ocr-service/test_metrics.py

@@ -390,6 +390,52 @@ async def test_ocr_training_runs_total_incremented_with_segmentation_success_lab
     )._value.get() == 1.0
 
 
+@pytest.mark.asyncio
+async def test_ocr_training_runs_total_incremented_with_recognition_success_label_for_train_sender(fresh_metrics):
+    """/train-sender success increments ocr_training_runs_total{kind=recognition, outcome=success}."""
+    async def fake_to_thread(func, *args, **kwargs):
+        return _fake_training_result()
+
+    with patch("main.TRAINING_TOKEN", "secret-token"), \
+         patch("main._models_ready", True), \
+         patch("main.asyncio.to_thread", side_effect=fake_to_thread):
+        async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+            response = await client.post(
+                "/train-sender",
+                files={"file": ("training.zip", _minimal_zip(), "application/zip")},
+                data={"output_model_path": "/app/models/sender_test.mlmodel"},
+                headers={"X-Training-Token": "secret-token"},
+            )
+
+    assert response.status_code == 200, response.text
+    assert fresh_metrics.ocr_training_runs_total.labels(
+        kind="recognition", outcome="success"
+    )._value.get() == 1.0
+
+
+@pytest.mark.asyncio
+async def test_ocr_model_accuracy_gauge_stays_default_when_training_returns_no_accuracy(fresh_metrics):
+    """When the runner returns accuracy=None, ocr_model_accuracy must remain at its default 0."""
+    async def fake_to_thread(func, *args, **kwargs):
+        return {"loss": None, "accuracy": None, "cer": None, "epochs": 5}
+
+    with patch("main.TRAINING_TOKEN", "secret-token"), \
+         patch("main._models_ready", True), \
+         patch("main.asyncio.to_thread", side_effect=fake_to_thread):
+        async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+            response = await client.post(
+                "/train",
+                files={"file": ("training.zip", _minimal_zip(), "application/zip")},
+                headers={"X-Training-Token": "secret-token"},
+            )
+
+    assert response.status_code == 200
+    # Gauge was never .set() — accessing the label child still creates it with default 0.0.
+    assert fresh_metrics.ocr_model_accuracy.labels(
+        kind="recognition"
+    )._value.get() == 0.0
+
+
 @pytest.mark.asyncio
 async def test_ocr_model_accuracy_gauge_set_per_kind_after_successful_training(fresh_metrics):
     """After /train and /segtrain succeed, ocr_model_accuracy{kind=...} reflects the result."""