feat(fireworks): service_tier init kwarg on ChatFireworks (#37143)

Add a `service_tier` init kwarg to `ChatFireworks`, mirroring the field
on `ChatOpenAI`. Forwards to the Fireworks chat completions API when
set, and echoes the response's tier back onto `response_metadata` and
`llm_output` so callbacks and consumers can read what the server
actually applied.

libs/partners/fireworks/tests/unit_tests/test_chat_models.py

@@ -974,3 +974,142 @@ class TestStreamUsage:
             "output_tokens": 2,
             "total_tokens": 7,
         }
+
+
+class TestServiceTier:
+    """Tests for the `service_tier` field plumbing."""
+
+    def test_service_tier_omitted_by_default(self) -> None:
+        model = _make_model()
+        assert "service_tier" not in model._default_params
+
+    def test_service_tier_in_default_params_when_set(self) -> None:
+        model = _make_model(service_tier="priority")
+        assert model._default_params["service_tier"] == "priority"
+
+    def test_service_tier_passed_to_client_when_set(self) -> None:
+        model = _make_model(service_tier="priority")
+        model.client = MagicMock()
+        model.client.create.return_value = {
+            "choices": [
+                {
+                    "message": {"role": "assistant", "content": "hi"},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+        }
+        model.invoke("Hello")
+        call_kwargs = model.client.create.call_args[1]
+        assert call_kwargs["service_tier"] == "priority"
+
+    def test_service_tier_not_passed_when_unset(self) -> None:
+        model = _make_model()
+        model.client = MagicMock()
+        model.client.create.return_value = {
+            "choices": [
+                {
+                    "message": {"role": "assistant", "content": "hi"},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+        }
+        model.invoke("Hello")
+        call_kwargs = model.client.create.call_args[1]
+        assert "service_tier" not in call_kwargs
+
+    def test_service_tier_echoed_in_response_metadata(self) -> None:
+        model = _make_model(service_tier="priority")
+        model.client = MagicMock()
+        model.client.create.return_value = {
+            "choices": [
+                {
+                    "message": {"role": "assistant", "content": "hi"},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+            "service_tier": "priority",
+        }
+        result = model.invoke("Hello")
+        assert isinstance(result, AIMessage)
+        assert result.response_metadata["service_tier"] == "priority"
+
+    def test_service_tier_echoed_in_stream_chunks(self) -> None:
+        model = _make_model(service_tier="priority")
+        model.client = MagicMock()
+        chunks: list[dict[str, Any]] = [
+            {
+                "choices": [{"delta": {"role": "assistant", "content": "hi"}}],
+                "service_tier": "priority",
+            },
+            {
+                "choices": [],
+                "usage": {
+                    "prompt_tokens": 1,
+                    "completion_tokens": 1,
+                    "total_tokens": 2,
+                },
+                "service_tier": "priority",
+            },
+        ]
+        model.client.create.return_value = iter(chunks)
+        out = list(model.stream("Hello"))
+        tagged = [c for c in out if c.response_metadata.get("service_tier")]
+        assert tagged
+        assert all(c.response_metadata["service_tier"] == "priority" for c in tagged)
+
+    def test_service_tier_absent_when_not_in_response(self) -> None:
+        model = _make_model()
+        model.client = MagicMock()
+        model.client.create.return_value = {
+            "choices": [
+                {
+                    "message": {"role": "assistant", "content": "hi"},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+        }
+        result = model.invoke("Hello")
+        assert isinstance(result, AIMessage)
+        assert "service_tier" not in result.response_metadata
+
+    def test_service_tier_in_llm_output_when_response_carries_it(self) -> None:
+        model = _make_model(service_tier="priority")
+        chat_result = model._create_chat_result(
+            {
+                "choices": [
+                    {
+                        "message": {"role": "assistant", "content": "hi"},
+                        "finish_reason": "stop",
+                    }
+                ],
+                "usage": {
+                    "prompt_tokens": 1,
+                    "completion_tokens": 1,
+                    "total_tokens": 2,
+                },
+                "service_tier": "priority",
+            }
+        )
+        assert chat_result.llm_output is not None
+        assert chat_result.llm_output["service_tier"] == "priority"
+
+    def test_service_tier_not_inferred_from_request(self) -> None:
+        """Init-set tier must not leak into response_metadata if API omits it."""
+        model = _make_model(service_tier="priority")
+        model.client = MagicMock()
+        model.client.create.return_value = {
+            "choices": [
+                {
+                    "message": {"role": "assistant", "content": "hi"},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+        }
+        result = model.invoke("Hello")
+        assert isinstance(result, AIMessage)
+        assert "service_tier" not in result.response_metadata