[Frontend] Added chat-style multimodal support to /classify. (#27516)

Signed-off-by: WorldExplored <srreyansh.sethi@gmail.com>
Signed-off-by: Srreyansh Sethi <107075589+WorldExplored@users.noreply.github.com>
Signed-off-by: vnadathur <glvikramn@gmail.com>
Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io>
Co-authored-by: vnadathur <236933696+vnadathur@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: vnadathur <glvikramn@gmail.com>
Co-authored-by: wang.yuqi <noooop@126.com>
Co-authored-by: wang.yuqi <yuqi.wang@daocloud.io>

tests/entrypoints/pooling/openai/test_vision_classification.py

@@ -0,0 +1,95 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import json
+
+import pytest
+import requests
+
+from tests.utils import RemoteOpenAIServer
+from vllm.entrypoints.openai.protocol import ClassificationResponse
+
+VLM_MODEL_NAME = "muziyongshixin/Qwen2.5-VL-7B-for-VideoCls"
+MAXIMUM_VIDEOS = 1
+TEST_VIDEO_URL = "https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4"
+
+HF_OVERRIDES = {
+    "text_config": {
+        "architectures": ["Qwen2_5_VLForSequenceClassification"],
+    },
+}
+
+
+@pytest.fixture(scope="module")
+def server_vlm_classify():
+    args = [
+        "--runner",
+        "pooling",
+        "--max-model-len",
+        "5000",
+        "--enforce-eager",
+        "--limit-mm-per-prompt",
+        json.dumps({"video": MAXIMUM_VIDEOS}),
+    ]
+
+    with RemoteOpenAIServer(
+        VLM_MODEL_NAME, args, override_hf_configs=HF_OVERRIDES
+    ) as remote_server:
+        yield remote_server
+
+
+@pytest.mark.parametrize("model_name", [VLM_MODEL_NAME])
+def test_classify_accepts_chat_text_only(
+    server_vlm_classify: RemoteOpenAIServer, model_name: str
+) -> None:
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Please classify this text request."},
+            ],
+        }
+    ]
+
+    response = requests.post(
+        server_vlm_classify.url_for("classify"),
+        json={"model": model_name, "messages": messages},
+    )
+    response.raise_for_status()
+
+    output = ClassificationResponse.model_validate(response.json())
+
+    assert output.object == "list"
+    assert output.model == model_name
+    assert len(output.data) == 1
+    assert len(output.data[0].probs) == 2
+    assert output.usage.prompt_tokens == 22
+
+
+@pytest.mark.parametrize("model_name", [VLM_MODEL_NAME])
+def test_classify_accepts_chat_video_url(
+    server_vlm_classify: RemoteOpenAIServer, model_name: str
+) -> None:
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Please classify this video."},
+                {"type": "video_url", "video_url": {"url": TEST_VIDEO_URL}},
+            ],
+        }
+    ]
+
+    response = requests.post(
+        server_vlm_classify.url_for("classify"),
+        json={"model": model_name, "messages": messages},
+    )
+    response.raise_for_status()
+
+    output = ClassificationResponse.model_validate(response.json())
+
+    assert output.object == "list"
+    assert output.model == model_name
+    assert len(output.data) == 1
+    assert len(output.data[0].probs) == 2
+    assert output.usage.prompt_tokens == 4807