Files
detections/e2e/tests/test_health_engine.py
T
Oleksandr Bezdieniezhnykh 8baa96978b [AZ-180] Refactor detection event handling and improve SSE support
- Updated the detection image endpoint to require a channel ID for event streaming.
- Introduced a new endpoint for streaming detection events, allowing clients to receive real-time updates.
- Enhanced the internal buffering mechanism for detection events to manage multiple channels.
- Refactored the inference module to support the new event handling structure.

Made-with: Cursor
2026-04-03 02:42:05 +03:00

154 lines
5.0 KiB
Python

import json
import threading
import time
import uuid
import pytest
import sseclient
_DETECT_TIMEOUT = 60
def _get_health(http_client):
r = http_client.get("/health")
r.raise_for_status()
return r.json()
def _assert_active_ai(data):
assert data["status"] == "healthy"
assert data["aiAvailability"] not in ("None", "Downloading")
@pytest.mark.cpu
class TestHealthEngineStep01PreInit:
def test_ft_p_01_pre_init_health(self, http_client):
t0 = time.monotonic()
data = _get_health(http_client)
assert time.monotonic() - t0 < 2.0
assert data["status"] == "healthy"
assert data["aiAvailability"] == "None", (
f"engine already initialized (aiAvailability={data['aiAvailability']}); "
"pre-init tests must run before any test that triggers warm_engine"
)
assert data.get("errorMessage") is None
@pytest.mark.cpu
@pytest.mark.slow
class TestHealthEngineStep02LazyInit:
def test_ft_p_14_lazy_initialization(self, http_client, image_small, auth_headers):
before = _get_health(http_client)
assert before["aiAvailability"] == "None", (
f"engine already initialized (aiAvailability={before['aiAvailability']}); "
"lazy-init test must run before any test that triggers warm_engine"
)
cid = str(uuid.uuid4())
headers = {**auth_headers, "X-Channel-Id": cid}
done = threading.Event()
connected = threading.Event()
def _listen():
try:
with http_client.get(
f"/detect/events/{cid}",
stream=True,
timeout=_DETECT_TIMEOUT + 2,
headers=auth_headers,
) as resp:
resp.raise_for_status()
connected.set()
for ev in sseclient.SSEClient(resp).events():
if not ev.data or not str(ev.data).strip():
continue
data = json.loads(ev.data)
if data.get("mediaStatus") in ("AIProcessed", "Error"):
break
except Exception:
pass
finally:
connected.set()
done.set()
th = threading.Thread(target=_listen, daemon=True)
th.start()
connected.wait(timeout=5)
files = {"file": ("lazy.jpg", image_small, "image/jpeg")}
r = http_client.post("/detect/image", files=files, headers=headers, timeout=_DETECT_TIMEOUT)
assert r.status_code == 202
done.wait(timeout=_DETECT_TIMEOUT)
th.join(timeout=2)
after = _get_health(http_client)
_assert_active_ai(after)
@pytest.mark.cpu
@pytest.mark.slow
class TestHealthEngineStep03Warmed:
@pytest.fixture(autouse=True)
def _warm(self, warm_engine):
pass
def test_ft_p_02_post_init_health(self, http_client):
data = _get_health(http_client)
_assert_active_ai(data)
assert data.get("errorMessage") is None
def test_ft_p_15_onnx_cpu_detect(self, http_client, image_small, auth_headers):
cid = str(uuid.uuid4())
headers = {**auth_headers, "X-Channel-Id": cid}
all_detections = []
done = threading.Event()
connected = threading.Event()
def _listen():
try:
with http_client.get(
f"/detect/events/{cid}",
stream=True,
timeout=_DETECT_TIMEOUT + 2,
headers=auth_headers,
) as resp:
resp.raise_for_status()
connected.set()
for ev in sseclient.SSEClient(resp).events():
if not ev.data or not str(ev.data).strip():
continue
data = json.loads(ev.data)
if data.get("mediaStatus") == "AIProcessing":
all_detections.extend(data.get("annotations", []))
if data.get("mediaStatus") in ("AIProcessed", "Error"):
break
except Exception:
pass
finally:
connected.set()
done.set()
th = threading.Thread(target=_listen, daemon=True)
th.start()
connected.wait(timeout=5)
files = {"file": ("onnx.jpg", image_small, "image/jpeg")}
r = http_client.post("/detect/image", files=files, headers=headers, timeout=_DETECT_TIMEOUT)
r.raise_for_status()
assert r.status_code == 202
done.wait(timeout=_DETECT_TIMEOUT)
th.join(timeout=2)
if all_detections:
d = all_detections[0]
for k in (
"centerX",
"centerY",
"width",
"height",
"classNum",
"label",
"confidence",
):
assert k in d