from src.services.ai_agent_autonomous_runtime_control import ( _RUNTIME_ALERT_OPERATION_COUNTS_SQL, _RUNTIME_ALERTMANAGER_EVENT_COUNTS_SQL, _RUNTIME_GROUPED_ALERT_EVENT_COUNTS_SQL, _RUNTIME_PLAYBOOK_TRUST_COUNTS_FALLBACK_SQL, _RUNTIME_TIMELINE_COUNTS_SQL, build_ai_agent_autonomous_runtime_control, build_runtime_receipt_readback_from_rows, classify_deploy_control_plane_observation, ) def _assert_log_controlled_writeback_executor(payload: dict): assert payload["schema_version"] == "ai_agent_log_controlled_writeback_executor_readback_v1" assert payload["priority"] == "P1-LOG-KM-RAG-MCP-PLAYBOOK" assert payload["status"] == "controlled_writeback_executor_ready" assert payload["active_blockers"] == [] policy = payload["executor_policy"] assert policy["low_medium_high_controlled_apply_enabled"] is True assert policy["owner_review_required_for_low_medium_high"] is False assert policy["critical_break_glass_required"] is True assert policy["target_selector_required"] is True assert policy["source_of_truth_diff_required"] is True assert policy["check_mode_required"] is True assert policy["rollback_required"] is True assert policy["post_apply_verifier_required"] is True assert payload["rollups"]["source_writeback_plan_count"] == 18 assert payload["rollups"]["execution_batch_count"] == 6 assert payload["rollups"]["ready_execution_batch_count"] == 6 assert payload["rollups"]["target_selector_count"] == 18 assert payload["rollups"]["source_of_truth_diff_count"] == 18 assert payload["rollups"]["controlled_executor_dispatch_ready"] is True assert payload["rollups"]["controlled_apply_enabled_by_policy"] is True assert payload["rollups"]["current_blocker_execution_queue_count"] == 1 assert payload["rollups"]["current_blocker_control_path_blocked_count"] == 1 assert payload["rollups"]["current_blocker_local_recovery_package_count"] == 1 assert payload["rollups"]["runtime_dispatch_performed"] is False context = payload["agent_consumption_context"] assert "ai_agent_autonomous_runtime_control" in context["consumable_by"] assert "km_rag_playbook_learning_loop" in context["consumable_by"] assert len(context["next_action_queue"]) == 6 assert len(context["current_blocker_execution_queue"]) == 1 current_queue = context["current_blocker_execution_queue"][0] assert current_queue["queue_item_id"] == ( "current-p0-blocker::harbor_110_repair_no_matching_runner" ) assert current_queue["controlled_recovery_package"] == ( "recover-110-control-path-and-harbor-local.sh --check" ) assert current_queue["post_apply_verifier"] == ( "check-awoooi-110-controlled-cd-lane-readiness.sh" ) assert [phase["phase_id"] for phase in current_queue[ "controlled_local_console_execution_plan" ]] == [ "diagnose_ssh_publickey", "preflight_control_path_and_harbor", "repair_ssh_metadata_if_check_confirms_metadata_drift", "repair_harbor_once_if_v2_still_502", "verify_controlled_cd_lane", ] assert current_queue["post_recovery_readback_commands"] == [ "read-public-gitea-actions-queue.py --json", "curl -k https://registry.wooo.work/v2/", "curl http://192.168.0.110:5000/v2/", ] assert "workflow_dispatch_from_this_endpoint" in current_queue[ "forbidden_runtime_actions" ] assert current_queue["external_control_path_blocker"] == ( "publickey_offer_timeout" ) assert context["raw_payload_required"] is False boundaries = payload["operation_boundaries"] assert boundaries["executor_readback_only"] is True assert boundaries["executor_dispatch_performed"] is False assert boundaries["km_write_performed"] is False assert boundaries["rag_index_write_performed"] is False assert boundaries["playbook_trust_write_performed"] is False assert boundaries["mcp_tool_call_performed"] is False assert boundaries["agent_runtime_action_performed"] is False assert boundaries["raw_log_payload_persisted"] is False assert boundaries["secret_value_collection_allowed"] is False assert boundaries["github_api_used"] is False def _log_controlled_writeback_consumer_readback() -> dict: targets = ("km", "rag", "playbook", "mcp", "verifier", "ai_agent") bindings = [ { "consumer_binding_id": f"consumer::receipt::{target}", "dispatch_receipt_id": f"receipt::{target}", "ledger_op_id": f"op::{target}", "target": target, "target_surface": f"{target}_metadata_feedback_binding", "consumer_surface": f"{target}_consumer_context", "status": "ready_for_consumer_context", "raw_payload_included": False, "post_apply_verifier_refs": [f"verifier://{target}"], "target_write_performed": False, } for target in targets ] return { "schema_version": "ai_agent_log_controlled_writeback_consumer_readback_v1", "priority": "P1-LOG-KM-RAG-MCP-PLAYBOOK", "scope": "ai_agent_log_controlled_writeback_consumer_readback", "status": "controlled_writeback_consumer_readback_ready", "readback": { "workplan_id": "P1-LOG-CONTROLLED-WRITEBACK-CONSUMER-READBACK", "source_operation_type": "log_controlled_writeback_dispatched", "source_executor_route": "ai_agent_metadata_writeback_executor", }, "controlled_consume": { "controlled_consume_allowed": True, "runtime_target_write_performed": False, }, "consumer_bindings": bindings, "target_rollups": [ { "target": target, "consumer_surface": f"{target}_consumer_context", "binding_count": 1, "ready_binding_count": 1, "metadata_only": True, } for target in targets ], "rollups": { "target_count": 6, "dispatch_ledger_row_count": 6, "consumer_binding_count": 6, "ready_consumer_binding_count": 6, "ready_target_count": 6, "metadata_only_receipt_count": 6, "post_apply_verifier_ref_count": 6, "controlled_consumer_readback_ready": True, "km_consumer_binding_count": 1, "rag_consumer_binding_count": 1, "playbook_consumer_binding_count": 1, "mcp_consumer_binding_count": 1, "verifier_consumer_binding_count": 1, "ai_agent_consumer_binding_count": 1, "runtime_target_write_performed": False, }, "active_blockers": [], "operation_boundaries": { "consumer_readback_only": True, "metadata_ledger_read_performed": True, "km_write_performed": False, "rag_index_write_performed": False, "playbook_trust_write_performed": False, "mcp_tool_call_performed": False, "agent_runtime_action_performed": False, "telegram_send_performed": False, "workflow_trigger_performed": False, "raw_log_payload_persisted": False, "secret_value_collection_allowed": False, "github_api_used": False, }, } def _assert_log_controlled_writeback_consumer(payload: dict): assert payload["schema_version"] == ( "ai_agent_log_controlled_writeback_consumer_readback_v1" ) assert payload["status"] == "controlled_writeback_consumer_readback_ready" assert payload["active_blockers"] == [] assert payload["controlled_consume"]["controlled_consume_allowed"] is True assert payload["controlled_consume"]["runtime_target_write_performed"] is False assert payload["rollups"]["consumer_binding_count"] == 6 assert payload["rollups"]["ready_consumer_binding_count"] == 6 assert payload["rollups"]["ready_target_count"] == 6 assert payload["rollups"]["controlled_consumer_readback_ready"] is True assert payload["operation_boundaries"]["consumer_readback_only"] is True assert payload["operation_boundaries"]["mcp_tool_call_performed"] is False assert payload["operation_boundaries"]["raw_log_payload_persisted"] is False assert payload["operation_boundaries"]["github_api_used"] is False def test_runtime_receipt_auxiliary_sql_keeps_source_family_counts_schema_safe(): from src.services.ai_agent_autonomous_runtime_control import ( _RUNTIME_OPERATION_COUNTS_SQL, _RUNTIME_OPERATION_LATEST_SQL, ) assert "semantic_operation_type" in _RUNTIME_OPERATION_COUNTS_SQL assert "km_linked" in _RUNTIME_OPERATION_COUNTS_SQL assert "log_controlled_writeback_dispatched" in _RUNTIME_OPERATION_COUNTS_SQL assert "semantic_operation_type" in _RUNTIME_OPERATION_LATEST_SQL assert "km_linked" in _RUNTIME_OPERATION_LATEST_SQL assert "GROUP BY coalesce(status, 'unknown')" in _RUNTIME_TIMELINE_COUNTS_SQL assert "FROM timeline_events" in _RUNTIME_TIMELINE_COUNTS_SQL assert "count(*) AS total" in _RUNTIME_PLAYBOOK_TRUST_COUNTS_FALLBACK_SQL assert "FROM playbooks" in _RUNTIME_PLAYBOOK_TRUST_COUNTS_FALLBACK_SQL assert "updated_at" not in _RUNTIME_PLAYBOOK_TRUST_COUNTS_FALLBACK_SQL assert "trust_score" not in _RUNTIME_PLAYBOOK_TRUST_COUNTS_FALLBACK_SQL assert "FROM alert_operation_log" in _RUNTIME_ALERT_OPERATION_COUNTS_SQL assert "ALERT_RECEIVED" in _RUNTIME_ALERT_OPERATION_COUNTS_SQL assert "FROM awooop_conversation_event" in _RUNTIME_ALERTMANAGER_EVENT_COUNTS_SQL assert "source_envelope ->> 'stage'" in _RUNTIME_ALERTMANAGER_EVENT_COUNTS_SQL assert "channel_chat_id LIKE 'alert-group:%'" in _RUNTIME_GROUPED_ALERT_EVENT_COUNTS_SQL def test_ai_agent_autonomous_runtime_control_uses_current_owner_directive(): data = build_ai_agent_autonomous_runtime_control() assert data["schema_version"] == "ai_agent_autonomous_runtime_control_v1" assert data["program_status"]["runtime_authority"] == ( "current_owner_directive_controlled_ai_automation" ) assert data["program_status"]["deploy_readback_marker"] == ( "p2_416_d1n_autonomous_runtime_control_prod_readback_v2" ) assert data["program_status"]["deploy_attempt_note"] == ( "cd_internal_control_plane_readback_retry_20260628_2" ) assert data["program_status"]["legacy_no_send_no_live_rules_overridden"] is True assert data["program_status"]["implementation_completion_percent"] == 100 assert data["current_policy"]["low_risk_controlled_apply_allowed"] is True assert data["current_policy"]["medium_risk_controlled_apply_allowed"] is True assert data["current_policy"]["high_risk_controlled_apply_allowed"] is True assert data["current_policy"]["owner_review_required_for_low_medium_high"] is False assert data["current_policy"]["telegram_gateway_required"] is True assert data["current_policy"]["direct_bot_api_allowed"] is False assert data["current_policy"]["post_apply_verifier_required"] is True assert data["current_policy"]["km_learning_writeback_required"] is True def test_ai_agent_autonomous_runtime_control_exposes_reports_and_executor_receipts(): data = build_ai_agent_autonomous_runtime_control() cadences = {item["cadence"]: item for item in data["report_delivery"]["cadences"]} assert set(cadences) == {"daily", "weekly", "monthly"} assert {item["telegram_gateway_delivery_enabled"] for item in cadences.values()} == {True} assert {item["direct_bot_api_allowed"] for item in cadences.values()} == {False} assert "run_daily_report_loop" in cadences["daily"]["worker"] assert "run_weekly_report_loop" in cadences["weekly"]["worker"] assert "run_monthly_report_loop" in cadences["monthly"]["worker"] operation_types = { item["operation_type"] for item in data["controlled_executor"]["operation_receipts"] } assert { "ansible_candidate_matched", "ansible_check_mode_executed", "ansible_apply_executed", "incident_evidence.post_execution_state", "knowledge_entries", "log_controlled_writeback_dispatched", }.issubset(operation_types) assert data["rollups"]["automated_risk_tier_count"] == 3 assert data["rollups"]["report_cadence_enabled_count"] == 3 assert data["rollups"]["direct_bot_api_allowed_count"] == 0 assert data["rollups"]["legacy_policy_overridden_count"] >= 4 assert data["runtime_receipt_readback"]["db_read_status"] == "not_queried" _assert_log_controlled_writeback_executor( data["runtime_receipt_readback"]["log_controlled_writeback_executor"] ) consumer = data["runtime_receipt_readback"]["log_controlled_writeback_consumer"] assert consumer["schema_version"] == ( "ai_agent_log_controlled_writeback_consumer_readback_v1" ) assert consumer["status"] == "blocked_waiting_controlled_writeback_consumer_receipts" assert data["rollups"]["live_log_controlled_writeback_executor_batch_count"] == 6 assert data["rollups"]["live_log_controlled_writeback_executor_ready_batch_count"] == 6 assert data["rollups"]["live_log_controlled_writeback_executor_ready_count"] == 1 assert data["rollups"]["live_log_controlled_writeback_executor_blocker_count"] == 0 assert data["rollups"]["live_log_controlled_writeback_next_action_queue_count"] == 6 assert ( data["rollups"]["live_log_controlled_writeback_current_blocker_queue_count"] == 1 ) assert ( data["rollups"][ "live_log_controlled_writeback_current_blocker_control_path_blocked_count" ] == 1 ) assert ( data["rollups"][ "live_log_controlled_writeback_current_blocker_local_recovery_package_count" ] == 1 ) assert data["rollups"]["live_log_controlled_writeback_dispatch_count"] == 0 assert data["rollups"]["live_log_controlled_writeback_recent_dispatch_count"] == 0 assert data["rollups"]["live_log_controlled_writeback_consumer_binding_count"] == 0 assert data["rollups"]["live_log_controlled_writeback_consumer_ready_count"] == 0 assert data["rollups"]["live_log_controlled_writeback_consumer_blocker_count"] == 1 assert data["runtime_receipt_readback"]["learning_loop"]["status"] == "in_progress" assert ( data["runtime_receipt_readback"]["learning_loop"]["rollups"][ "required_stage_missing_count" ] == 7 ) def test_ai_agent_autonomous_runtime_control_exposes_internal_control_loop(): data = build_ai_agent_autonomous_runtime_control() integration = data["control_plane_integration"] assert integration["schema_version"] == "ai_agent_autonomous_runtime_internal_loop_v1" assert integration["status"] == "mcp_rag_km_playbook_log_control_loop_declared" assert {sensor["normalized_event"] for sensor in integration["mcp_sensors"]} == { "RunObservation", "RunnerLaneState", "ProductionTruthSnapshot", "FrontendTruthSnapshot", } assert "controlled_cd_lane_capacity_label_guardrails" in integration["rag_context_queries"] assert "running_no_container_stale_ui" in integration["playbook_decision_classes"] assert integration["km_writeback_contract"]["stores_raw_logs"] is False assert integration["km_writeback_contract"]["stores_secret_values"] is False assert integration["log_projection_contract"]["raw_html_or_long_log_allowed"] is False assert data["rollups"]["mcp_sensor_count"] == 4 assert data["rollups"]["playbook_decision_class_count"] == 7 def test_deploy_control_plane_classifier_separates_stale_spinner_from_real_failure(): stale = classify_deploy_control_plane_observation( run_status="running", is_latest_deploy_intent=True, active_task_container_count=0, production_marker_hit=True, latest_flow_closed=True, runner_capacity_ok=True, runner_forbidden_label_count=0, ) assert stale["classification"] == "running_no_container_stale_ui" assert stale["action"] == "treat_gitea_spinner_as_stale_and_keep_production_truth" assert stale["safety_boundary"]["writes_runtime_state"] is False assert stale["internal_writeback"]["km_writeback_required"] is True failure = classify_deploy_control_plane_observation( run_status="failure", is_latest_deploy_intent=True, active_task_container_count=0, production_marker_hit=False, latest_flow_closed=False, runner_capacity_ok=True, runner_forbidden_label_count=0, ) assert failure["classification"] == "real_failure_requires_playbook_repair" assert failure["action"] == "open_cd_repair_playbook_with_target_selector_and_verifier" assert failure["safety_boundary"]["opens_legacy_runner"] is False assert failure["internal_writeback"]["playbook_route_required"] is True def test_ai_agent_autonomous_runtime_control_keeps_hard_blockers_and_redaction(): data = build_ai_agent_autonomous_runtime_control() assert "secret_token_private_key_cookie_session_auth_header_cleartext" in data["hard_blockers"] assert "drop_truncate_restore_prune_destructive_database_operation" in data["hard_blockers"] assert "force_push_delete_repo_refs_or_visibility_change" in data["hard_blockers"] visibility = data["visibility_contract"] assert visibility["work_window_transcript_display_allowed"] is False assert visibility["prompt_body_display_allowed"] is False assert visibility["internal_reasoning_display_allowed"] is False assert visibility["sensitive_value_display_allowed"] is False assert visibility["telegram_unredacted_payload_display_allowed"] is False def test_runtime_receipt_readback_summarizes_live_executor_closure_rows(): apply_op_id = "73b7a95c-3652-4c0d-bb4c-729e500acedb" incident_id = "INC-20260627-64472B" readback = build_runtime_receipt_readback_from_rows( project_id="awoooi", db_read_status="ok", operation_count_rows=[ { "operation_type": "ansible_candidate_matched", "status": "dry_run", "total": 1, "recent": 1, }, { "operation_type": "ansible_apply_executed", "status": "success", "total": 1, "recent": 1, }, { "operation_type": "ansible_check_mode_executed", "status": "success", "total": 1, "recent": 1, }, { "operation_type": "ansible_learning_writeback_recorded", "status": "success", "total": 1, "recent": 1, }, { "operation_type": "log_controlled_writeback_dispatched", "status": "success", "total": 6, "recent": 6, }, ], operation_latest_rows=[ { "op_id": "candidate-op", "parent_op_id": None, "operation_type": "ansible_candidate_matched", "status": "dry_run", "actor": "decision_manager", "incident_id": incident_id, "catalog_id": "ansible:188-momo-backup-user", "playbook_path": "infra/ansible/playbooks/188-momo-backup-user.yml", "execution_mode": "check_mode", }, { "op_id": "check-mode-op", "parent_op_id": "candidate-op", "operation_type": "ansible_check_mode_executed", "status": "success", "actor": "ansible_check_mode_worker", "incident_id": incident_id, "catalog_id": "ansible:188-momo-backup-user", "playbook_path": "infra/ansible/playbooks/188-momo-backup-user.yml", "execution_mode": "check_mode", "returncode": "0", }, { "op_id": apply_op_id, "parent_op_id": "check-mode-op", "operation_type": "ansible_apply_executed", "status": "success", "actor": "ansible_controlled_apply_worker", "incident_id": incident_id, "catalog_id": "ansible:188-momo-backup-user", "playbook_path": "infra/ansible/playbooks/188-momo-backup-user.yml", "execution_mode": "controlled_apply", "source_candidate_op_id": "candidate-op", "check_mode_op_id": "check-mode-op", "returncode": "0", "duration_ms": 7727, }, { "op_id": "learning-op", "parent_op_id": apply_op_id, "operation_type": "ansible_learning_writeback_recorded", "status": "success", "actor": "ansible_controlled_apply_worker", "incident_id": incident_id, "catalog_id": "ansible:188-momo-backup-user", "playbook_path": "infra/ansible/playbooks/188-momo-backup-user.yml", "execution_mode": "learning_writeback", "returncode": "0", }, ], auto_repair_count_rows=[ {"result_status": "success", "total": 1, "recent": 1}, ], auto_repair_latest_rows=[ { "id": "auto-repair-1", "incident_id": incident_id, "catalog_id": "ansible:188-momo-backup-user", "playbook_name": "infra/ansible/playbooks/188-momo-backup-user.yml", "result_status": "success", "executed_steps_text": f'["apply:{apply_op_id}"]', "triggered_by": "ansible_controlled_apply", "risk_level": "low", "execution_time_ms": 7727, }, ], verifier_count_rows=[ {"verification_result": "success", "total": 1, "recent": 1}, ], verifier_latest_rows=[ { "id": "evidence-1", "incident_id": incident_id, "verification_result": "success", "apply_op_id": apply_op_id, "catalog_id": "ansible:188-momo-backup-user", "playbook_path": "infra/ansible/playbooks/188-momo-backup-user.yml", "returncode": "0", }, ], km_count_rows=[ {"status": "review", "total": 1, "recent": 1}, ], km_latest_rows=[ { "id": "km-1", "title": "AI 自動修復沉澱：INC-20260627-64472B", "related_incident_id": incident_id, "related_playbook_id": "ansible:188-momo-backup-user", "path_type": "ansible_apply_receipt:73b7a95c", "status": "review", "created_by": "ai_agent_ansible_worker", }, ], telegram_count_rows=[ {"send_status": "sent", "total": 1, "recent": 1}, ], telegram_latest_rows=[ { "message_id": "telegram-row-1", "run_id": "telegram-run-1", "message_type": "final", "send_status": "sent", "provider_message_id": "12345", "incident_id": incident_id, "action": "controlled_apply_result", }, ], mcp_gateway_count_rows=[ {"status": "success", "total": 3, "recent": 1}, ], legacy_mcp_count_rows=[ {"status": "success", "total": 2, "recent": 2}, ], service_log_count_rows=[ {"status": "sanitized_recent_logs", "total": 2, "recent": 2}, ], executor_log_count_rows=[ {"status": "success", "total": 2, "recent": 1}, ], timeline_count_rows=[ {"status": "success", "total": 1, "recent": 1}, ], playbook_trust_count_rows=[ {"status": "learning_active", "total": 4, "recent": 1}, ], alert_operation_count_rows=[ {"event_type": "ALERT_RECEIVED", "total": 5, "recent": 2}, {"event_type": "AUTO_REPAIR_TRIGGERED", "total": 2, "recent": 1}, {"event_type": "EXECUTION_STARTED", "total": 1, "recent": 1}, {"event_type": "EXECUTION_COMPLETED", "total": 1, "recent": 1}, {"event_type": "NOTIFICATION_CLASSIFIED", "total": 1, "recent": 1}, {"event_type": "GUARDRAIL_BLOCKED", "total": 1, "recent": 0}, ], alertmanager_event_count_rows=[ {"stage": "received", "total": 5, "recent": 2}, {"stage": "converged", "total": 3, "recent": 1}, {"stage": "llm_inflight_suppressed", "total": 1, "recent": 0}, ], grouped_alert_event_count_rows=[ {"status": "grouped_child_alert", "total": 4, "recent": 1}, ], log_controlled_writeback_consumer=_log_controlled_writeback_consumer_readback(), ) assert readback["db_read_status"] == "ok" assert readback["writes_on_read"] is False assert readback["ansible_apply_executed"]["total"] == 1 assert ( readback["ansible_operations"]["counts"]["log_controlled_writeback_dispatched"][ "total" ] == 6 ) assert readback["auto_repair_execution_receipt"]["by_status"]["success"] == 1 assert readback["post_apply_verifier"]["by_status"]["success"] == 1 assert readback["km_writeback"]["by_status"]["review"] == 1 assert readback["telegram_receipt"]["by_status"]["sent"] == 1 assert readback["latest_flow_closure"] == { "apply_op_id": apply_op_id, "incident_id": incident_id, "has_post_apply_verifier": True, "has_km_writeback": True, "has_telegram_receipt": True, "closed": True, "missing": [], } assert readback["latest_failure_classification"]["classification"] == ( "latest_controlled_apply_closed_success" ) assert readback["controlled_retry_package"]["status"] == "not_required_for_latest_apply" ledger = readback["autonomous_execution_loop_ledger"] assert ledger["schema_version"] == "ai_agent_autonomous_execution_loop_ledger_v1" assert ledger["operation_id"] == apply_op_id assert ledger["root_candidate_op_id"] == "candidate-op" assert ledger["check_mode_op_id"] == "check-mode-op" assert ledger["apply_op_id"] == apply_op_id assert ledger["execution_state"] == "closed_success" assert ledger["closed"] is True assert ledger["missing_stage_ids"] == [] assert ledger["next_executor_action"] == "keep_receipt_chain_closed" assert [stage["stage_id"] for stage in ledger["stages"]] == [ "candidate", "check_mode", "controlled_apply", "auto_repair_execution_receipt", "post_apply_verifier", "km_playbook_writeback", "telegram_receipt", ] assert {stage["present"] for stage in ledger["stages"]} == {True} assert ledger["safety_contract"]["backfill_may_send_telegram"] is False assert ledger["safety_contract"]["live_apply_may_send_telegram_gateway_receipt"] is True trace = readback["trace_ledger"] assert trace["schema_version"] == "ai_agent_autonomous_trace_ledger_v1" trace_stage_ids = {stage["stage_id"] for stage in trace["stages"]} assert { "mcp_context", "service_log_evidence", "candidate", "check_mode", "executor_log_projection", "controlled_apply", "auto_repair_execution_receipt", "post_apply_verifier", "rag_km_learning", "playbook_trust", "timeline_projection", "telegram_receipt", } == trace_stage_ids assert trace["missing_required_stage_ids"] == [] assert trace["recorded_stage_count"] == trace["stage_count"] assert "rag_km_learning" in trace["learning_source_stage_ids"] assert "playbook_trust" in trace["learning_source_stage_ids"] assert trace["public_safety"] == { "reads_raw_sessions": False, "stores_secret_values": False, "stores_unredacted_telegram_payload": False, "stores_internal_reasoning": False, } assert readback["mcp_context"]["total"] == 5 assert readback["service_log_evidence"]["total"] == 2 assert readback["executor_log_projection"]["total"] == 2 assert readback["playbook_trust"]["by_status"]["learning_active"] == 4 taxonomy = readback["log_integration_taxonomy"] assert taxonomy["schema_version"] == "ai_agent_log_integration_taxonomy_v1" assert taxonomy["normalized_event_flow"] == [ "collect_source_log_or_receipt", "redact_and_hash_sensitive_fields", "assign_labels", "correlate_incident_operation_playbook", "write_trace_ledger", "retrieve_similar_context_via_rag", "select_or_repair_playbook", "run_check_mode_then_controlled_apply", "verify_and_write_learning_back", ] assert { "project", "product", "website", "service", "package", "tool", "incident", "operation", "playbook", }.issubset(set(taxonomy["label_dimensions"])) source_family_ids = {item["source_family_id"] for item in taxonomy["source_families"]} assert { "mcp_gateway_tool_calls", "legacy_mcp_tool_calls", "service_package_logs", "executor_operation_logs", "auto_repair_receipts", "post_apply_verifier", "rag_km_entries", "playbook_trust_signals", "operator_timeline_projection", "telegram_delivery_receipts", } == source_family_ids assert taxonomy["rollups"]["source_family_count"] == 10 assert taxonomy["rollups"]["active_source_family_count"] == 10 assert taxonomy["rollups"]["classified_event_total"] > 0 assert { "project", "product", "website", "service", "package", "tool", "source_family", }.issubset(set(taxonomy["required_label_dimensions"])) assert taxonomy["public_safety"]["raw_secret_collection_allowed"] is False assert taxonomy["public_safety"]["unredacted_payload_storage_allowed"] is False _assert_log_controlled_writeback_executor( readback["log_controlled_writeback_executor"] ) _assert_log_controlled_writeback_consumer( readback["log_controlled_writeback_consumer"] ) decision_wiring = readback["agent_decision_wiring"] assert decision_wiring["schema_version"] == "ai_agent_decision_wiring_readback_v1" assert decision_wiring["status"] == "completed" assert decision_wiring["missing_required_stage_ids"] == [] assert decision_wiring["closed_loop_observed"] is True assert { stage["stage_id"] for stage in decision_wiring["stages"] if stage["required_for_decision_wiring"] } == { "labeled_evidence_sources", "rag_context_retrieval", "playbook_candidate_selection", "check_mode_dry_run", "controlled_apply_boundary", "post_apply_verifier", } assert decision_wiring["rollups"]["candidate_total"] == 1 assert decision_wiring["rollups"]["check_mode_total"] == 1 assert decision_wiring["rollups"]["controlled_apply_total"] == 1 assert decision_wiring["rollups"]["required_stage_missing_count"] == 0 learning_loop = readback["learning_loop"] assert learning_loop["schema_version"] == "ai_agent_learning_loop_readback_v1" assert learning_loop["status"] == "completed" assert learning_loop["missing_required_stage_ids"] == [] assert { stage["stage_id"] for stage in learning_loop["stages"] if stage["required_for_learning_loop"] } == { "verified_execution_outcome", "km_learning_writeback", "learning_repair_record", "playbook_trust_delta", "similar_case_context", "repair_candidate_feedback", "next_decision_context", } assert learning_loop["rollups"]["required_stage_present_count"] == 7 assert learning_loop["rollups"]["required_stage_missing_count"] == 0 assert learning_loop["rollups"]["learning_writeback_total"] == 1 assert learning_loop["rollups"]["learning_writeback_recent"] == 1 assert learning_loop["rollups"]["similar_case_source_total"] > 0 assert learning_loop["rollups"]["repair_feedback_ready_count"] == 1 assert learning_loop["public_safety"]["stores_secret_values"] is False assert learning_loop["public_safety"]["executes_on_read"] is False alert_noise = readback["alert_noise_reduction"] assert alert_noise["schema_version"] == "ai_agent_alert_noise_reduction_readback_v1" assert alert_noise["status"] == "completed" assert alert_noise["missing_required_stage_ids"] == [] assert { stage["stage_id"] for stage in alert_noise["stages"] if stage["required_for_noise_reduction"] } == { "alert_intake_receipts", "duplicate_convergence", "notification_suppression", "ai_controlled_routing", "learning_feedback", } assert alert_noise["rollups"]["required_stage_present_count"] == 5 assert alert_noise["rollups"]["required_stage_missing_count"] == 0 assert alert_noise["rollups"]["alert_received_total"] == 10 assert alert_noise["rollups"]["suppressed_alert_total"] == 8 assert alert_noise["rollups"]["controlled_route_total"] == 8 assert alert_noise["routing_policy"]["manual_default_route_allowed"] is False assert alert_noise["routing_policy"]["low_medium_high_alerts_route_to_ai_controlled_queue"] is True assert alert_noise["public_safety"]["stores_raw_alert_payload"] is False ui_productization = readback["ui_productization"] assert ui_productization["schema_version"] == "ai_agent_ui_productization_readback_v1" assert ui_productization["status"] == "completed" assert ui_productization["missing_required_surface_ids"] == [] assert ui_productization["public_safety"]["manual_default_outcome_allowed"] is False assert ui_productization["rollups"]["required_surface_present_count"] == 5 assert ui_productization["rollups"]["segmented_filter_count"] == 5 multi_product = readback["multi_product_taxonomy"] assert multi_product["schema_version"] == "ai_agent_multi_product_taxonomy_contract_v1" assert multi_product["status"] == "completed" assert multi_product["missing_product_scope_ids"] == [] assert multi_product["missing_required_dimension_ids"] == [] assert { "awoooi", "stockplatform", "vibework", "momo", "awooogo", "tsenyang", "agent_bounty_protocol", "public_websites", } == {scope["product_id"] for scope in multi_product["product_scopes"]} assert multi_product["rollups"]["product_scope_count"] == 8 assert multi_product["rollups"]["contract_ready_product_scope_count"] == 8 assert multi_product["rollups"]["runtime_adapter_active_count"] == 1 assert multi_product["public_safety"]["external_product_runtime_write_enabled_on_read"] is False progress = readback["work_item_progress"] assert progress["schema_version"] == "ai_agent_automation_work_item_progress_v1" ordered_ids = [item["work_item_id"] for item in progress["ordered_items"]] assert ordered_ids == [ "P0-A-runtime-truth", "P0-B-trace-ledger", "P0-C-log-taxonomy", "P0-D-ui-visibility", "P0-E-verification-deploy", "P1-A-ingestion-coverage", "P1-B-agent-decision-wiring", "P1-C-learning-loop", "P1-D-alert-noise-reduction", "P1-E-log-controlled-writeback-executor", "P1-F-log-controlled-writeback-consumer", "P2-A-ui-ux-productization", "P2-B-multi-product-expansion", ] assert progress["ordered_items"][4]["status"] == "completed" assert progress["ordered_items"][5]["status"] == "completed" assert progress["ordered_items"][6]["status"] == "completed" assert progress["ordered_items"][7]["status"] == "completed" assert progress["ordered_items"][7]["remaining_learning_loop_stage_count"] == 0 assert progress["ordered_items"][8]["status"] == "completed" assert progress["ordered_items"][8]["remaining_alert_noise_stage_count"] == 0 assert progress["ordered_items"][9]["status"] == "completed" assert progress["ordered_items"][9]["remaining_executor_batch_count"] == 0 assert progress["ordered_items"][9]["active_blocker_count"] == 0 assert progress["ordered_items"][10]["status"] == "completed" assert progress["ordered_items"][10]["remaining_consumer_binding_count"] == 0 assert progress["ordered_items"][10]["active_blocker_count"] == 0 assert progress["ordered_items"][11]["status"] == "completed" assert progress["ordered_items"][11]["remaining_ui_surface_count"] == 0 assert progress["ordered_items"][12]["status"] == "completed" assert progress["ordered_items"][12]["remaining_product_scope_count"] == 0 assert progress["source_family_items"] assert {item["status"] for item in progress["source_family_items"]} == {"completed"} assert progress["rollups"]["source_family_work_item_count"] == 10 assert progress["rollups"]["completed_count"] == 23 assert progress["rollups"]["pending_count"] == 0 def test_runtime_receipt_work_items_use_learning_receipts_without_latest_telegram_gate(): apply_op_id = "2f8ef5c8-fd4e-4950-99e9-dc9e61150cab" incident_id = "INC-20260629-LEARNING" readback = build_runtime_receipt_readback_from_rows( project_id="awoooi", db_read_status="ok", operation_count_rows=[ { "operation_type": "ansible_candidate_matched", "status": "dry_run", "total": 1, "recent": 1, }, { "operation_type": "ansible_check_mode_executed", "status": "success", "total": 1, "recent": 1, }, { "operation_type": "ansible_apply_executed", "status": "success", "total": 1, "recent": 1, }, { "operation_type": "ansible_learning_writeback_recorded", "status": "success", "total": 1, "recent": 1, }, ], operation_latest_rows=[ { "op_id": "candidate-op-learning", "parent_op_id": None, "operation_type": "ansible_candidate_matched", "status": "dry_run", "actor": "decision_manager", "incident_id": incident_id, "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "execution_mode": "check_mode", }, { "op_id": "check-mode-op-learning", "parent_op_id": "candidate-op-learning", "operation_type": "ansible_check_mode_executed", "status": "success", "actor": "ansible_check_mode_worker", "incident_id": incident_id, "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "execution_mode": "check_mode", "returncode": "0", }, { "op_id": apply_op_id, "parent_op_id": "check-mode-op-learning", "operation_type": "ansible_apply_executed", "status": "success", "actor": "ansible_controlled_apply_worker", "incident_id": incident_id, "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "execution_mode": "controlled_apply", "source_candidate_op_id": "candidate-op-learning", "check_mode_op_id": "check-mode-op-learning", "returncode": "0", }, { "op_id": "learning-op", "parent_op_id": apply_op_id, "operation_type": "ansible_learning_writeback_recorded", "status": "success", "actor": "ansible_controlled_apply_worker", "incident_id": incident_id, "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "execution_mode": "learning_writeback", "returncode": "0", }, ], auto_repair_count_rows=[ {"result_status": "success", "total": 1, "recent": 1}, ], auto_repair_latest_rows=[ { "id": "auto-repair-learning", "incident_id": incident_id, "catalog_id": "ansible:188-ai-web", "playbook_name": "infra/ansible/playbooks/188-ai-web.yml", "result_status": "success", "executed_steps_text": f'["apply:{apply_op_id}"]', "triggered_by": "ansible_controlled_apply", "risk_level": "low", "execution_time_ms": 2400, }, ], verifier_count_rows=[ {"verification_result": "success", "total": 1, "recent": 1}, ], verifier_latest_rows=[ { "id": "evidence-learning", "incident_id": incident_id, "verification_result": "success", "apply_op_id": apply_op_id, "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "returncode": "0", }, ], km_count_rows=[ {"status": "review", "total": 1, "recent": 1}, ], km_latest_rows=[ { "id": "km-learning", "title": "AI 自動修復沉澱：INC-20260629-LEARNING", "related_incident_id": incident_id, "related_playbook_id": "ansible:188-ai-web", "path_type": "ansible_apply_receipt:2f8ef5c8", "status": "review", "created_by": "ai_agent_ansible_worker", }, ], telegram_count_rows=[ {"send_status": "sent", "total": 1, "recent": 1}, ], telegram_latest_rows=[], mcp_gateway_count_rows=[ {"status": "success", "total": 1, "recent": 1}, ], legacy_mcp_count_rows=[ {"status": "success", "total": 1, "recent": 1}, ], service_log_count_rows=[ {"status": "sanitized_recent_logs", "total": 1, "recent": 1}, ], executor_log_count_rows=[ {"status": "success", "total": 1, "recent": 1}, ], timeline_count_rows=[ {"status": "success", "total": 1, "recent": 1}, ], playbook_trust_count_rows=[ {"status": "learning_active", "total": 1, "recent": 1}, ], alert_operation_count_rows=[ {"event_type": "ALERT_RECEIVED", "total": 5, "recent": 2}, {"event_type": "AUTO_REPAIR_TRIGGERED", "total": 2, "recent": 1}, {"event_type": "EXECUTION_STARTED", "total": 1, "recent": 1}, {"event_type": "EXECUTION_COMPLETED", "total": 1, "recent": 1}, ], alertmanager_event_count_rows=[ {"stage": "received", "total": 5, "recent": 2}, {"stage": "converged", "total": 3, "recent": 1}, {"stage": "llm_inflight_suppressed", "total": 1, "recent": 1}, ], grouped_alert_event_count_rows=[ {"status": "grouped_child_alert", "total": 4, "recent": 1}, ], log_controlled_writeback_consumer=_log_controlled_writeback_consumer_readback(), ) assert readback["latest_flow_closure"]["closed"] is False assert readback["latest_flow_closure"]["missing"] == ["telegram_receipt"] assert readback["autonomous_execution_loop_ledger"]["closed"] is False assert readback["learning_loop"]["status"] == "completed" assert readback["learning_loop"]["missing_required_stage_ids"] == [] assert readback["learning_loop"]["rollups"]["next_decision_ready_count"] == 1 assert readback["alert_noise_reduction"]["status"] == "completed" assert readback["alert_noise_reduction"]["missing_required_stage_ids"] == [] progress = readback["work_item_progress"] statuses = { item["work_item_id"]: item["status"] for item in progress["ordered_items"] } assert statuses["P1-C-learning-loop"] == "completed" assert statuses["P1-D-alert-noise-reduction"] == "completed" assert statuses["P1-E-log-controlled-writeback-executor"] == "completed" assert statuses["P1-F-log-controlled-writeback-consumer"] == "completed" assert statuses["P2-A-ui-ux-productization"] == "completed" assert statuses["P2-B-multi-product-expansion"] == "completed" assert {item["status"] for item in progress["source_family_items"]} == {"completed"} assert progress["rollups"]["completed_count"] == 23 assert progress["rollups"]["pending_count"] == 0 def test_runtime_receipt_readback_classifies_closed_failed_apply_as_ai_repair(): apply_op_id = "94925d5e-6fdc-49c3-90e8-f0a0d57a6a58" incident_id = "INC-20260628-A40A9A" readback = build_runtime_receipt_readback_from_rows( project_id="awoooi", db_read_status="ok", operation_count_rows=[ { "operation_type": "ansible_apply_executed", "status": "failed", "total": 1, "recent": 1, }, ], operation_latest_rows=[ { "op_id": "8b555f41-e81f-4d8e-956b-fb20d358db63", "parent_op_id": "candidate-op-2", "operation_type": "ansible_check_mode_executed", "status": "success", "actor": "ansible_check_mode_worker", "incident_id": incident_id, "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web-readonly.yml", "execution_mode": "check_mode", "returncode": "0", }, { "op_id": apply_op_id, "parent_op_id": "8b555f41-e81f-4d8e-956b-fb20d358db63", "operation_type": "ansible_apply_executed", "status": "failed", "actor": "ansible_controlled_apply_worker", "incident_id": incident_id, "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "execution_mode": "controlled_apply", "source_candidate_op_id": "candidate-op-2", "check_mode_op_id": "8b555f41-e81f-4d8e-956b-fb20d358db63", "returncode": "2", "duration_ms": 4797, }, ], auto_repair_count_rows=[ {"result_status": "failed", "total": 1, "recent": 1}, ], auto_repair_latest_rows=[ { "id": "auto-repair-2", "incident_id": incident_id, "catalog_id": "ansible:188-ai-web", "playbook_name": "infra/ansible/playbooks/188-ai-web.yml", "result_status": "failed", "executed_steps_text": f'["apply:{apply_op_id}"]', "triggered_by": "ansible_controlled_apply", "risk_level": "medium", "execution_time_ms": 4797, }, ], verifier_count_rows=[ {"verification_result": "failed", "total": 1, "recent": 1}, ], verifier_latest_rows=[ { "id": "evidence-1", "incident_id": incident_id, "verification_result": "failed", "apply_op_id": apply_op_id, "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "returncode": "2", }, ], km_count_rows=[ {"status": "REVIEW", "total": 1, "recent": 1}, ], km_latest_rows=[ { "id": "km-1", "title": "AI 自動修復沉澱：INC-20260628-A40A9A", "related_incident_id": incident_id, "related_playbook_id": "ansible:188-ai-web", "path_type": "ansible_apply_receipt:94925d5e", "status": "REVIEW", "created_by": "ai_agent_ansible_worker", }, ], telegram_count_rows=[ {"send_status": "sent", "total": 1, "recent": 1}, ], telegram_latest_rows=[ { "message_id": "telegram-row-1", "run_id": "telegram-run-1", "message_type": "final", "send_status": "sent", "provider_message_id": "32016", "incident_id": incident_id, "action": "controlled_apply_result", }, ], ) classification = readback["latest_failure_classification"] assert classification["classification"] == "closed_failed_apply_requires_ai_repair" assert classification["action"] == "queue_check_mode_replay_and_playbook_repair_candidate" assert classification["target_selector"] == { "incident_id": incident_id, "apply_op_id": apply_op_id, "parent_op_id": "8b555f41-e81f-4d8e-956b-fb20d358db63", "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "execution_mode": "controlled_apply", } assert classification["evidence"]["returncode"] == "2" assert classification["evidence"]["verification_result"] == "failed" assert classification["evidence"]["latest_flow_closed"] is True assert classification["evidence"]["output_tail_in_readback"] is False assert classification["evidence"]["unredacted_output_required"] is False assert classification["safe_next_steps"] == [ "run_no_write_check_mode_replay", "extract_sanitized_failed_task_summary", "write_km_playbook_repair_candidate", "retry_controlled_apply_only_after_check_mode_passes", ] retry = readback["controlled_retry_package"] assert retry["package_id"] == "ansible_retry:94925d5e" assert retry["status"] == "ready_for_no_write_check_mode_replay" assert retry["source_of_truth"] == { "catalog_id": "ansible:188-ai-web", "playbook_path": "infra/ansible/playbooks/188-ai-web.yml", "source_diff_required_before_retry": True, "failed_task_summary_required": True, } assert retry["preflight"]["no_write_check_mode_replay_required"] is True assert retry["preflight"]["reuse_parent_check_mode_op_id"] == ( "8b555f41-e81f-4d8e-956b-fb20d358db63" ) assert retry["apply_gate"]["controlled_apply_retry_allowed_now"] is False assert retry["apply_gate"]["requires_check_mode_success_before_apply"] is True assert retry["rollback"]["destructive_rollback_allowed"] is False assert retry["post_apply"] == { "post_apply_verifier_required": True, "km_playbook_trust_writeback_required": True, "telegram_receipt_required": True, } assert retry["next_ai_action"] == "run_no_write_check_mode_replay" ledger = readback["autonomous_execution_loop_ledger"] assert ledger["closed"] is True assert ledger["execution_state"] == "closed_failed_apply_repair_ready" assert ledger["next_executor_action"] == "run_no_write_check_mode_replay" assert ledger["missing_stage_ids"] == [] assert ledger["stages"][3]["stage_id"] == "auto_repair_execution_receipt" assert ledger["stages"][3]["status"] == "failed" def test_runtime_execution_loop_ledger_does_not_mix_unrelated_check_mode_rows(): apply_op_id = "db3f12ce-08fc-4289-8c93-338305d5850c" readback = build_runtime_receipt_readback_from_rows( project_id="awoooi", db_read_status="ok", operation_latest_rows=[ { "op_id": "unrelated-check-mode-op", "parent_op_id": "unrelated-candidate", "operation_type": "ansible_check_mode_executed", "status": "success", "actor": "ansible_check_mode_worker", "incident_id": "INC-OTHER", "catalog_id": "ansible:110-devops", "playbook_path": "infra/ansible/playbooks/110-devops.yml", "execution_mode": "check_mode", "returncode": "0", }, { "op_id": apply_op_id, "parent_op_id": "expected-check-mode-op", "operation_type": "ansible_apply_executed", "status": "success", "actor": "ansible_controlled_apply_worker", "incident_id": "INC-20260629-LEDGER", "catalog_id": "ansible:188-momo-backup-user", "playbook_path": "infra/ansible/playbooks/188-momo-backup-user.yml", "execution_mode": "controlled_apply", "returncode": "0", }, ], ) ledger = readback["autonomous_execution_loop_ledger"] assert ledger["operation_id"] == apply_op_id assert ledger["check_mode_op_id"] == "expected-check-mode-op" assert ledger["root_candidate_op_id"] is None assert ledger["incident_id"] == "INC-20260629-LEDGER" assert ledger["stages"][1]["stage_id"] == "check_mode" assert ledger["stages"][1]["ref_id"] == "expected-check-mode-op" assert ledger["stages"][1]["status"] == "inferred_from_apply_parent" assert "candidate" in ledger["missing_stage_ids"]