Module: Legion::LLM::Inference
- Extended by:
- Legion::Logging::Helper
- Defined in:
- lib/legion/llm/inference.rb,
lib/legion/llm/inference/steps.rb,
lib/legion/llm/inference/prompt.rb,
lib/legion/llm/inference/profile.rb,
lib/legion/llm/inference/request.rb,
lib/legion/llm/inference/tracing.rb,
lib/legion/llm/inference/executor.rb,
lib/legion/llm/inference/response.rb,
lib/legion/llm/inference/timeline.rb,
lib/legion/llm/inference/steps/rbac.rb,
lib/legion/llm/inference/gaia_caller.rb,
lib/legion/llm/inference/conversation.rb,
lib/legion/llm/inference/steps/debate.rb,
lib/legion/llm/inference/steps/billing.rb,
lib/legion/llm/inference/steps/logging.rb,
lib/legion/llm/inference/route_attempts.rb,
lib/legion/llm/inference/steps/metering.rb,
lib/legion/llm/inference/audit_publisher.rb,
lib/legion/llm/inference/steps/rag_guard.rb,
lib/legion/llm/inference/tool_dispatcher.rb,
lib/legion/llm/inference/steps/tool_calls.rb,
lib/legion/llm/inference/steps/rag_context.rb,
lib/legion/llm/inference/steps/prompt_cache.rb,
lib/legion/llm/inference/steps/token_budget.rb,
lib/legion/llm/inference/steps/tool_history.rb,
lib/legion/llm/inference/enrichment_injector.rb,
lib/legion/llm/inference/steps/gaia_advisory.rb,
lib/legion/llm/inference/steps/mcp_discovery.rb,
lib/legion/llm/inference/steps/post_response.rb,
lib/legion/llm/inference/steps/tier_assigner.rb,
lib/legion/llm/inference/steps/trigger_match.rb,
lib/legion/llm/inference/steps/classification.rb,
lib/legion/llm/inference/steps/skill_injector.rb,
lib/legion/llm/inference/steps/span_annotator.rb,
lib/legion/llm/inference/steps/sticky_helpers.rb,
lib/legion/llm/inference/steps/sticky_persist.rb,
lib/legion/llm/inference/steps/sticky_runners.rb,
lib/legion/llm/inference/steps/tool_discovery.rb,
lib/legion/llm/inference/steps/knowledge_capture.rb,
lib/legion/llm/inference/steps/confidence_scoring.rb
Defined Under Namespace
Modules: AuditPublisher, Conversation, EnrichmentInjector, GaiaCaller, Profile, Prompt, RouteAttempts, Steps, Tracing Classes: Executor, Request, Response, Timeline
Constant Summary collapse
- FRAMEWORK_KEYS =
%i[request_id source timestamp datetime task_id parent_id master_id check_subtask generate_task catch_exceptions worker_id principal_id principal_type caller].freeze
- ToolDispatcher =
Tools::Dispatcher
Class Method Summary collapse
- .apply_response_guards(result, kwargs) ⇒ Object
- .ask(message:, model: nil, provider: nil, intent: nil, tier: nil, context: {}, identity: nil) ⇒ Object
- .ask_direct(message:, model: nil, provider: nil, intent: nil, tier: nil) ⇒ Object
- .assert_external_allowed! ⇒ Object (also: assert_cloud_allowed!)
- .attach_escalation_history(response, history, resolution, chain) ⇒ Object
- .blocked_hook_response(blocked) ⇒ Object
- .build_attempt(resolution, outcome, failures, duration_ms) ⇒ Object
- .build_cache_key(model, provider, message, temperature) ⇒ Object
- .cacheable?(cache_opt, temperature, message) ⇒ Boolean
- .caller_descriptor(caller_context) ⇒ Object
-
.chat(model: nil, provider: nil, intent: nil, tier: nil, escalate: nil, max_escalations: nil, quality_check: nil, message: nil, **kwargs) ⇒ Object
Public inference entry points — these are the methods delegated from Legion::LLM.
- .chat_direct(model: nil, provider: nil, intent: nil, tier: nil, escalate: nil, max_escalations: nil, quality_check: nil, message: nil, **kwargs) ⇒ Object
- .chat_single(model:, provider:, intent:, tier:, message: nil, **kwargs) ⇒ Object
- .chat_single_native(model:, provider:, message:, instance: nil, caller: nil, &block) ⇒ Object
- .chat_via_pipeline(&block) ⇒ Object
- .chat_with_escalation(model:, provider:, intent:, tier:, max_escalations:, quality_check:, message:, **kwargs) ⇒ Object
-
.daemon_ask(message:, model: nil, provider: nil, context: {}, tier: nil, identity: nil) ⇒ Object
rubocop:disable Lint/UnusedMethodArgument.
- .direct_chat_session?(result) ⇒ Boolean
- .dispatch_chat(model:, provider:, intent:, tier:, escalate:, max_escalations:, quality_check:, message:, **kwargs) ⇒ Object
- .effective_tier_is_external?(tier, provider) ⇒ Boolean (also: effective_tier_is_cloud?)
- .elapsed_ms_since(started_at) ⇒ Object
- .emit_non_pipeline_metering(response, model:, provider:, caller: nil) ⇒ Object
- .emit_privacy_blocked_audit ⇒ Object
- .enterprise_privacy? ⇒ Boolean
- .escalation_attempt_passed?(response, result, resolution, duration_ms, history, chain, caller: nil) ⇒ Boolean
- .escalation_attempt_response(resolution, message, kwargs) ⇒ Object
- .escalation_enabled? ⇒ Boolean
- .escalation_quality_threshold ⇒ Object
- .external_tier?(tier) ⇒ Boolean
- .hash_response_details(result, requested_model:, requested_provider:) ⇒ Object
- .inference_input_payload(message:, messages:) ⇒ Object
- .inference_response_details(result, requested_model:, requested_provider:) ⇒ Object
- .inference_text_length(payload) ⇒ Object
- .inference_token_value(tokens, key) ⇒ Object
- .llm_setting(key, default = nil) ⇒ Object
- .log_inference_error(request_type:, requested_model:, requested_provider:, error:, duration_ms:) ⇒ Object
- .log_inference_request(request_type:, requested_model:, requested_provider:, intent:, tier:, message:, kwargs:) ⇒ Object
- .log_inference_response(request_type:, requested_model:, requested_provider:, result:, duration_ms:) ⇒ Object
- .maybe_shadow_evaluate(response, messages, primary_model) ⇒ Object
- .native_provider_error(operation) ⇒ Object
- .normalize_ask_direct_hash(result, fallback_model:) ⇒ Object
- .object_response_details(result, requested_model:, requested_provider:) ⇒ Object
- .pipeline_enabled? ⇒ Boolean
- .pipeline_response_details(result, requested_model:, requested_provider:) ⇒ Object
- .publish_escalation_event(history, final_outcome, caller: nil) ⇒ Object
- .record_escalation_error(error, resolution, duration_ms, history) ⇒ Object
- .report_health(signal, resolution, duration_ms, failures: nil) ⇒ Object
- .resolve_ask_direct_response(result, message, requested_model) ⇒ Object
- .response_guards_enabled? ⇒ Boolean
- .run_escalation_attempt(resolution, message:, kwargs:, threshold:, quality_check:, history:, chain:) ⇒ Object
- .safe_inference_value(object, method_name) ⇒ Object
- .settings_value(*keys, default: nil) ⇒ Object
- .try_defer(intent:, urgency:, model:, provider:, message:) ⇒ Object
Class Method Details
.apply_response_guards(result, kwargs) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 716 def apply_response_guards(result, kwargs) context = kwargs[:context] response_text = result[:response] || result[:content] guard_result = Hooks::ResponseGuard.guard_response( response: response_text, context: context ) log.warn "[llm][inference] response_guard passed=#{guard_result[:passed]}" unless guard_result[:passed] result.merge(_guard_result: guard_result) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.apply_response_guards') result end |
.ask(message:, model: nil, provider: nil, intent: nil, tier: nil, context: {}, identity: nil) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 89 def ask(message:, model: nil, provider: nil, intent: nil, tier: nil, context: {}, identity: nil, &) started_at = ::Process.clock_gettime(::Process::CLOCK_MONOTONIC) log_inference_request( request_type: :ask, requested_model: model, requested_provider: provider, intent: intent, tier: tier, message: , kwargs: { context: context, identity: identity } ) if Call::DaemonClient.available? result = daemon_ask(message: , model: model, provider: provider, context: context, tier: tier, identity: identity) if result log_inference_response( request_type: :ask, requested_model: model, requested_provider: provider, result: result, duration_ms: elapsed_ms_since(started_at) ) return result end end result = ask_direct(message: , model: model, provider: provider, intent: intent, tier: tier, &) log_inference_response( request_type: :ask, requested_model: model, requested_provider: provider, result: result, duration_ms: elapsed_ms_since(started_at) ) result rescue StandardError => e log_inference_error( request_type: :ask, requested_model: model, requested_provider: provider, error: e, duration_ms: elapsed_ms_since(started_at) ) raise end |
.ask_direct(message:, model: nil, provider: nil, intent: nil, tier: nil) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 432 def ask_direct(message:, model: nil, provider: nil, intent: nil, tier: nil, &) assert_external_allowed! if effective_tier_is_external?(tier, provider) result = chat_direct( model: model, provider: provider, intent: intent, tier: tier, message: , & ) return result if result.is_a?(Hash) && result[:deferred] return normalize_ask_direct_hash(result, fallback_model: model || llm_setting(:default_model)) if result.is_a?(Hash) response, resolved_model = resolve_ask_direct_response(result, , model, &) { status: :done, response: response.content, meta: { tier: :direct, model: resolved_model, tokens_in: response.respond_to?(:input_tokens) ? response.input_tokens : nil, tokens_out: response.respond_to?(:output_tokens) ? response.output_tokens : nil } } end |
.assert_external_allowed! ⇒ Object Also known as: assert_cloud_allowed!
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# File 'lib/legion/llm/inference.rb', line 790 def assert_external_allowed! return unless enterprise_privacy? emit_privacy_blocked_audit raise Legion::LLM::PrivacyModeError, 'External LLM tiers are disabled: enterprise_data_privacy is enabled. ' \ 'Only local and fleet tiers are permitted.' end |
.attach_escalation_history(response, history, resolution, chain) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 668 def attach_escalation_history(response, history, resolution, chain) return unless response.respond_to?(:extend) response.extend(EscalationHistory) history.each { |h| response.record_escalation_attempt(**h) } response.final_resolution = resolution response.escalation_chain = chain end |
.blocked_hook_response(blocked) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 711 def blocked_hook_response(blocked) reason = blocked[:reason] || blocked['reason'] || blocked[:message] || blocked['message'] || 'request blocked by hook' { error: 'request_blocked', message: reason.to_s } end |
.build_attempt(resolution, outcome, failures, duration_ms) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 660 def build_attempt(resolution, outcome, failures, duration_ms) attempt = { model: resolution.model, provider: resolution.provider, tier: resolution.tier, outcome: outcome, failures: failures, duration_ms: duration_ms } attempt[:offering_id] = resolution.offering_id if resolution.offering_id attempt[:offering_metadata] = resolution. unless resolution..empty? attempt end |
.build_cache_key(model, provider, message, temperature) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 735 def build_cache_key(model, provider, , temperature) = .is_a?(Array) ? : [{ role: 'user', content: .to_s }] Cache.key( model: model || llm_setting(:default_model), provider: provider || llm_setting(:default_provider), messages: , temperature: temperature ) end |
.cacheable?(cache_opt, temperature, message) ⇒ Boolean
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# File 'lib/legion/llm/inference.rb', line 731 def cacheable?(cache_opt, temperature, ) cache_opt != false && temperature.to_f.zero? && && Cache.enabled? end |
.caller_descriptor(caller_context) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 342 def caller_descriptor(caller_context) return caller_context unless caller_context.is_a?(Hash) source = caller_context[:source] || caller_context['source'] path = caller_context[:path] || caller_context['path'] return "#{source}:#{path}" if source && path return source.to_s if source caller_context.inspect end |
.chat(model: nil, provider: nil, intent: nil, tier: nil, escalate: nil, max_escalations: nil, quality_check: nil, message: nil, **kwargs) ⇒ Object
Public inference entry points — these are the methods delegated from Legion::LLM
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# File 'lib/legion/llm/inference.rb', line 42 def chat(model: nil, provider: nil, intent: nil, tier: nil, escalate: nil, max_escalations: nil, quality_check: nil, message: nil, **kwargs, &) started_at = ::Process.clock_gettime(::Process::CLOCK_MONOTONIC) log_inference_request( request_type: :chat, requested_model: model, requested_provider: provider, intent: intent, tier: tier, message: , kwargs: kwargs ) result = if defined?(Legion::Telemetry::OpenInference) Legion::Telemetry::OpenInference.llm_span( model: (model || llm_setting(:default_model)).to_s, provider: provider&.to_s, input: ) do |_span| dispatch_chat(model: model, provider: provider, intent: intent, tier: tier, escalate: escalate, max_escalations: max_escalations, quality_check: quality_check, message: , **kwargs, &) end else dispatch_chat(model: model, provider: provider, intent: intent, tier: tier, escalate: escalate, max_escalations: max_escalations, quality_check: quality_check, message: , **kwargs, &) end log_inference_response( request_type: :chat, requested_model: model, requested_provider: provider, result: result, duration_ms: elapsed_ms_since(started_at) ) result rescue StandardError => e log_inference_error( request_type: :chat, requested_model: model, requested_provider: provider, error: e, duration_ms: elapsed_ms_since(started_at) ) raise end |
.chat_direct(model: nil, provider: nil, intent: nil, tier: nil, escalate: nil, max_escalations: nil, quality_check: nil, message: nil, **kwargs) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 138 def chat_direct(model: nil, provider: nil, intent: nil, tier: nil, escalate: nil, max_escalations: nil, quality_check: nil, message: nil, **kwargs, &) log.debug( "[llm][inference] chat_direct.enter model=#{model} provider=#{provider} intent=#{intent} " \ "tier=#{tier} escalate=#{escalate} message_present=#{!.nil?} kwargs=#{kwargs.keys.sort}" ) cache_opt = kwargs.delete(:cache) { true } temperature = kwargs.delete(:temperature) escalate = escalation_enabled? if escalate.nil? cache_key = build_cache_key(model, provider, , temperature) if cacheable?(cache_opt, temperature, ) if cache_key cached = Cache.get(cache_key) if cached log.debug '[llm][inference] chat_direct cache=hit' cached_response = cached.dup cached_response[:meta] = (cached_response[:meta] || {}).merge(cached: true) return cached_response end end urgency = kwargs.delete(:urgency) { :normal } deferred = try_defer(intent: intent, urgency: urgency, model: model, provider: provider, message: , **kwargs) return deferred if deferred log.debug( "[llm][inference] chat_direct.dispatch model=#{model} provider=#{provider} " \ "escalate=#{escalate} message_present=#{!.nil?}" ) result = if escalate && chat_with_escalation( model: model, provider: provider, intent: intent, tier: tier, max_escalations: max_escalations, quality_check: quality_check, message: , temperature: temperature, **kwargs ) else chat_single(model: model, provider: provider, intent: intent, tier: tier, temperature: temperature, message: , **kwargs, &) end log.debug("[llm][inference] chat_direct.exit result_class=#{result.class} result_nil=#{result.nil?}") if cache_key && result.is_a?(Hash) ttl = settings_value(:prompt_caching, :response_cache, :ttl_seconds) || Cache::DEFAULT_TTL Cache.set(cache_key, result, ttl: ttl) end result end |
.chat_single(model:, provider:, intent:, tier:, message: nil, **kwargs) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 491 def chat_single(model:, provider:, intent:, tier:, message: nil, **kwargs, &) explicit_tools = kwargs.delete(:tools) tools = explicit_tools tools = nil if tools.respond_to?(:empty?) && tools.empty? if (intent || tier) && Router.routing_enabled? resolution = Router.resolve(intent: intent, tier: tier, model: model, provider: provider) if resolution model = resolution.model provider = resolution.provider assert_external_allowed! if resolution.external? end elsif tier assert_external_allowed! if external_tier?(tier.to_sym) end model ||= llm_setting(:default_model) instance = resolution&.instance || kwargs[:instance] || kwargs[:instance_id] || kwargs[:provider_instance] provider ||= (model && Router.infer_provider_for_model(model)) || llm_setting(:default_provider) opts = {} opts[:model] = model if model opts[:provider] = provider if provider opts.merge!(kwargs.except(*FRAMEWORK_KEYS)) opts.delete(:temperature) if opts[:temperature].nil? Call::Providers.inject_anthropic_cache_control!(opts, provider) opts[:tools] = tools if tools log.debug "[llm][inference] chat_single model=#{opts[:model]} provider=#{opts[:provider]} message_present=#{!.nil?} tools=#{tools&.size || 0}" chat_single_native(model: opts[:model], provider: opts[:provider], instance: instance, message: , caller: kwargs[:caller], **opts.except(:model, :provider), &) end |
.chat_single_native(model:, provider:, message:, instance: nil, caller: nil, &block) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 526 def chat_single_native(model:, provider:, message:, instance: nil, caller: nil, **, &block) raise native_provider_error('session-style chat requires message or messages') unless raise native_provider_error('chat without a native provider') unless provider = .is_a?(Array) ? : [{ role: 'user', content: .to_s }] result = if block Call::Dispatch.call(provider: provider, instance: instance, capability: :stream, model: model, messages: , **, &block) else Call::Dispatch.call(provider: provider, instance: instance, capability: :chat, model: model, messages: , **) end response = Call::NativeResponseAdapter.new(result) emit_non_pipeline_metering(response, model: model, provider: provider, caller: caller) response end |
.chat_via_pipeline(&block) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 408 def chat_via_pipeline(**, &block) request = Request.from_chat_args(**) executor = Executor.new(request) block ? executor.call_stream(&block) : executor.call end |
.chat_with_escalation(model:, provider:, intent:, tier:, max_escalations:, quality_check:, message:, **kwargs) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 573 def chat_with_escalation(model:, provider:, intent:, tier:, max_escalations:, quality_check:, message:, **kwargs) log.debug "[llm][inference] chat_with_escalation.enter model=#{model} provider=#{provider} max_escalations=#{max_escalations}" chain = Router.resolve_chain( intent: intent, tier: tier, model: model, provider: provider, max_escalations: max_escalations ) threshold = escalation_quality_threshold history = [] last_error = nil chain.each do |resolution| response, error = run_escalation_attempt( resolution, message: , kwargs: kwargs, threshold: threshold, quality_check: quality_check, history: history, chain: chain ) last_error = error if error return response if response end publish_escalation_event(history, :exhausted, caller: kwargs[:caller]) if history.size > 1 = "All #{history.size} escalation attempts failed" if last_error providers = history.filter_map { |attempt| attempt[:provider] }.uniq.join(', ') = "#{}; no usable native provider handled the request. " \ "providers=#{providers} last_error=#{last_error.class}: #{last_error.}" end raise Legion::LLM::EscalationExhausted, end |
.daemon_ask(message:, model: nil, provider: nil, context: {}, tier: nil, identity: nil) ⇒ Object
rubocop:disable Lint/UnusedMethodArgument
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# File 'lib/legion/llm/inference.rb', line 414 def daemon_ask(message:, model: nil, provider: nil, context: {}, tier: nil, identity: nil) # rubocop:disable Lint/UnusedMethodArgument result = Call::DaemonClient.chat( message: , model: model, provider: provider, context: context, tier_preference: tier || :auto ) case result[:status] when :immediate, :created result[:body] when :accepted Cache::Response.poll(result[:request_id]) when :denied raise Legion::LLM::DaemonDeniedError, result.dig(:error, :message) || 'Access denied' when :rate_limited raise Legion::LLM::DaemonRateLimitedError, "Rate limited. Retry after #{result[:retry_after]}s" end end |
.direct_chat_session?(result) ⇒ Boolean
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# File 'lib/legion/llm/inference.rb', line 459 def direct_chat_session?(result) result.respond_to?(:ask) && result.respond_to?(:model) && !result.respond_to?(:content) end |
.dispatch_chat(model:, provider:, intent:, tier:, escalate:, max_escalations:, quality_check:, message:, **kwargs) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 353 def dispatch_chat(model:, provider:, intent:, tier:, escalate:, max_escalations:, quality_check:, message:, **kwargs, &) log.debug( "[llm][inference] dispatch_chat.enter model=#{model} provider=#{provider} intent=#{intent} " \ "tier=#{tier} escalate=#{escalate} max_escalations=#{max_escalations} " \ "quality_check=#{quality_check} message_present=#{!.nil?} kwargs=#{kwargs.keys.sort}" ) if pipeline_enabled? && ( || kwargs[:messages]) && !block_given? return Prompt.dispatch( || kwargs[:messages], intent: intent, tier: tier, provider: provider, model: model, escalate: escalate, max_escalations: max_escalations, quality_check: quality_check, **kwargs.except(:messages) ) end if pipeline_enabled? && ( || kwargs[:messages]) && block_given? return chat_via_pipeline(model: model, provider: provider, intent: intent, tier: tier, message: , escalate: escalate, max_escalations: max_escalations, quality_check: quality_check, **kwargs, &) end if block_given? && return chat_single(model: model, provider: provider, intent: intent, tier: tier, message: , **kwargs, &) end = .is_a?(Array) ? : [{ role: 'user', content: .to_s }] resolved_model = model || llm_setting(:default_model) if defined?(Legion::LLM::Hooks) blocked = Legion::LLM::Hooks.run_before(messages: , model: resolved_model) return blocked[:response] || blocked_hook_response(blocked) if blocked end result = chat_direct(model: model, provider: provider, intent: intent, tier: tier, escalate: escalate, max_escalations: max_escalations, quality_check: quality_check, message: , **kwargs) if defined?(Legion::LLM::Hooks) blocked = Legion::LLM::Hooks.run_after(response: result, messages: , model: resolved_model) return blocked[:response] || blocked_hook_response(blocked) if blocked end result = apply_response_guards(result, kwargs) if response_guards_enabled? && result.is_a?(Hash) log.debug("[llm][inference] dispatch_chat.exit result_class=#{result.class} result_nil=#{result.nil?}") result end |
.effective_tier_is_external?(tier, provider) ⇒ Boolean Also known as: effective_tier_is_cloud?
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# File 'lib/legion/llm/inference.rb', line 801 def effective_tier_is_external?(tier, provider) return external_tier?(tier.to_sym) if tier return false unless enterprise_privacy? resolved = provider || llm_setting(:default_provider) external_providers = %i[anthropic bedrock openai gemini azure] external_providers.include?(resolved&.to_sym) end |
.elapsed_ms_since(started_at) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 248 def elapsed_ms_since(started_at) ((::Process.clock_gettime(::Process::CLOCK_MONOTONIC) - started_at) * 1000).round end |
.emit_non_pipeline_metering(response, model:, provider:, caller: nil) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 761 def emit_non_pipeline_metering(response, model:, provider:, caller: nil) return unless response input = response.respond_to?(:input_tokens) ? response.input_tokens.to_i : 0 output = response.respond_to?(:output_tokens) ? response.output_tokens.to_i : 0 Legion::LLM::Metering.emit( provider: provider, model_id: model, request_type: 'chat', tier: 'direct', input_tokens: input, output_tokens: output, total_tokens: input + output, caller: caller ) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.non_pipeline_metering') end |
.emit_privacy_blocked_audit ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 779 def emit_privacy_blocked_audit Legion::LLM::Audit.emit_prompt( request_id: nil, conversation_id: nil, caller: Legion::LLM::PublisherIdentity.caller_hash, routing: {}, tokens: {}, status: 'privacy_blocked', error: { class: 'PrivacyModeError', message: 'External tiers blocked by enterprise privacy' }, timestamp: Time.now, request_type: 'chat' ) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.emit_privacy_blocked_audit') end |
.enterprise_privacy? ⇒ Boolean
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# File 'lib/legion/llm/inference.rb', line 775 def enterprise_privacy? Legion::LLM::Settings.enterprise_privacy? end |
.escalation_attempt_passed?(response, result, resolution, duration_ms, history, chain, caller: nil) ⇒ Boolean
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# File 'lib/legion/llm/inference.rb', line 635 def escalation_attempt_passed?(response, result, resolution, duration_ms, history, chain, caller: nil) return false unless result.passed report_health(:success, resolution, duration_ms) history << build_attempt(resolution, :success, [], duration_ms) attach_escalation_history(response, history, resolution, chain) publish_escalation_event(history, :success, caller: caller) if history.size > 1 log.debug "[llm][inference] chat_with_escalation success attempts=#{history.size}" true end |
.escalation_attempt_response(resolution, message, kwargs) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 627 def escalation_attempt_response(resolution, , kwargs) opts = { model: resolution.model, provider: resolution.provider } opts.merge!(kwargs.except(*FRAMEWORK_KEYS)) chat_single_native(model: opts[:model], provider: opts[:provider], message: , caller: kwargs[:caller], **opts.except(:model, :provider)) end |
.escalation_enabled? ⇒ Boolean
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# File 'lib/legion/llm/inference.rb', line 745 def escalation_enabled? routing = llm_setting(:routing) return false unless routing.is_a?(Hash) esc = Legion::LLM::Settings.config_value(routing, :escalation, {}) Legion::LLM::Settings.config_value(esc, :enabled) == true end |
.escalation_quality_threshold ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 753 def escalation_quality_threshold routing = llm_setting(:routing) return 50 unless routing.is_a?(Hash) esc = Legion::LLM::Settings.config_value(routing, :escalation, {}) Legion::LLM::Settings.config_value(esc, :quality_threshold, 50) end |
.external_tier?(tier) ⇒ Boolean
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# File 'lib/legion/llm/inference.rb', line 812 def external_tier?(tier) %i[cloud frontier openai_compat].include?(tier) end |
.hash_response_details(result, requested_model:, requested_provider:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 297 def hash_response_details(result, requested_model:, requested_provider:) = result[:meta] || result['meta'] || {} { output: result[:response] || result['response'] || result[:content] || result['content'] || result.dig(:message, :content) || result.to_s, provider: result[:provider] || result['provider'] || [:provider] || ['provider'] || requested_provider, model: result[:model] || result['model'] || [:model] || ['model'] || requested_model, input_tokens: result[:input_tokens] || result['input_tokens'] || [:tokens_in] || ['tokens_in'], output_tokens: result[:output_tokens] || result['output_tokens'] || [:tokens_out] || ['tokens_out'], stop_reason: result[:stop_reason] || result['stop_reason'] || result.dig(:stop, :reason) || result.dig('stop', 'reason'), tool_calls: Array(result[:tool_calls] || result['tool_calls'] || result[:tools] || result['tools']).size } end |
.inference_input_payload(message:, messages:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 252 def inference_input_payload(message:, messages:) return unless .nil? end |
.inference_response_details(result, requested_model:, requested_provider:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 274 def inference_response_details(result, requested_model:, requested_provider:) if result.is_a?(Legion::LLM::Inference::Response) return pipeline_response_details(result, requested_model: requested_model, requested_provider: requested_provider) end return hash_response_details(result, requested_model: requested_model, requested_provider: requested_provider) if result.is_a?(Hash) object_response_details(result, requested_model: requested_model, requested_provider: requested_provider) end |
.inference_text_length(payload) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 258 def inference_text_length(payload) case payload when Array payload.sum { |item| inference_text_length(item) } when Hash return payload[:content].to_s.length if payload.key?(:content) return payload['content'].to_s.length if payload.key?('content') payload.values.sum { |item| inference_text_length(item) } when nil 0 else payload.to_s.length end end |
.inference_token_value(tokens, key) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 332 def inference_token_value(tokens, key) return nil if tokens.nil? return tokens[key] || tokens[key.to_s] if tokens.is_a?(Hash) method_name = { input: :input_tokens, output: :output_tokens, total: :total_tokens }[key] return tokens.public_send(method_name) if method_name && tokens.respond_to?(method_name) nil end |
.llm_setting(key, default = nil) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 29 def llm_setting(key, default = nil) Legion::LLM::Settings.config_value(Legion::LLM::Settings.current_settings, key, default) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.settings') default end |
.log_inference_error(request_type:, requested_model:, requested_provider:, error:, duration_ms:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 232 def log_inference_error(request_type:, requested_model:, requested_provider:, error:, duration_ms:) parts = [ '[llm][inference] response', "type=#{request_type}", 'status=error', "duration_ms=#{duration_ms}", "error_class=#{error.class}", "error=#{error..inspect}" ] parts << "requested_provider=#{requested_provider}" if requested_provider parts << "requested_model=#{requested_model}" if requested_model log.error(parts.join(' ')) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.log_error') end |
.log_inference_request(request_type:, requested_model:, requested_provider:, intent:, tier:, message:, kwargs:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 188 def log_inference_request(request_type:, requested_model:, requested_provider:, intent:, tier:, message:, kwargs:) input = inference_input_payload(message: , messages: kwargs[:messages]) parts = [ '[llm][inference] request', "type=#{request_type}", "input_length=#{inference_text_length(input)}", "input=#{input.inspect}" ] parts << "requested_provider=#{requested_provider}" if requested_provider parts << "requested_model=#{requested_model}" if requested_model parts << "intent=#{intent}" if intent parts << "tier=#{tier}" if tier parts << "caller=#{caller_descriptor(kwargs[:caller])}" if kwargs[:caller] parts << "conversation_id=#{kwargs[:conversation_id]}" if kwargs[:conversation_id] parts << "request_id=#{kwargs[:request_id]}" if kwargs[:request_id] parts << "tools=#{Array(kwargs[:tools]).size}" if kwargs.key?(:tools) parts << 'stream=true' if kwargs[:stream] log.info(parts.join(' ')) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.log_request') end |
.log_inference_response(request_type:, requested_model:, requested_provider:, result:, duration_ms:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 210 def log_inference_response(request_type:, requested_model:, requested_provider:, result:, duration_ms:) details = inference_response_details(result, requested_model: requested_model, requested_provider: requested_provider) parts = [ '[llm][inference] response', "type=#{request_type}", 'status=ok', "duration_ms=#{duration_ms}", "result_class=#{result.class}", "output_length=#{inference_text_length(details[:output])}", "output=#{details[:output].inspect}" ] parts << "provider=#{details[:provider]}" if details[:provider] parts << "model=#{details[:model]}" if details[:model] parts << "input_tokens=#{details[:input_tokens]}" unless details[:input_tokens].nil? parts << "output_tokens=#{details[:output_tokens]}" unless details[:output_tokens].nil? parts << "stop_reason=#{details[:stop_reason]}" if details[:stop_reason] parts << "tool_calls=#{details[:tool_calls]}" unless details[:tool_calls].nil? log.info(parts.join(' ')) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.log_response') end |
.maybe_shadow_evaluate(response, messages, primary_model) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 558 def maybe_shadow_evaluate(response, , primary_model) return unless Quality::ShadowEval.enabled? && Quality::ShadowEval.should_sample? log.debug "[llm][inference] shadow_evaluate primary_model=#{primary_model}" Thread.new do Quality::ShadowEval.evaluate( primary_response: { content: response.respond_to?(:content) ? response.content : response.to_s, model: primary_model, usage: {} }, messages: ) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.shadow_eval') end end |
.native_provider_error(operation) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 543 def native_provider_error(operation) Legion::LLM::ProviderError.new( "Native provider dispatch is required for #{operation}. Configure a registered lex-llm provider." ) end |
.normalize_ask_direct_hash(result, fallback_model:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 477 def normalize_ask_direct_hash(result, fallback_model:) = result[:meta].is_a?(Hash) ? result[:meta] : {} { status: result[:status] || :done, response: result[:response] || result[:content], meta: { tier: [:tier] || :direct, model: ([:model] || fallback_model).to_s, tokens_in: [:tokens_in], tokens_out: [:tokens_out] } } end |
.object_response_details(result, requested_model:, requested_provider:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 310 def object_response_details(result, requested_model:, requested_provider:) tool_calls = safe_inference_value(result, :tool_calls) { output: safe_inference_value(result, :content) || result.to_s, provider: requested_provider, model: safe_inference_value(result, :model_id)&.to_s || requested_model, input_tokens: safe_inference_value(result, :input_tokens), output_tokens: safe_inference_value(result, :output_tokens), stop_reason: safe_inference_value(result, :stop_reason), tool_calls: tool_calls.nil? ? nil : Array(tool_calls).size } end |
.pipeline_enabled? ⇒ Boolean
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# File 'lib/legion/llm/inference.rb', line 401 def pipeline_enabled? llm_setting(:pipeline_enabled) == true rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.pipeline_enabled') false end |
.pipeline_response_details(result, requested_model:, requested_provider:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 283 def pipeline_response_details(result, requested_model:, requested_provider:) = result. tokens = result.tokens { output: .is_a?(Hash) ? ([:content] || ['content']) : .to_s, provider: result.routing[:provider] || result.routing['provider'] || requested_provider, model: result.routing[:model] || result.routing['model'] || requested_model, input_tokens: inference_token_value(tokens, :input), output_tokens: inference_token_value(tokens, :output), stop_reason: result.stop[:reason] || result.stop['reason'], tool_calls: Array(result.tools).size } end |
.publish_escalation_event(history, final_outcome, caller: nil) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 688 def publish_escalation_event(history, final_outcome, caller: nil) payload = { outcome: final_outcome, attempts: history.size, history: history, caller: caller || Legion::LLM::PublisherIdentity.caller_hash, timestamp: Time.now.utc.iso8601 } Legion::Events.emit('llm.escalation', **payload) if defined?(Legion::Events) && Legion::Events.respond_to?(:emit) log.info "[llm][inference] escalation_event outcome=#{final_outcome} attempts=#{history.size}" Transport::Messages::EscalationEvent.new(payload).publish if Legion::LLM::Settings.transport_connected? rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.publish_escalation_event', outcome: final_outcome) nil end |
.record_escalation_error(error, resolution, duration_ms, history) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 646 def record_escalation_error(error, resolution, duration_ms, history) handle_exception( error, level: :warn, handled: true, operation: 'llm.inference.escalation_attempt', model: resolution&.model, provider: resolution&.provider, tier: resolution&.tier ) report_health(:error, resolution, duration_ms) if resolution history << build_attempt(resolution, :error, [error.class.name], duration_ms) if resolution end |
.report_health(signal, resolution, duration_ms, failures: nil) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 677 def report_health(signal, resolution, duration_ms, failures: nil) return unless Router.routing_enabled? = { duration_ms: duration_ms } [:failures] = failures if failures Router.health_tracker.report(provider: resolution.provider, offering_id: resolution.offering_id, signal: signal, value: 1, metadata: ) Router.health_tracker.report(provider: resolution.provider, offering_id: resolution.offering_id, signal: :latency, value: duration_ms, metadata: {}) end |
.resolve_ask_direct_response(result, message, requested_model) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 463 def resolve_ask_direct_response(result, , requested_model, &) if direct_chat_session?(result) response = block_given? ? result.ask(, &) : result.ask() return [response, result.model.to_s] end resolved_model = if result.respond_to?(:model_id) && result.model_id result.model_id.to_s else (requested_model || llm_setting(:default_model)).to_s end [result, resolved_model] end |
.response_guards_enabled? ⇒ Boolean
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# File 'lib/legion/llm/inference.rb', line 707 def response_guards_enabled? settings_value(:response_guards, :enabled) == true end |
.run_escalation_attempt(resolution, message:, kwargs:, threshold:, quality_check:, history:, chain:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 604 def run_escalation_attempt(resolution, message:, kwargs:, threshold:, quality_check:, history:, chain:) start_time = Time.now assert_external_allowed! if resolution.respond_to?(:external?) && resolution.external? response = escalation_attempt_response(resolution, , kwargs) duration_ms = ((Time.now - start_time) * 1000).round result = Quality::Checker.check(response, quality_threshold: threshold, quality_check: quality_check) return [response, nil] if escalation_attempt_passed?(response, result, resolution, duration_ms, history, chain, caller: kwargs[:caller]) report_health(:quality_failure, resolution, duration_ms, failures: result.failures) history << build_attempt(resolution, :quality_failure, result.failures, duration_ms) log.debug "[llm][inference] chat_with_escalation quality_failure attempt=#{history.size} failures=#{result.failures}" [nil, nil] rescue Legion::LLM::PrivacyModeError raise rescue StandardError => e duration_ms = ((Time.now - start_time) * 1000).round record_escalation_error(e, resolution, duration_ms, history) [nil, e] end |
.safe_inference_value(object, method_name) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 323 def safe_inference_value(object, method_name) return nil unless object.methods.include?(method_name) || object.private_methods.include?(method_name) object.public_send(method_name) rescue StandardError => e handle_exception(e, level: :warn, operation: 'llm.inference.safe_value', method_name: method_name) nil end |
.settings_value(*keys, default: nil) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 36 def settings_value(*keys, default: nil) Legion::LLM::Settings.value(*keys, default: default) end |
.try_defer(intent:, urgency:, model:, provider:, message:) ⇒ Object
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# File 'lib/legion/llm/inference.rb', line 549 def try_defer(intent:, urgency:, model:, provider:, message:, **) return nil unless Scheduling.enabled? && Scheduling.should_defer?(intent: intent || :normal, urgency: urgency) return nil unless Legion::LLM::Scheduling::Batch.enabled? log.debug "[llm][inference] try_defer deferring intent=#{intent} urgency=#{urgency}" entry_id = Legion::LLM::Scheduling::Batch.enqueue(model: model, provider: provider, message: , priority: urgency, **) { deferred: true, batch_id: entry_id, next_off_peak: Scheduling.next_off_peak.iso8601 } end |