[Feature][Response API] Support `num_cached_tokens` and `num_reasoning_tokens` in ResponseUsage

[heheda12345]

🚀 The feature, motivation and pitch

These attributes are important for monitoring model behavior. But both variables are set to 0 now.

vllm/vllm/entrypoints/context.py

Lines 70 to 74 in 8a19303

	# TODO(woosuk): Implement the following fields.
	self.num_prompt_tokens = 0
	self.num_cached_tokens = 0
	self.num_output_tokens = 0
	self.num_reasoning_tokens = 0

#22667 implements num_prompt_tokens and num_output_tokens, but we still need help for num_cached_tokens and num_reasoning_tokens.

When implementing this, please note that

1. gpt-oss has built-in tool calls so one request can trigger multiple rounds of generation

   vllm/vllm/entrypoints/openai/serving_engine.py

   Line 954 in 8a19303

   async def _generate_with_builtin_tools(

2. For non_streaming case, Context.append_output is called for each round of generation, while for streaming case, append_output is called for each output token.

Alternatives

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Additional context

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[NagyGeorge]

Hello I'd like to work on this if it could be assigned?

[heheda12345]

Assigned. Thanks for your help.

[simon-mo]

@heheda12345 this doesn't solve the streaming case right? do we have a ticket for that?

[heheda12345]

For streaming case, the usage is included in the final response:

ResponseCompletedEvent(response=Response(id='resp_453ccb3f9ea741d486c28660e8d15d3c', created_at=1757033373.0, error=None, incomplete_details=None, instructions=None, metadata=None, model='openai/gpt-oss-20b', object='response', output=[], parallel_tool_calls=True, temperature=1.0, tool_choice='auto', tools=[], top_p=1.0, background=False, conversation=None, max_output_tokens=130990, max_tool_calls=None, previous_response_id=None, prompt=None, prompt_cache_key=None, reasoning=Reasoning(effort='low', generate_summary=None, summary=None), safety_identifier=None, service_tier='auto', status='completed', text=None, top_logprobs=None, truncation='disabled', usage=ResponseUsage(input_tokens=82, input_tokens_details=InputTokensDetails(cached_tokens=0), output_tokens=49, output_tokens_details=OutputTokensDetails(reasoning_tokens=11), total_tokens=131), user=None), sequence_number=50, type='response.completed')

We need to also support include_continuous_usage. @NagyGeorge Do you want to take a look?

[NagyGeorge]

We need to also support include_continuous_usage. @NagyGeorge Do you want to take a look?

@heheda12345
Yeah sure sounds interesting.