.build(
    id:              request_id,
    messages:        messages,
    system:          canonical_request.system,
    routing:         canonical_request.routing,
    tools:           tool_defs,
    tool_choice:     canonical_request.tool_choice,
    caller:          server_caller,
    conversation_id: canonical_request.conversation_id,
    metadata:        metadata.compact,
    stream:          canonical_request.stream == true,
    modality:        modality,
    cache:           { strategy: :default, cacheable: true },
    extra:           extra.empty? ? {} : extra
  )
end

#events_emitter(out, request_id:, model:, conv_id: nil, include_reasoning: true) ⇒ Object 



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# File 'lib/legion/llm/api/client_translators/openai_chat.rb', line 185

def events_emitter(out, request_id:, model:, conv_id: nil, include_reasoning: true)
  Events.new(out: out, request_id: request_id, model: model.to_s, conv_id: conv_id, include_reasoning: include_reasoning)
end

#extract_tool_choice(raw) ⇒ Object

OpenAI chat-completions tool_choice shapes:

"auto" / "none" / "required"                       → sym
{type: 'function', function: {name: 'X'}}          → {type: 'function', name: 'X'}
{type: 'function', name: 'X'} (lenient passthrough)→ {type: 'function', name: 'X'}



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# File 'lib/legion/llm/api/client_translators/openai_chat.rb', line 115

def extract_tool_choice(raw)
  return nil if raw.nil?

  case raw
  when Hash
    symbolized = raw.transform_keys(&:to_sym)
    type = symbolized[:type].to_s
    if type == 'function'
      fn = symbolized[:function].is_a?(Hash) ? symbolized[:function].transform_keys(&:to_sym) : nil
      name = symbolized[:name] || fn&.[](:name)
      return { type: :function, name: name.to_s } if name

      symbolized
    else
      %w[auto none required].include?(type) ? type.to_sym : symbolized
    end
  when String, Symbol
    raw.to_sym
  end
end

#format_chunk(canonical_chunk) ⇒ Object 



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# File 'lib/legion/llm/api/client_translators/openai_chat.rb', line 189

def format_chunk(canonical_chunk)
  return nil if canonical_chunk.nil?

  case canonical_chunk.type
  when :text_delta
    chunk_envelope({ content: canonical_chunk.delta.to_s })
  when :thinking_delta
    chunk_envelope({ reasoning_content: canonical_chunk.delta.to_s })
  when :tool_call_delta
    tc = canonical_chunk.tool_call
    args = tc.respond_to?(:arguments) ? tc.arguments : {}
    chunk_envelope({
                     tool_calls: [{
                       index:    canonical_chunk.block_index || 0,
                       id:       tc.respond_to?(:id) ? tc.id : nil,
                       type:     'function',
                       function: {
                         name:      tc.respond_to?(:name) ? tc.name.to_s : '',
                         arguments: args_as_json_string(args)
                       }
                     }]
                   })
  when :done
    { object: 'chat.completion.chunk', choices: [{ index: 0, delta: {}, finish_reason: 'stop' }] }
  end
end

#format_error(error, status_code: 500, type: 'server_error', code: nil) ⇒ Object 



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# File 'lib/legion/llm/api/client_translators/openai_chat.rb', line 179

def format_error(error, status_code: 500, type: 'server_error', code: nil)
  body = { error: { message: error.respond_to?(:message) ? error.message : error.to_s, type: type } }
  body[:error][:code] = code if code
  [status_code, body]
end

#format_response(pipeline_response, model:, request_id:, include_reasoning: false) ⇒ Object 



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# File 'lib/legion/llm/api/client_translators/openai_chat.rb', line 136

def format_response(pipeline_response, model:, request_id:, include_reasoning: false)
  request_id ||= SecureRandom.uuid
  routing = pipeline_response.respond_to?(:routing) ? pipeline_response.routing || {} : {}
  tokens = pipeline_response.respond_to?(:tokens) ? pipeline_response.tokens || {} : {}
  raw_msg = pipeline_response.respond_to?(:message) ? pipeline_response.message : nil
  content = extract_content_text(raw_msg)
  content = server_tool_results_text(pipeline_response) if content.empty?
  stop_reason = pipeline_response.respond_to?(:stop) ? pipeline_response.stop&.dig(:reason)&.to_s : nil

  actionable_tool_calls = build_tool_calls(pipeline_response)
  resolved_model = (routing[:model] || routing['model'] || model).to_s

  # G24 — server-executed tools are not actionable. When all tool
  # calls were server-resolved, finish_reason is 'stop' (not
  # 'tool_calls') and the model's text content is the only
  # client-visible turn. The server-resolved exchange is recorded
  # in the conversation history (via the executor's tool loop),
  # not on this response.
  finish_reason = actionable_tool_calls.empty? ? map_finish_reason(stop_reason) : 'tool_calls'

  content = nil if actionable_tool_calls.any? && content_looks_like_tool_json?(content)

  message_body = { role: 'assistant', content: content }
  message_body[:tool_calls] = actionable_tool_calls unless actionable_tool_calls.empty?

  if include_reasoning && pipeline_response.respond_to?(:thinking) && pipeline_response.thinking
    text = extract_thinking_text(pipeline_response.thinking)
    message_body[:reasoning_content] = text unless text.empty?
  end

  input = token_value(tokens, :input, :input_tokens).to_i
  output = token_value(tokens, :output, :output_tokens).to_i

  {
    id:      "chatcmpl-#{request_id.delete('-')}",
    object:  'chat.completion',
    created: Time.now.to_i,
    model:   resolved_model,
    choices: [{ index: 0, message: message_body, finish_reason: finish_reason }],
    usage:   { prompt_tokens: input, completion_tokens: output, total_tokens: input + output }
  }
end

#g24_format ⇒ Object

G24 — declares which execution-proxy contract shape this translator surfaces. Consumed by the lex-llm conformance shared examples.



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# File 'lib/legion/llm/api/client_translators/openai_chat.rb', line 39

def g24_format
  :openai_chat
end

#parse_request(body, env = {}) ⇒ Object 



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# File 'lib/legion/llm/api/client_translators/openai_chat.rb', line 43

def parse_request(body, env = {})
  log.debug('[llm][client_translator][openai_chat] action=parse_request')
  body = symbolize(body)

  messages, system = extract_messages_and_system(body[:messages] || [])
  tools = build_tools(body[:tools])
  params = extract_params(body)
  tool_choice = extract_tool_choice(body[:tool_choice])
  external = external_refs(body, env)

  Canonical::Request.build(
    id:              body[:request_id] || env['HTTP_X_CLIENT_REQUEST_ID'] || SecureRandom.uuid,
    messages:        messages,
    system:          system,
    tools:           tools,
    tool_choice:     tool_choice,
    params:          params,
    stream:          body[:stream] == true,
    conversation_id: env['HTTP_X_LEGION_CONVERSATION_ID'] || body[:conversation_id],
    routing:         legion_routing_from_env(env),
    metadata:        {
      client_model:            body[:model],
      tier:                    env['HTTP_X_LEGION_TIER'] || body[:tier],
      routing_explicit:        legion_routing_explicit_from_env(env),
      cwd:                     env['HTTP_X_LEGION_CWD'] || body[:cwd],
      requested_tools:         body[:requested_tools] || [],
      client_tool_passthrough: extract_client_tool_passthrough(body, env),
      caller_context:          body[:caller],
      include_reasoning:       body[:include_reasoning] != false && body[:include_thinking] != false,
      external_refs:           external
    }.compact
  )
end