server: add OpenAI-compatible /v1/responses endpoint

tests/test_chat_template_kwargs.py

@@ -0,0 +1,165 @@
+# SPDX-License-Identifier: Apache-2.0
+"""Focused regressions for chat_template_kwargs forwarding."""
+
+from types import SimpleNamespace
+from unittest.mock import MagicMock, patch
+
+import pytest
+from fastapi.testclient import TestClient
+
+import vllm_mlx.server as srv
+from vllm_mlx.engine.base import GenerationOutput
+
+
+@pytest.fixture
+def anyio_backend():
+    return "asyncio"
+
+
+def test_chat_completion_request_preserves_chat_template_kwargs():
+    request = srv.ChatCompletionRequest(
+        model="test-model",
+        messages=[srv.Message(role="user", content="Hello")],
+        chat_template_kwargs={"enable_thinking": False},
+    )
+
+    assert request.chat_template_kwargs == {"enable_thinking": False}
+
+
+def test_chat_completion_endpoint_forwards_chat_template_kwargs():
+    captured = {}
+
+    class FakeEngine:
+        model_name = "test-model"
+        is_mllm = False
+        preserve_native_tool_format = False
+
+        async def chat(self, messages, **kwargs):
+            captured["messages"] = messages
+            captured["kwargs"] = kwargs
+            return GenerationOutput(
+                text="ORBIT",
+                prompt_tokens=4,
+                completion_tokens=1,
+                finish_reason="stop",
+            )
+
+    client = TestClient(srv.app)
+    original_engine = srv._engine
+    original_model_name = srv._model_name
+    srv._engine = FakeEngine()
+    srv._model_name = "test-model"
+    try:
+        response = client.post(
+            "/v1/chat/completions",
+            json={
+                "model": "test-model",
+                "messages": [{"role": "user", "content": "Reply with ORBIT."}],
+                "max_tokens": 8,
+                "chat_template_kwargs": {"enable_thinking": False},
+            },
+        )
+    finally:
+        srv._engine = original_engine
+        srv._model_name = original_model_name
+
+    assert response.status_code == 200
+    assert captured["kwargs"]["chat_template_kwargs"] == {"enable_thinking": False}
+    assert response.json()["choices"][0]["message"]["content"] == "ORBIT"
+
+
+def test_llm_chat_applies_chat_template_kwargs_before_generate():
+    from vllm_mlx.models.llm import MLXLanguageModel
+
+    model = MLXLanguageModel.__new__(MLXLanguageModel)
+    model._loaded = True
+    model.tokenizer = MagicMock()
+    model.tokenizer.apply_chat_template.return_value = "prompt"
+    model.generate = MagicMock(return_value="ok")
+
+    result = model.chat(
+        [{"role": "user", "content": "Hello"}],
+        chat_template_kwargs={"enable_thinking": False},
+    )
+
+    assert result == "ok"
+    model.tokenizer.apply_chat_template.assert_called_once()
+    assert (
+        model.tokenizer.apply_chat_template.call_args.kwargs["enable_thinking"] is False
+    )
+    model.generate.assert_called_once()
+
+
+@pytest.mark.anyio
+async def test_simple_engine_llm_chat_forwards_chat_template_kwargs():
+    from vllm_mlx.engine.simple import SimpleEngine
+
+    with patch("vllm_mlx.engine.simple.is_mllm_model", return_value=False):
+        engine = SimpleEngine("test-model")
+        engine._loaded = True
+        engine._is_mllm = False
+        engine._model = MagicMock()
+        engine._model.chat = MagicMock(
+            return_value=SimpleNamespace(
+                text="OK",
+                tokens=[1],
+                finish_reason="stop",
+            )
+        )
+
+        await engine.chat(
+            [{"role": "user", "content": "Hello"}],
+            chat_template_kwargs={"enable_thinking": False},
+        )
+
+        assert engine._model.chat.call_args.kwargs["chat_template_kwargs"] == {
+            "enable_thinking": False
+        }
+
+
+@pytest.mark.anyio
+async def test_simple_engine_tool_fallback_preserves_stream_state_and_kwargs():
+    from vllm_mlx.engine.simple import SimpleEngine
+
+    captured = {}
+
+    async def fake_stream_chat(*args, **kwargs):
+        captured["kwargs"] = kwargs
+        yield SimpleNamespace(
+            text="partial",
+            tokens=[7],
+            prompt_tokens=11,
+            completion_tokens=1,
+            finish_reason=None,
+            finished=False,
+        )
+        yield SimpleNamespace(
+            text="<|im_end|><tool_call>{\"name\":\"bash\",\"arguments\":{\"command\":\"pwd\"}}</tool_call>",
+            tokens=[7, 8],
+            prompt_tokens=11,
+            completion_tokens=4,
+            finish_reason="stop",
+            finished=True,
+        )
+
+    with patch("vllm_mlx.engine.simple.is_mllm_model", return_value=False):
+        engine = SimpleEngine("test-model")
+        engine._loaded = True
+        engine._is_mllm = False
+        engine._model = MagicMock()
+        engine._model.tokenizer.encode = MagicMock(return_value=[99])
+        engine.stream_chat = fake_stream_chat  # type: ignore[method-assign]
+
+        output = await engine.chat(
+            [{"role": "user", "content": "Hello"}],
+            tools=[{"type": "function", "function": {"name": "bash"}}],
+            chat_template_kwargs={"enable_thinking": False},
+        )
+
+        assert captured["kwargs"]["chat_template_kwargs"] == {
+            "enable_thinking": False
+        }
+        assert output.tokens == [7, 8]
+        assert output.prompt_tokens == 11
+        assert output.completion_tokens == 4
+        assert output.finish_reason == "stop"