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/langchain_fireworks/chat_models.py

@@ -321,6 +321,9 @@ def _convert_chunk_to_message_chunk(
     chunk: Mapping[str, Any], default_class: type[BaseMessageChunk]
 ) -> BaseMessageChunk:
     choices = chunk.get("choices") or []
+    response_metadata: dict[str, Any] = {"model_provider": "fireworks"}
+    if service_tier := chunk.get("service_tier"):
+        response_metadata["service_tier"] = service_tier
     if not choices:
         # Final chunk emitted when `stream_options.include_usage=True`:
         # `choices` is empty and the chunk carries only `usage`.
@@ -333,7 +336,7 @@ def _convert_chunk_to_message_chunk(
         return AIMessageChunk(
             content="",
             usage_metadata=usage_metadata,  # type: ignore[arg-type]
-            response_metadata={"model_provider": "fireworks"},
+            response_metadata=response_metadata,
         )
     choice = choices[0]
     _dict = choice["delta"]
@@ -368,7 +371,7 @@ def _convert_chunk_to_message_chunk(
             additional_kwargs=additional_kwargs,
             tool_call_chunks=tool_call_chunks,
             usage_metadata=usage_metadata,  # type: ignore[arg-type]
-            response_metadata={"model_provider": "fireworks"},
+            response_metadata=response_metadata,
         )
     if role == "system" or default_class == SystemMessageChunk:
         return SystemMessageChunk(content=content)
@@ -647,6 +650,21 @@ class ChatFireworks(BaseChatModel):
     A value of `None` or `0` disables retries.
     """
 
+    service_tier: str | None = None
+    """Service tier for the request.
+
+    Forwarded as the `service_tier` field on the Fireworks chat completions
+    request when set. Pass `'priority'` to opt into Fireworks' priority tier;
+    leave as `None` to use the default tier.
+
+    To use Fireworks' fast mode instead, select a fast-routed `model`; fast mode
+    is not controlled by this field. See Fireworks'
+    [serverless product docs](https://docs.fireworks.ai/guides/serverless-products)
+    for the current list of fast routers and tiers.
+
+    !!! version-added "Added in `langchain-fireworks` 1.3.0"
+    """
+
     model_config = ConfigDict(
         populate_by_name=True,
     )
@@ -701,6 +719,8 @@ class ChatFireworks(BaseChatModel):
             params["temperature"] = self.temperature
         if self.max_tokens is not None:
             params["max_tokens"] = self.max_tokens
+        if self.service_tier is not None:
+            params["service_tier"] = self.service_tier
         return params
 
     def _get_ls_params(
@@ -819,16 +839,20 @@ class ChatFireworks(BaseChatModel):
         if not isinstance(response, dict):
             response = response.model_dump()
         token_usage = response.get("usage", {})
+        service_tier = response.get("service_tier")
         for res in response["choices"]:
             message = _convert_dict_to_message(res["message"])
-            if token_usage and isinstance(message, AIMessage):
-                message.usage_metadata = {
-                    "input_tokens": token_usage.get("prompt_tokens", 0),
-                    "output_tokens": token_usage.get("completion_tokens", 0),
-                    "total_tokens": token_usage.get("total_tokens", 0),
-                }
-                message.response_metadata["model_provider"] = "fireworks"
-                message.response_metadata["model_name"] = self.model_name
+            if isinstance(message, AIMessage):
+                if token_usage:
+                    message.usage_metadata = {
+                        "input_tokens": token_usage.get("prompt_tokens", 0),
+                        "output_tokens": token_usage.get("completion_tokens", 0),
+                        "total_tokens": token_usage.get("total_tokens", 0),
+                    }
+                    message.response_metadata["model_provider"] = "fireworks"
+                    message.response_metadata["model_name"] = self.model_name
+                if service_tier:
+                    message.response_metadata["service_tier"] = service_tier
             generation_info = {"finish_reason": res.get("finish_reason")}
             if "logprobs" in res:
                 generation_info["logprobs"] = res["logprobs"]
@@ -841,6 +865,8 @@ class ChatFireworks(BaseChatModel):
             "token_usage": token_usage,
             "system_fingerprint": response.get("system_fingerprint", ""),
         }
+        if service_tier:
+            llm_output["service_tier"] = service_tier
         return ChatResult(generations=generations, llm_output=llm_output)
 
     async def _astream(