chore: import upstream snapshot with attribution

python/sglang/multimodal_gen/test/server/test_request_logger.py

@@ -0,0 +1,233 @@
+"""
+Test request logging for diffusion models.
+
+Tests the --log-requests CLI flags for diffusion model serving,
+verifying that request logs are correctly written to stdout and files.
+"""
+
+import json
+import os
+import shutil
+import tempfile
+import time
+from pathlib import Path
+
+import pytest
+from openai import OpenAI
+
+from sglang.multimodal_gen.test.server.test_server_utils import ServerManager
+from sglang.multimodal_gen.test.test_utils import get_dynamic_server_port
+
+# Test models and prompts
+IMAGE_MODEL = "Efficient-Large-Model/Sana_600M_512px_diffusers"
+IMAGE_PROMPT = "A beautiful sunset over mountains, oil painting style"
+VIDEO_MODEL = "Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
+VIDEO_PROMPT = "A cat playing with a ball"
+
+# Timeout settings
+BASE_TIMEOUT = float(os.environ.get("SGLANG_TEST_OPENAI_REQUEST_TIMEOUT_SECS", "600"))
+POLL_INTERVAL = 1.0
+
+
+def _start_server(model: str, log_format: str):
+    """Start server with request logging enabled."""
+    temp_dir = tempfile.mkdtemp()
+    port = get_dynamic_server_port()
+    extra_args = (
+        f"--log-requests "
+        f"--log-requests-level 2 "
+        f"--log-requests-format {log_format} "
+        f"--log-requests-target stdout {temp_dir} "
+        f"--strict-ports"
+    )
+    wait_deadline = float(os.environ.get("SGLANG_TEST_WAIT_SECS", "1200"))
+    manager = ServerManager(
+        model=model,
+        port=port,
+        wait_deadline=wait_deadline,
+        extra_args=extra_args,
+    )
+    ctx = manager.start()
+    ctx.temp_dir = temp_dir
+    return ctx
+
+
+def _cleanup_server(ctx):
+    """Cleanup server and temp directory."""
+    ctx.cleanup()
+    shutil.rmtree(ctx.temp_dir, ignore_errors=True)
+
+
+def _create_client(ctx) -> OpenAI:
+    """Create OpenAI client for the server."""
+    return OpenAI(
+        api_key="test",
+        base_url=f"http://localhost:{ctx.port}/v1",
+        timeout=BASE_TIMEOUT,
+    )
+
+
+def _wait_for_video_completion(client: OpenAI, video_id: str, timeout: float):
+    """Poll video job until completion."""
+    deadline = time.time() + timeout
+    while time.time() < deadline:
+        page = client.videos.list()
+        item = next((v for v in page.data if v.id == video_id), None)
+        status = getattr(item, "status", None) if item else None
+
+        if status == "completed":
+            return True
+        if status in ("failed", "cancelled", "deleted"):
+            pytest.fail(f"Video job {video_id} ended with status={status}")
+
+        time.sleep(POLL_INTERVAL)
+
+    pytest.fail(f"Video job {video_id} did not complete in {timeout}s")
+
+
+def _verify_json_logs(content: str):
+    """Verify JSON logs contain request.received and request.finished events."""
+    has_received = False
+    has_finished = False
+
+    for line in content.splitlines():
+        idx = line.find("{")
+        if idx == -1:
+            continue
+        try:
+            data = json.loads(line[idx:])
+        except json.JSONDecodeError:
+            continue
+
+        if data.get("event") == "request.received":
+            has_received = True
+        elif data.get("event") == "request.finished":
+            has_finished = True
+
+    assert has_received, "request.received event not found"
+    assert has_finished, "request.finished event not found"
+
+
+def _verify_text_logs(content: str, prompt: str):
+    """Verify text logs contain Receive, prompt, and Finish markers."""
+    assert "Receive:" in content, "'Receive:' not found"
+    assert prompt in content, f"Prompt '{prompt}' not found"
+    assert "Finish:" in content, "'Finish:' not found"
+
+
+@pytest.fixture(scope="class")
+def image_text_server():
+    """Server with text-format logging for image model."""
+    ctx = _start_server(IMAGE_MODEL, "text")
+    yield ctx
+    _cleanup_server(ctx)
+
+
+@pytest.fixture(scope="class")
+def image_json_server():
+    """Server with JSON-format logging for image model."""
+    ctx = _start_server(IMAGE_MODEL, "json")
+    yield ctx
+    _cleanup_server(ctx)
+
+
+@pytest.fixture(scope="class")
+def video_text_server():
+    """Server with text-format logging for video model."""
+    ctx = _start_server(VIDEO_MODEL, "text")
+    yield ctx
+    _cleanup_server(ctx)
+
+
+@pytest.fixture(scope="class")
+def video_json_server():
+    """Server with JSON-format logging for video model."""
+    ctx = _start_server(VIDEO_MODEL, "json")
+    yield ctx
+    _cleanup_server(ctx)
+
+
+class TestImageRequestLoggerText:
+    """Test text-format request logging for image models."""
+
+    def test_request_logging(self, image_text_server):
+        ctx = image_text_server
+        client = _create_client(ctx)
+
+        # Image generation is synchronous, waits for completion
+        client.images.generate(prompt=IMAGE_PROMPT, size="256x256", n=1)
+
+        # Verify stdout and file logs
+        stdout = ctx.log_tail(lines=500)
+        _verify_text_logs(stdout, IMAGE_PROMPT[:30])
+
+        logs = list(Path(ctx.temp_dir).glob("*.log"))
+        assert logs, "No log files found"
+        _verify_text_logs("".join(f.read_text() for f in logs), IMAGE_PROMPT[:30])
+
+
+class TestImageRequestLoggerJson:
+    """Test JSON-format request logging for image models."""
+
+    def test_request_logging(self, image_json_server):
+        ctx = image_json_server
+        client = _create_client(ctx)
+
+        # Image generation is synchronous, waits for completion
+        client.images.generate(prompt=IMAGE_PROMPT, size="256x256", n=1)
+
+        # Verify stdout and file logs
+        stdout = ctx.log_tail(lines=500)
+        _verify_json_logs(stdout)
+
+        logs = list(Path(ctx.temp_dir).glob("*.log"))
+        assert logs, "No log files found"
+        _verify_json_logs("".join(f.read_text() for f in logs))
+
+
+class TestVideoRequestLoggerText:
+    """Test text-format request logging for video models."""
+
+    def test_request_logging(self, video_text_server):
+        ctx = video_text_server
+        client = _create_client(ctx)
+
+        # Video generation is async - create job and poll until completion
+        job = client.videos.create(
+            prompt=VIDEO_PROMPT,
+            size="832x480",
+            extra_body={"num_frames": 5, "num_inference_steps": 10},
+        )
+        _wait_for_video_completion(client, job.id, BASE_TIMEOUT * 2)
+
+        # Verify stdout and file logs
+        stdout = ctx.log_tail(lines=500)
+        _verify_text_logs(stdout, VIDEO_PROMPT[:20])
+
+        logs = list(Path(ctx.temp_dir).glob("*.log"))
+        assert logs, "No log files found"
+        _verify_text_logs("".join(f.read_text() for f in logs), VIDEO_PROMPT[:20])
+
+
+class TestVideoRequestLoggerJson:
+    """Test JSON-format request logging for video models."""
+
+    def test_request_logging(self, video_json_server):
+        ctx = video_json_server
+        client = _create_client(ctx)
+
+        # Video generation is async - create job and poll until completion
+        job = client.videos.create(
+            prompt=VIDEO_PROMPT,
+            size="832x480",
+            extra_body={"num_frames": 5, "num_inference_steps": 10},
+        )
+        _wait_for_video_completion(client, job.id, BASE_TIMEOUT * 2)
+
+        # Verify stdout and file logs
+        stdout = ctx.log_tail(lines=500)
+        _verify_json_logs(stdout)
+
+        logs = list(Path(ctx.temp_dir).glob("*.log"))
+        assert logs, "No log files found"
+        _verify_json_logs("".join(f.read_text() for f in logs))