Score API

Signed-off-by: wang.yuqi <noooop@126.com>

Author: noooop

tests/conftest.py

@@ -454,11 +454,10 @@ def classify(self, prompts: list[str]) -> list[str]:
         # output is final logits
         all_inputs = self.get_inputs(prompts)
         outputs = []
+        problem_type = getattr(self.config, "problem_type", "")
+
         for inputs in all_inputs:
             output = self.model(**self.wrap_device(inputs))
-
-            problem_type = getattr(self.config, "problem_type", "")
-
             if problem_type == "regression":
                 logits = output.logits[0].tolist()
             elif problem_type == "multi_label_classification":

tests/entrypoints/openai/test_classification.py

@@ -226,3 +226,33 @@ def test_pooling(server: RemoteOpenAIServer, model_name: str):
         },
     )
     assert response.json()["error"]["type"] == "BadRequestError"
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+def test_score(server: RemoteOpenAIServer, model_name: str):
+    # score api is only enabled for num_labels == 1.
+    response = requests.post(
+        server.url_for("score"),
+        json={
+            "model": model_name,
+            "text_1": "ping",
+            "text_2": "pong",
+        },
+    )
+    assert response.json()["error"]["type"] == "BadRequestError"
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+def test_rerank(server: RemoteOpenAIServer, model_name: str):
+    # rerank api is only enabled for num_labels == 1.
+    response = requests.post(
+        server.url_for("rerank"),
+        json={
+            "model": model_name,
+            "query": "ping",
+            "documents": ["pong"],
+        },
+    )
+    assert response.json()["error"]["type"] == "BadRequestError"

vllm/entrypoints/openai/api_server.py

@@ -1797,16 +1797,12 @@ async def init_app_state(
         state.openai_serving_models,
         request_logger=request_logger,
     ) if "classify" in supported_tasks else None
-
-    enable_serving_reranking = ("classify" in supported_tasks and getattr(
-        model_config.hf_config, "num_labels", 0) == 1)
     state.openai_serving_scores = ServingScores(
         engine_client,
         model_config,
         state.openai_serving_models,
         request_logger=request_logger,
-    ) if ("embed" in supported_tasks or enable_serving_reranking) else None
-
+    ) if ("embed" in supported_tasks or "score" in supported_tasks) else None
     state.openai_serving_tokenization = OpenAIServingTokenization(
         engine_client,
         model_config,

vllm/v1/worker/gpu_model_runner.py

@@ -1302,6 +1302,13 @@ def get_supported_pooling_tasks(self) -> list[PoolingTask]:
                              "Please turn off chunked prefill by "
                              "`--no-enable-chunked-prefill` before using it.")
 
+        if "score" in supported_tasks:
+            num_labels = getattr(
+                self.model_config.hf_config, "num_labels", 0)
+            if num_labels != 1:
+                supported_tasks.remove("score")
+                logger.info_once("Score API is only enabled for num_labels == 1.")
+
         return supported_tasks
 
     def get_supported_tasks(self) -> tuple[SupportedTask, ...]: