Implement AI orchestration wedding demo

backend/tests/test_planner_validation_policy.py

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+from datetime import datetime
+
+import pytest
+
+from app.ai.tool_registry import ToolRegistry
+from app.domain.schemas import PlannerDecision, ToolDefinition, TranscriptChunk
+from app.planner.llm_planner import HybridPlanner
+from app.validation.action_validator import ActionValidator
+from app.validation.policy_engine import PolicyEngine
+
+
+@pytest.mark.asyncio
+async def test_fallback_planner_extracts_task():
+    planner = HybridPlanner()
+    chunk = TranscriptChunk(speaker="Bride", timestamp=datetime(2026, 6, 26, 12, 0), text="Create a task for Maria to confirm the photographer.")
+
+    decision = await planner.plan(chunk, {}, [], [])
+
+    assert decision.tool == "create_task"
+    assert decision.extracted_entities["assignee"] == "Maria"
+    assert decision.arguments["is_completed"] is False
+    assert "Suggested owner: Maria" in decision.arguments["description"]
+    assert "photographer" in decision.arguments["title"].lower()
+
+
+def test_validator_rejects_hallucinated_parameters():
+    registry = ToolRegistry(
+        [
+            ToolDefinition(
+                name="create_task",
+                description="Create task",
+                method="POST",
+                path="/tasks",
+                schema={"type": "object", "required": ["title"], "properties": {"title": {"type": "string"}}},
+                required=["title"],
+            )
+        ]
+    )
+    decision = PlannerDecision(
+        intent="create_task",
+        confidence=0.9,
+        reasoning="test",
+        tool="create_task",
+        arguments={"title": "Confirm photographer", "unexpected": True},
+    )
+
+    result = ActionValidator(registry).validate(decision)
+
+    assert not result.valid
+    assert "Hallucinated" in result.errors[0]
+
+
+def test_policy_rejects_low_confidence():
+    decision = PlannerDecision(intent="create_note", confidence=0.2, reasoning="weak", tool="create_note", arguments={"content": "x"})
+
+    result = PolicyEngine().evaluate(decision)
+
+    assert not result.allowed
+    assert "below threshold" in result.reasons[0]