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feat(api): roll up log writeback executor readiness
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Your Name
2026-06-30 00:15:34 +08:00
parent 20aa1bf0f7
commit 56ba5fc38d
2 changed files with 216 additions and 6 deletions
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152
apps/api/src/services/ai_agent_autonomous_runtime_control.py
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@@ -18,6 +18,9 @@ from sqlalchemy import text
from src.core.config import settings
from src.core.logging import get_logger
from src.db.base import get_db_context
from src.services.ai_agent_log_controlled_writeback_executor_readback import (
load_latest_ai_agent_log_controlled_writeback_executor_readback,
)
from src.services.report_generation_service import (
DAILY_REPORT_HOUR_TAIPEI,
MONTHLY_REPORT_DAY_TAIPEI,
@@ -178,6 +181,90 @@ def _status_recent(summary: Mapping[str, Any] | None, *statuses: str) -> int:
return sum(_int_value(by_status.get(status)) for status in statuses)
def _load_log_controlled_writeback_executor_readback() -> dict[str, Any]:
"""Attach the LOG/KM/RAG/MCP/PlayBook executor queue without dispatching it."""
try:
return load_latest_ai_agent_log_controlled_writeback_executor_readback()
except Exception as exc: # pragma: no cover - keeps runtime control API visible
logger.warning(
"log_controlled_writeback_executor_readback_failed",
error_type=type(exc).__name__,
)
return {
"schema_version": "ai_agent_log_controlled_writeback_executor_readback_v1",
"priority": "P1-LOG-KM-RAG-MCP-PLAYBOOK",
"scope": "ai_agent_log_controlled_writeback_executor",
"status": "blocked_waiting_log_controlled_writeback_executor_readback",
"readback": {
"workplan_id": "P1-LOG-CONTROLLED-WRITEBACK-EXECUTOR",
"workplan_title": "LOG feedback controlled writeback executor and AI Agent consumption readback",
"safe_next_step": "repair_log_controlled_writeback_executor_readback_then_retry",
"error_type": type(exc).__name__,
},
"executor_policy": {
"executor_route": "ai_agent_metadata_writeback_executor",
"low_medium_high_controlled_apply_enabled": True,
"owner_review_required_for_low_medium_high": False,
"critical_break_glass_required": True,
"target_selector_required": True,
"source_of_truth_diff_required": True,
"check_mode_required": True,
"rollback_required": True,
"post_apply_verifier_required": True,
},
"execution_batches": [],
"agent_consumption_context": {
"context_id": "ai-agent-log-controlled-writeback-consumption-v1",
"consumable_by": [
"ai_agent_autonomous_runtime_control",
"awooop_work_items",
"alert_triage_loop",
"km_rag_playbook_learning_loop",
"mcp_audit_context_loop",
],
"evidence_chain": [
"/api/v1/agents/agent-log-intelligence-integration-readback",
"/api/v1/agents/agent-log-feedback-receipt-dry-run",
"/api/v1/agents/agent-log-post-write-verifier-dry-run",
"/api/v1/agents/agent-log-controlled-writeback-plan-readback",
],
"next_action_queue": [],
"learning_feedback_targets": [],
"raw_payload_required": False,
},
"rollups": {
"source_writeback_plan_count": 0,
"execution_batch_count": 0,
"ready_execution_batch_count": 0,
"target_count": 0,
"target_selector_count": 0,
"source_of_truth_diff_count": 0,
"check_mode_ready_count": 0,
"rollback_ready_count": 0,
"post_apply_verifier_ready_count": 0,
"controlled_executor_dispatch_ready": False,
"controlled_apply_enabled_by_policy": True,
"runtime_dispatch_performed": False,
},
"active_blockers": ["log_controlled_writeback_executor_readback_unavailable"],
"operation_boundaries": {
"executor_readback_only": True,
"controlled_apply_enabled_by_policy": True,
"executor_dispatch_performed": False,
"km_write_performed": False,
"rag_index_write_performed": False,
"playbook_trust_write_performed": False,
"mcp_tool_call_performed": False,
"agent_runtime_action_performed": False,
"workflow_trigger_performed": False,
"raw_log_payload_persisted": False,
"secret_value_collection_allowed": False,
"github_api_used": False,
},
}
def _trace_stage(
*,
stage_id: str,
@@ -1533,6 +1620,7 @@ def _build_work_item_progress(
*,
trace_ledger: Mapping[str, Any],
log_integration_taxonomy: Mapping[str, Any],
log_controlled_writeback_executor: Mapping[str, Any],
agent_decision_wiring: Mapping[str, Any],
learning_loop: Mapping[str, Any],
alert_noise_reduction: Mapping[str, Any],
@@ -1581,6 +1669,20 @@ def _build_work_item_progress(
and alert_noise_reduction.get("status") == "completed"
and alert_noise_missing == 0
)
log_executor_rollups = log_controlled_writeback_executor.get("rollups")
if not isinstance(log_executor_rollups, Mapping):
log_executor_rollups = {}
log_executor_blockers = log_controlled_writeback_executor.get("active_blockers")
if not isinstance(log_executor_blockers, list):
log_executor_blockers = []
log_executor_ready = (
log_controlled_writeback_executor.get("schema_version")
== "ai_agent_log_controlled_writeback_executor_readback_v1"
and log_controlled_writeback_executor.get("status")
== "controlled_writeback_executor_ready"
and log_executor_rollups.get("controlled_executor_dispatch_ready") is True
and not log_executor_blockers
)
ui_rollups = ui_productization.get("rollups")
if not isinstance(ui_rollups, Mapping):
ui_rollups = {}
@@ -1680,11 +1782,24 @@ def _build_work_item_progress(
"exit_criteria": "repeated alerts are clustered, deduped, routed to controlled automation, and no longer default to manual handling",
"remaining_alert_noise_stage_count": alert_noise_missing,
},
{
"work_item_id": "P1-E-log-controlled-writeback-executor",
"priority": "P1-E",
"title": "LOG feedback executor queue for KM / RAG / MCP / PlayBook",
"status": "completed" if log_executor_ready else "in_progress" if p1d_completed else "pending",
"exit_criteria": "executor readback exposes ready batches, target selectors, source diffs, rollback, verifier, and next-action queue",
"remaining_executor_batch_count": max(
0,
_int_value(log_executor_rollups.get("execution_batch_count"))
- _int_value(log_executor_rollups.get("ready_execution_batch_count")),
),
"active_blocker_count": len(log_executor_blockers),
},
{
"work_item_id": "P2-A-ui-ux-productization",
"priority": "P2-A",
"title": "Professional product UI replacing text-heavy surfaces",
"status": "completed" if p2a_completed else "in_progress" if p1d_completed else "pending",
"status": "completed" if p2a_completed else "in_progress" if log_executor_ready else "pending",
"exit_criteria": "AI automation status is shown as dense dashboard controls, filters, counters, and action rails",
"remaining_ui_surface_count": ui_surface_missing,
},
@@ -2589,9 +2704,11 @@ def build_runtime_receipt_readback_from_rows(
)
ui_productization = _build_ui_productization_readback()
multi_product_taxonomy = _build_multi_product_taxonomy_contract(log_integration_taxonomy)
log_controlled_writeback_executor = _load_log_controlled_writeback_executor_readback()
work_item_progress = _build_work_item_progress(
trace_ledger=trace_ledger,
log_integration_taxonomy=log_integration_taxonomy,
log_controlled_writeback_executor=log_controlled_writeback_executor,
agent_decision_wiring=agent_decision_wiring,
learning_loop=learning_loop,
alert_noise_reduction=alert_noise_reduction,
@@ -2718,6 +2835,7 @@ def build_runtime_receipt_readback_from_rows(
"autonomous_execution_loop_ledger": loop_ledger,
"trace_ledger": trace_ledger,
"log_integration_taxonomy": log_integration_taxonomy,
"log_controlled_writeback_executor": log_controlled_writeback_executor,
"agent_decision_wiring": agent_decision_wiring,
"learning_loop": learning_loop,
"alert_noise_reduction": alert_noise_reduction,
@@ -2739,6 +2857,21 @@ def _attach_runtime_receipt_readback(
) -> dict[str, Any]:
payload["runtime_receipt_readback"] = readback
rollups = payload.setdefault("rollups", {})
log_executor = readback.get("log_controlled_writeback_executor")
if not isinstance(log_executor, Mapping):
log_executor = {}
log_executor_rollups = log_executor.get("rollups")
if not isinstance(log_executor_rollups, Mapping):
log_executor_rollups = {}
log_executor_context = log_executor.get("agent_consumption_context")
if not isinstance(log_executor_context, Mapping):
log_executor_context = {}
log_executor_queue = log_executor_context.get("next_action_queue")
if not isinstance(log_executor_queue, list):
log_executor_queue = []
log_executor_blockers = log_executor.get("active_blockers")
if not isinstance(log_executor_blockers, list):
log_executor_blockers = []
rollups.update({
"live_ansible_apply_executed_count": _int_value(
readback.get("ansible_apply_executed", {}).get("total")
@@ -2826,6 +2959,23 @@ def _attach_runtime_receipt_readback(
"recent_classified_event_total"
)
),
"live_log_controlled_writeback_executor_batch_count": _int_value(
log_executor_rollups.get("execution_batch_count")
),
"live_log_controlled_writeback_executor_ready_batch_count": _int_value(
log_executor_rollups.get("ready_execution_batch_count")
),
"live_log_controlled_writeback_executor_ready_count": (
1
if log_executor.get("status") == "controlled_writeback_executor_ready"
else 0
),
"live_log_controlled_writeback_executor_blocker_count": len(
log_executor_blockers
),
"live_log_controlled_writeback_next_action_queue_count": len(
log_executor_queue
),
"live_agent_decision_wiring_stage_count": _int_value(
((readback.get("agent_decision_wiring") or {}).get("rollups") or {}).get(
"stage_count"