[Bugfix] [Frontend] Cleanup gpt-oss non-streaming chat tool calls

tests/entrypoints/openai/test_serving_chat.py

@@ -194,6 +194,7 @@ async def test_gpt_oss_multi_turn_chat(gptoss_client: OpenAI,
     assert tc.function is not None and tc.function.name == "get_current_weather"
     args1 = tc.function.arguments
     assert args1 is not None and len(args1) > 0
+    assert not first_msg.content
 
     messages.append({"role": "assistant", "content": args1})
     messages.append({

tests/tool_use/test_openai_tool_parser.py

@@ -70,7 +70,12 @@ def test_extract_tool_calls_no_tools(openai_tool_parser, harmony_encoding):
     assert extracted_info.content == "This is a test"
 
 
-def test_extract_tool_calls_single_tool(openai_tool_parser, harmony_encoding):
+@pytest.mark.parametrize("tool_args", [
+    '{"location": "Tokyo"}',
+    '{\n"location": "Tokyo"\n}',
+])
+def test_extract_tool_calls_single_tool(openai_tool_parser, harmony_encoding,
+                                        tool_args):
     convo = Conversation.from_messages([
         Message.from_role_and_content(Role.USER,
                                       "What is the weather in Tokyo?"),
@@ -80,7 +85,7 @@ def test_extract_tool_calls_single_tool(openai_tool_parser, harmony_encoding):
         ).with_channel("analysis"),
         Message.from_role_and_content(
             Role.ASSISTANT,
-            '{"location": "Tokyo"}').with_channel("commentary").with_recipient(
+            tool_args).with_channel("commentary").with_recipient(
                 "functions.get_current_weather").with_content_type("json"),
     ])
     token_ids = harmony_encoding.render_conversation_for_completion(

vllm/entrypoints/openai/serving_chat.py

@@ -1186,6 +1186,10 @@ async def chat_completion_full_generator(
                 logprobs = None
 
             if self.use_harmony:
+                reasoning_content, content, _ = parse_chat_output(token_ids)
+                if not request.include_reasoning:
+                    reasoning_content = None
+
                 if self.tool_parser is not None:
                     tool_parser = self.tool_parser(tokenizer)
                     # NOTE: We use token_ids for openai tool parser
@@ -1194,21 +1198,14 @@ async def chat_completion_full_generator(
                         request=request,
                         token_ids=token_ids,  # type: ignore
                     )
-                    reasoning_content, content = None, tool_call_info.content
-                    if request.include_reasoning:
-                        reasoning_content, content, _ = parse_chat_output(
-                            token_ids)
+                    content = tool_call_info.content
                     message = ChatMessage(
                         role=role,
                         reasoning_content=reasoning_content,
                         content=content,
                         tool_calls=tool_call_info.tool_calls,
                     )
                 else:
-                    reasoning_content, content, _ = parse_chat_output(
-                        token_ids)
-                    if not request.include_reasoning:
-                        reasoning_content = None
                     message = ChatMessage(
                         role=role,
                         reasoning_content=reasoning_content,

vllm/entrypoints/openai/tool_parsers/openai_tool_parser.py

@@ -2,6 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 from __future__ import annotations
 
+import json
 from collections.abc import Sequence
 from typing import TYPE_CHECKING
 
@@ -41,12 +42,18 @@ def extract_tool_calls(
         if len(parser.messages) > 0:
             for msg in parser.messages:
                 if msg.recipient and msg.recipient.startswith("functions."):
+                    if "json" in msg.content_type:
+                        # round-trip JSON text to ensure valid JSON and remove
+                        # any extra newlines
+                        tool_args = json.dumps(json.loads(msg.content[0].text))
+                    else:
+                        tool_args = msg.content[0].text
                     tool_calls.append(
                         ToolCall(
                             type="function",
                             function=FunctionCall(
                                 name=msg.recipient.split("functions.")[1],
-                                arguments=msg.content[0].text,
+                                arguments=tool_args,
                             ),
                         ))
                 elif msg.channel == "final":