test(analytics): add PSA metrics endpoint tests — funnel, time entries, daily trend

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

backend/tests/test_analytics_phase5.py

@@ -454,3 +454,227 @@ class TestFlowQualityEndpoint:
         flows = response.json()["flows"]
         usage_counts = [f["usage_count"] for f in flows]
         assert usage_counts == sorted(usage_counts, reverse=True)
+
+
+# ─── PSA metrics endpoint tests ───────────────────────────────────────────────
+
+class TestPsaMetrics:
+    """Tests for GET /api/v1/analytics/flowpilot/psa-metrics."""
+
+    async def test_requires_auth(self, client: AsyncClient, test_db: AsyncSession):
+        """Unauthenticated requests are rejected."""
+        response = await client.get("/api/v1/analytics/flowpilot/psa-metrics")
+        assert response.status_code == 401
+
+    async def test_empty_state(
+        self,
+        client: AsyncClient,
+        test_db: AsyncSession,
+        team_admin_headers: dict,
+    ):
+        """When no PSA activity logs exist, returns zeros gracefully."""
+        response = await client.get(
+            "/api/v1/analytics/flowpilot/psa-metrics",
+            headers=team_admin_headers,
+        )
+        assert response.status_code == 200
+        data = response.json()
+
+        assert data["total_time_entries"] == 0
+        assert data["total_hours_logged"] == 0.0
+        assert data["avg_hours_per_session"] == 0.0
+        assert data["daily_trend"] == []
+
+        funnel = data["push_funnel"]
+        assert funnel["total_sessions"] == 0
+        assert funnel["linked_to_ticket"] == 0
+        assert funnel["doc_pushed"] == 0
+        assert funnel["time_entry_logged"] == 0
+
+    async def test_returns_time_entry_metrics(
+        self,
+        client: AsyncClient,
+        test_db: AsyncSession,
+        team_admin: dict,
+        team_admin_headers: dict,
+    ):
+        """Seeded time_entry_posted logs produce correct totals and averages."""
+        from app.models.psa_activity_log import PsaActivityLog
+
+        account_id = team_admin["user"].account_id
+
+        # 3 time entries: 1.5 + 2.0 + 0.5 = 4.0 hours total, avg = 4.0/3 ≈ 1.33
+        for hours in (1.5, 2.0, 0.5):
+            log = PsaActivityLog(
+                id=uuid.uuid4(),
+                account_id=account_id,
+                activity_type="time_entry_posted",
+                hours_logged=hours,
+            )
+            test_db.add(log)
+        await test_db.commit()
+
+        response = await client.get(
+            "/api/v1/analytics/flowpilot/psa-metrics",
+            headers=team_admin_headers,
+        )
+        assert response.status_code == 200
+        data = response.json()
+
+        assert data["total_time_entries"] == 3
+        assert data["total_hours_logged"] == pytest.approx(4.0, abs=0.01)
+        assert data["avg_hours_per_session"] == pytest.approx(4.0 / 3, abs=0.01)
+
+    async def test_non_time_entry_logs_excluded(
+        self,
+        client: AsyncClient,
+        test_db: AsyncSession,
+        team_admin: dict,
+        team_admin_headers: dict,
+    ):
+        """Activity logs with a different activity_type do not count as time entries."""
+        from app.models.psa_activity_log import PsaActivityLog
+
+        account_id = team_admin["user"].account_id
+
+        # One real time entry, one "note_posted" that should be ignored
+        test_db.add(PsaActivityLog(
+            id=uuid.uuid4(),
+            account_id=account_id,
+            activity_type="time_entry_posted",
+            hours_logged=1.0,
+        ))
+        test_db.add(PsaActivityLog(
+            id=uuid.uuid4(),
+            account_id=account_id,
+            activity_type="note_posted",
+            hours_logged=5.0,
+        ))
+        await test_db.commit()
+
+        response = await client.get(
+            "/api/v1/analytics/flowpilot/psa-metrics",
+            headers=team_admin_headers,
+        )
+        assert response.status_code == 200
+        data = response.json()
+        assert data["total_time_entries"] == 1
+        assert data["total_hours_logged"] == pytest.approx(1.0, abs=0.01)
+
+    async def test_funnel_counts(
+        self,
+        client: AsyncClient,
+        test_db: AsyncSession,
+        team_admin: dict,
+        team_admin_headers: dict,
+    ):
+        """Funnel steps count the correct subset of sessions."""
+        from app.models.ai_session import AISession
+        from app.models.psa_activity_log import PsaActivityLog
+        from app.models.psa_post_log import PsaPostLog
+
+        account_id = team_admin["user"].account_id
+        user_id = team_admin["user"].id
+
+        # 4 total sessions — 2 linked to a ticket
+        session_ids = [uuid.uuid4() for _ in range(4)]
+        for i, sid in enumerate(session_ids):
+            s = AISession(
+                id=sid,
+                user_id=user_id,
+                account_id=account_id,
+                status="resolved",
+                psa_ticket_id="TICKET-123" if i < 2 else None,
+            )
+            test_db.add(s)
+        await test_db.commit()
+
+        # 1 session with a successful doc push
+        push_session_id = session_ids[0]
+        post_log = PsaPostLog(
+            id=uuid.uuid4(),
+            ai_session_id=push_session_id,
+            ticket_id="TICKET-123",
+            note_type="internal",
+            content_posted="Session summary",
+            status="success",
+            posted_by=user_id,
+        )
+        test_db.add(post_log)
+
+        # 1 session with a time entry logged (same session as push for realism)
+        activity_log = PsaActivityLog(
+            id=uuid.uuid4(),
+            account_id=account_id,
+            session_id=push_session_id,
+            activity_type="time_entry_posted",
+            hours_logged=1.0,
+        )
+        test_db.add(activity_log)
+        await test_db.commit()
+
+        response = await client.get(
+            "/api/v1/analytics/flowpilot/psa-metrics",
+            headers=team_admin_headers,
+        )
+        assert response.status_code == 200
+        funnel = response.json()["push_funnel"]
+
+        assert funnel["total_sessions"] == 4
+        assert funnel["linked_to_ticket"] == 2
+        assert funnel["doc_pushed"] == 1
+        assert funnel["time_entry_logged"] == 1
+
+    async def test_daily_trend(
+        self,
+        client: AsyncClient,
+        test_db: AsyncSession,
+        team_admin: dict,
+        team_admin_headers: dict,
+    ):
+        """Time entries grouped by date produce the correct daily trend array."""
+        from app.models.psa_activity_log import PsaActivityLog
+
+        account_id = team_admin["user"].account_id
+        now = datetime.now(timezone.utc)
+
+        # Day -2: 2 entries totalling 3.0 hours
+        # Day -1: 1 entry with 1.5 hours
+        entries = [
+            (now - timedelta(days=2), 1.5),
+            (now - timedelta(days=2), 1.5),
+            (now - timedelta(days=1), 1.5),
+        ]
+        for created_at, hours in entries:
+            log = PsaActivityLog(
+                id=uuid.uuid4(),
+                account_id=account_id,
+                activity_type="time_entry_posted",
+                hours_logged=hours,
+                created_at=created_at,
+            )
+            test_db.add(log)
+        await test_db.commit()
+
+        response = await client.get(
+            "/api/v1/analytics/flowpilot/psa-metrics?period=30d",
+            headers=team_admin_headers,
+        )
+        assert response.status_code == 200
+        trend = response.json()["daily_trend"]
+
+        assert len(trend) == 2
+
+        # Trend is ordered by date ascending
+        dates = [t["date"] for t in trend]
+        assert dates == sorted(dates)
+
+        # Oldest day: 2 entries, 3.0 hours
+        oldest = trend[0]
+        assert oldest["entries"] == 2
+        assert oldest["hours"] == pytest.approx(3.0, abs=0.01)
+
+        # Most recent day: 1 entry, 1.5 hours
+        newest = trend[1]
+        assert newest["entries"] == 1
+        assert newest["hours"] == pytest.approx(1.5, abs=0.01)