[Frontend] Add /classify endpoint (#17032)

Signed-off-by: Frieda (Jingying) Huang <jingyingfhuang@gmail.com>

tests/entrypoints/openai/test_classification.py

@@ -0,0 +1,156 @@
+# SPDX-License-Identifier: Apache-2.0
+
+import pytest
+import requests
+
+from vllm.entrypoints.openai.protocol import ClassificationResponse
+
+from ...utils import RemoteOpenAIServer
+
+MODEL_NAME = "jason9693/Qwen2.5-1.5B-apeach"
+DTYPE = "float32"  # Use float32 to avoid NaN issue
+
+
+@pytest.fixture(scope="module")
+def server():
+    args = [
+        "--enforce-eager",
+        "--max-model-len",
+        "512",
+        "--dtype",
+        DTYPE,
+    ]
+
+    with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
+        yield remote_server
+
+
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+def test_single_input_classification(server: RemoteOpenAIServer,
+                                     model_name: str):
+    input_text = "This product was excellent and exceeded my expectations"
+
+    classification_response = requests.post(
+        server.url_for("classify"),
+        json={
+            "model": model_name,
+            "input": input_text
+        },
+    )
+
+    classification_response.raise_for_status()
+    output = ClassificationResponse.model_validate(
+        classification_response.json())
+
+    assert output.object == "list"
+    assert output.model == MODEL_NAME
+    assert len(output.data) == 1
+    assert hasattr(output.data[0], "label")
+    assert hasattr(output.data[0], "probs")
+
+
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+def test_multiple_inputs_classification(server: RemoteOpenAIServer,
+                                        model_name: str):
+    input_texts = [
+        "The product arrived on time and works perfectly",
+        "I'm very satisfied with my purchase, would buy again",
+        "The customer service was helpful and resolved my issue quickly",
+        "This product broke after one week, terrible quality",
+        "I'm very disappointed with this purchase, complete waste of money",
+        "The customer service was rude and unhelpful",
+    ]
+
+    classification_response = requests.post(
+        server.url_for("classify"),
+        json={
+            "model": model_name,
+            "input": input_texts
+        },
+    )
+    output = ClassificationResponse.model_validate(
+        classification_response.json())
+
+    assert len(output.data) == len(input_texts)
+    for i, item in enumerate(output.data):
+        assert item.index == i
+        assert hasattr(item, "label")
+        assert hasattr(item, "probs")
+        assert len(item.probs) == item.num_classes
+        assert item.label in ["Default", "Spoiled"]
+
+
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+def test_truncate_prompt_tokens(server: RemoteOpenAIServer, model_name: str):
+    long_text = "hello " * 600
+
+    classification_response = requests.post(
+        server.url_for("classify"),
+        json={
+            "model": model_name,
+            "input": long_text,
+            "truncate_prompt_tokens": 5
+        },
+    )
+
+    classification_response.raise_for_status()
+    output = ClassificationResponse.model_validate(
+        classification_response.json())
+
+    assert len(output.data) == 1
+    assert output.data[0].index == 0
+    assert hasattr(output.data[0], "probs")
+    assert output.usage.prompt_tokens == 5
+    assert output.usage.total_tokens == 5
+
+
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+def test_invalid_truncate_prompt_tokens_error(server: RemoteOpenAIServer,
+                                              model_name: str):
+    classification_response = requests.post(
+        server.url_for("classify"),
+        json={
+            "model": model_name,
+            "input": "test",
+            "truncate_prompt_tokens": 513
+        },
+    )
+
+    error = classification_response.json()
+    assert classification_response.status_code == 400
+    assert error["object"] == "error"
+    assert "truncate_prompt_tokens" in error["message"]
+
+
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+def test_empty_input_error(server: RemoteOpenAIServer, model_name: str):
+    classification_response = requests.post(
+        server.url_for("classify"),
+        json={
+            "model": model_name,
+            "input": ""
+        },
+    )
+
+    error = classification_response.json()
+    assert classification_response.status_code == 400
+    assert error["object"] == "error"
+
+
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+def test_batch_classification_empty_list(server: RemoteOpenAIServer,
+                                         model_name: str):
+    classification_response = requests.post(
+        server.url_for("classify"),
+        json={
+            "model": model_name,
+            "input": []
+        },
+    )
+    classification_response.raise_for_status()
+    output = ClassificationResponse.model_validate(
+        classification_response.json())
+
+    assert output.object == "list"
+    assert isinstance(output.data, list)
+    assert len(output.data) == 0