223 lines
8.6 KiB
Python
223 lines
8.6 KiB
Python
from __future__ import annotations
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import json
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import pytest
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from src.services.ai_agent_interaction_learning_proof import (
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load_latest_ai_agent_interaction_learning_proof,
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)
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def test_load_latest_ai_agent_interaction_learning_proof_reads_committed_snapshot():
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data = load_latest_ai_agent_interaction_learning_proof()
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assert data["schema_version"] == "ai_agent_interaction_learning_proof_v1"
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assert data["program_status"]["overall_completion_percent"] == 94
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assert data["program_status"]["current_task_id"] == "P2-403G"
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assert data["program_status"]["next_task_id"] == "P2-403H"
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assert data["program_status"]["read_only_mode"] is True
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assert data["program_status"]["runtime_authority"] == "proof_surface_only_no_live_worker"
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assert data["live_truth"]["runtime_loop_enabled"] is False
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assert data["live_truth"]["active_live_agent_sessions"] == 0
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assert data["live_truth"]["live_learning_writes_24h"] == 0
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assert data["frontend_redaction"]["operator_conversation_display_allowed"] is False
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assert data["frontend_redaction"]["agent_private_reasoning_display_allowed"] is False
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assert data["frontend_redaction"]["raw_prompt_display_allowed"] is False
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assert data["approval_boundaries"]["runtime_worker_allowed"] is False
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assert data["approval_boundaries"]["telegram_direct_send_allowed"] is False
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assert data["rollups"]["proof_level_count"] == len(data["proof_ladder"]) == 7
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assert data["rollups"]["signal_count"] == len(data["proof_signals"]) == 9
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assert data["rollups"]["operator_surface_count"] == len(data["operator_surfaces"]) == 5
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assert data["rollups"]["runtime_gate_count"] == len(data["runtime_gates"]) == 5
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assert data["rollups"]["live_signal_count"] == 0
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assert data["rollups"]["live_pending_level_ids"] == []
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assert {lane["agent_id"] for lane in data["agent_lanes"]} == {
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"openclaw",
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"hermes",
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"nemotron",
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}
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def test_load_latest_ai_agent_interaction_learning_proof_rejects_runtime_worker(tmp_path):
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snapshot = _snapshot()
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snapshot["approval_boundaries"]["runtime_worker_allowed"] = True
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(tmp_path / "ai_agent_interaction_learning_proof_2026-06-11.json").write_text(
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json.dumps(snapshot),
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encoding="utf-8",
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)
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with pytest.raises(ValueError, match="approval boundaries"):
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load_latest_ai_agent_interaction_learning_proof(tmp_path)
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def test_load_latest_ai_agent_interaction_learning_proof_rejects_live_truth(tmp_path):
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snapshot = _snapshot()
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snapshot["live_truth"]["runtime_loop_enabled"] = True
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(tmp_path / "ai_agent_interaction_learning_proof_2026-06-11.json").write_text(
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json.dumps(snapshot),
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encoding="utf-8",
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)
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with pytest.raises(ValueError, match="live truth flags"):
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load_latest_ai_agent_interaction_learning_proof(tmp_path)
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def test_load_latest_ai_agent_interaction_learning_proof_rejects_rollup_mismatch(tmp_path):
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snapshot = _snapshot()
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snapshot["rollups"]["signal_count"] = 99
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(tmp_path / "ai_agent_interaction_learning_proof_2026-06-11.json").write_text(
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json.dumps(snapshot),
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encoding="utf-8",
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)
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with pytest.raises(ValueError, match="rollup counts"):
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load_latest_ai_agent_interaction_learning_proof(tmp_path)
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def test_load_latest_ai_agent_interaction_learning_proof_rejects_transcript_display(tmp_path):
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snapshot = _snapshot()
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snapshot["frontend_redaction"]["operator_conversation_display_allowed"] = True
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(tmp_path / "ai_agent_interaction_learning_proof_2026-06-11.json").write_text(
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json.dumps(snapshot),
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encoding="utf-8",
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)
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with pytest.raises(ValueError, match="operator conversation display"):
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load_latest_ai_agent_interaction_learning_proof(tmp_path)
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def _snapshot() -> dict:
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return {
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"schema_version": "ai_agent_interaction_learning_proof_v1",
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"generated_at": "2026-06-11T23:20:00+08:00",
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"program_status": {
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"overall_completion_percent": 65,
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"current_priority": "P2",
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"current_task_id": "P2-403C",
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"next_task_id": "P2-403D",
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"read_only_mode": True,
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"runtime_authority": "proof_surface_only_no_live_worker",
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},
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"live_truth": {
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"runtime_loop_enabled": False,
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"live_agent_session_readback_enabled": False,
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"redis_consumer_group_enabled": False,
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"telegram_send_enabled": False,
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"learning_writeback_enabled": False,
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"active_live_agent_sessions": 0,
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"live_agent_messages_24h": 0,
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"live_handoffs_24h": 0,
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"live_learning_writes_24h": 0,
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"telegram_digest_receipts_24h": 0,
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},
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"proof_ladder": [
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_proof_level("contract_surface", "contract_ready"),
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_proof_level("proof_dashboard", "proof_surface_ready"),
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_proof_level("live_read_model", "contract_ready"),
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],
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"agent_lanes": [
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_agent_lane("openclaw"),
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_agent_lane("hermes"),
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_agent_lane("nemotron"),
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],
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"proof_signals": [
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{
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"signal_id": "agent_heartbeat",
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"display_name": "Agent 心跳",
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"category": "heartbeat",
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"source_of_truth": "agent_sessions.last_seen_at",
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"visible_surface": "governance",
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"current_state": "live_pending",
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"operator_interpretation": "測試。",
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"next_gate": "P2-403B",
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}
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],
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"operator_surfaces": [
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{
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"surface_id": "governance_agent_proof_panel",
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"display_name": "治理頁 Agent 證據面板",
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"route_or_channel": "/zh-TW/governance?tab=automation-inventory",
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"operator_feel": "測試。",
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"redaction_policy": "只顯示摘要。",
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"current_state": "implemented_read_only",
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}
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],
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"runtime_gates": [
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{
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"gate_id": "agent_session_read_model_gate",
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"display_name": "AgentSession 唯讀 read model",
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"status": "approval_required",
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"required_before_green": "測試。",
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"next_task_id": "P2-403B",
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}
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],
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"learning_memory_stack": [
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{
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"layer_id": "hot_agent_session_memory",
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"display_name": "Hot",
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"storage_or_service": "agent_sessions",
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"visible_growth_signal": "心跳",
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"current_state": "pending",
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}
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],
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"telegram_receipt_contract": {
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"direct_send_allowed": False,
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"gateway_queue_write_allowed": False,
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"receipt_visible_to_operator": True,
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},
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"frontend_redaction": {
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"operator_conversation_display_allowed": False,
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"agent_private_reasoning_display_allowed": False,
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"raw_prompt_display_allowed": False,
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},
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"approval_boundaries": {
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"runtime_worker_allowed": False,
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"db_migration_allowed": False,
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"redis_consumer_group_allowed": False,
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"telegram_direct_send_allowed": False,
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"conversation_transcript_display_allowed": False,
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"agent_private_reasoning_display_allowed": False,
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"secret_plaintext_allowed": False,
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"autonomous_self_modify_allowed": False,
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},
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"rollups": {
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"proof_level_count": 3,
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"contract_ready_level_count": 3,
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"live_pending_level_ids": [],
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"signal_count": 1,
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"live_signal_count": 0,
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"operator_surface_count": 1,
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"runtime_gate_count": 1,
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"blocked_gate_ids": ["agent_session_read_model_gate"],
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"active_live_agent_sessions": 0,
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"live_agent_messages_24h": 0,
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"live_handoffs_24h": 0,
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"live_learning_writes_24h": 0,
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"telegram_digest_receipts_24h": 0,
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},
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}
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def _proof_level(level_id: str, status: str) -> dict:
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return {
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"level_id": level_id,
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"display_name": level_id,
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"status": status,
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"completion_percent": 100 if status != "live_pending" else 0,
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"operator_meaning": "測試。",
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"source_of_truth": "test",
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"next_gate": "test",
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}
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def _agent_lane(agent_id: str) -> dict:
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return {
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"agent_id": agent_id,
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"display_name": agent_id,
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"primary_role": "測試。",
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"current_visible_state": "contract_visible_live_runtime_pending",
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"visible_signals": ["agent_heartbeat"],
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"growth_metric": "測試。",
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}
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