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- Auto-fix 155 errors (import sorting, annotations, deprecated imports) - Format 87 files with ruff format for line length compliance - Fix 15 F401 unused imports (add __all__ for re-exports, remove truly unused) - Fix 7 F841 unused variables (prefix with _) - Fix 2 F821 undefined names (add missing imports) - Fix 3 E402 module-level imports not at top - Fix 2 UP042 str+Enum → StrEnum - Fix 1 E712 == False comparison - Fix remaining 51 E501 line-too-long in string literals and expressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
239 lines
8.7 KiB
Python
239 lines
8.7 KiB
Python
# test_e2e_decision_loop.py — E2E: Fabric objects → Instinct pipeline → Audit export.
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# Created: 2026-03-28
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# Tests the full decision loop without any HTTP calls:
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# define object type → create objects → detect low stock (threshold check)
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# → propose actions → approve/reject → audit trail → JSON export.
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"""E2E test: The full decision loop.
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Fabric objects → agent queries → proposes action → approves → audit logged.
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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import pytest
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from ee.fabric.models import FabricQuery, PropertyDef
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from ee.fabric.store import FabricStore
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from ee.instinct.models import ActionTrigger
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from ee.instinct.store import InstinctStore
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _agent_trigger(reason: str = "Low stock detected") -> ActionTrigger:
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return ActionTrigger(type="agent", source="pocketpaw", reason=reason)
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async def _evaluate_threshold(
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store: FabricStore, type_name: str, property_name: str, operator: str, threshold: float
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) -> list:
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"""Evaluate a threshold rule against Fabric objects — inline evaluator.
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Replaces the not-yet-implemented ee/automations evaluator. Returns a list
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of FabricObject instances that satisfy the rule.
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"""
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result = await store.query(FabricQuery(type_name=type_name))
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fired = []
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for obj in result.objects:
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val = obj.properties.get(property_name)
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if val is None:
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continue
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try:
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val = float(val)
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except (TypeError, ValueError):
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continue
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match = False
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if operator == "lt" and val < threshold:
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match = True
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elif operator == "lte" and val <= threshold:
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match = True
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elif operator == "gt" and val > threshold:
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match = True
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elif operator == "gte" and val >= threshold:
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match = True
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elif operator == "eq" and val == threshold:
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match = True
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if match:
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fired.append(obj)
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return fired
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# ---------------------------------------------------------------------------
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# Test
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# ---------------------------------------------------------------------------
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@pytest.mark.asyncio
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async def test_full_decision_loop(tmp_path: Path) -> None:
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"""Step-by-step decision loop: Fabric → threshold rule → Instinct → audit export."""
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fabric = FabricStore(tmp_path / "fabric.db")
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instinct = InstinctStore(tmp_path / "instinct.db")
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# --- Step 1: Define object type with properties ---
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inv_type = await fabric.define_type(
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name="Inventory",
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properties=[
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PropertyDef(name="name", type="string", required=True),
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PropertyDef(name="quantity", type="number", required=True),
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],
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icon="box",
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color="#FF6B35",
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)
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assert inv_type.id.startswith("ot-")
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assert inv_type.name == "Inventory"
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assert len(inv_type.properties) == 2
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# --- Step 2: Create 3 inventory objects ---
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_oat_milk = await fabric.create_object(inv_type.id, {"name": "Oat Milk", "quantity": 4})
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_coffee = await fabric.create_object(inv_type.id, {"name": "Coffee Beans", "quantity": 50})
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_cups = await fabric.create_object(inv_type.id, {"name": "Cups", "quantity": 200})
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all_inv = await fabric.query(FabricQuery(type_name="Inventory"))
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assert all_inv.total == 3
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# --- Step 3: Query for low stock (qty < 10) ---
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low_stock = await _evaluate_threshold(fabric, "Inventory", "quantity", "lt", 10)
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# Only Oat Milk (qty=4) triggers; Coffee (50) and Cups (200) don't.
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assert len(low_stock) == 1
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assert low_stock[0].properties["name"] == "Oat Milk"
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# --- Step 4: Propose an Instinct action for each triggered object ---
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proposed_actions = []
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for obj in low_stock:
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qty = obj.properties["quantity"]
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action = await instinct.propose(
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pocket_id="store-hq",
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title=f"Reorder {obj.properties['name']}",
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description=f"Stock at {qty} units (threshold: 10)",
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recommendation=f"Order 20 units of {obj.properties['name']}",
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trigger=_agent_trigger(f"Quantity {qty} < 10"),
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)
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proposed_actions.append(action)
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# --- Step 5: Verify pending actions exist ---
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pending = await instinct.pending()
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assert len(pending) == len(proposed_actions)
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for action in pending:
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assert action.status.value == "pending"
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# We also need a second action to reject — propose one more
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second_action = await instinct.propose(
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pocket_id="store-hq",
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title="Deep-clean espresso machine",
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description="Scheduled maintenance",
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recommendation="Run descaling cycle",
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trigger=_agent_trigger("Scheduled maintenance"),
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)
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assert second_action.status.value == "pending"
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# --- Step 6: Approve one, reject one ---
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approved = await instinct.approve(proposed_actions[0].id, "user:owner")
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assert approved is not None
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assert approved.status.value == "approved"
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assert approved.approved_by == "user:owner"
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rejected = await instinct.reject(second_action.id, "Not urgent right now")
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assert rejected is not None
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assert rejected.status.value == "rejected"
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assert rejected.rejected_reason == "Not urgent right now"
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# --- Step 7: Verify audit log has all expected events ---
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audit_entries = await instinct.query_audit(pocket_id="store-hq")
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events = [e.event for e in audit_entries]
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assert "action_proposed" in events, "Expected action_proposed in audit"
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assert "action_approved" in events, "Expected action_approved in audit"
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assert "action_rejected" in events, "Expected action_rejected in audit"
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# --- Step 8: Mark approved action as executed ---
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executed = await instinct.mark_executed(approved.id, "Order placed with SupplierCo")
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assert executed is not None
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assert executed.status.value == "executed"
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assert executed.outcome == "Order placed with SupplierCo"
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# --- Step 9: Export audit as JSON and verify completeness ---
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audit_json = await instinct.export_audit("store-hq")
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parsed = json.loads(audit_json)
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exported_events = [e["event"] for e in parsed]
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assert "action_proposed" in exported_events
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assert "action_approved" in exported_events
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assert "action_rejected" in exported_events
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assert "action_executed" in exported_events
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# Confirm structure — every entry has required fields
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for entry in parsed:
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assert "id" in entry
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assert "actor" in entry
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assert "event" in entry
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assert "description" in entry
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assert "timestamp" in entry
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@pytest.mark.asyncio
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async def test_multiple_low_stock_items_all_get_actions(tmp_path: Path) -> None:
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"""When multiple items breach the threshold, all of them get proposed actions."""
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fabric = FabricStore(tmp_path / "fabric.db")
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instinct = InstinctStore(tmp_path / "instinct.db")
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inv_type = await fabric.define_type(
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name="Inventory",
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properties=[
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PropertyDef(name="name", type="string"),
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PropertyDef(name="quantity", type="number"),
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],
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)
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# Three items below threshold, one above
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items = [
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{"name": "Milk", "quantity": 2},
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{"name": "Sugar", "quantity": 5},
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{"name": "Salt", "quantity": 8},
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{"name": "Coffee", "quantity": 100},
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]
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for props in items:
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await fabric.create_object(inv_type.id, props)
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low_stock = await _evaluate_threshold(fabric, "Inventory", "quantity", "lt", 10)
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assert len(low_stock) == 3 # Milk, Sugar, Salt
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names = {obj.properties["name"] for obj in low_stock}
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assert names == {"Milk", "Sugar", "Salt"}
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# Propose actions for all
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for obj in low_stock:
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await instinct.propose(
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pocket_id="store-hq",
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title=f"Reorder {obj.properties['name']}",
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description="Low stock",
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recommendation="Order 20 units",
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trigger=_agent_trigger(),
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)
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pending_count = await instinct.pending_count()
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assert pending_count == 3
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@pytest.mark.asyncio
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async def test_approved_action_audit_contains_approver(tmp_path: Path) -> None:
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"""Audit trail captures who approved the action."""
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instinct = InstinctStore(tmp_path / "instinct.db")
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action = await instinct.propose(
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pocket_id="p1",
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title="Test approval tracking",
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description="",
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recommendation="Do something",
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trigger=ActionTrigger(type="agent", source="pocketpaw", reason="test"),
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)
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await instinct.approve(action.id, "user:jane")
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entries = await instinct.query_audit(pocket_id="p1", event="action_approved")
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assert len(entries) == 1
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assert entries[0].actor == "user:jane"
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