[gpt-oss] add input/output usage in responses api when harmony context is leveraged

vllm/entrypoints/context.py

@@ -3,6 +3,7 @@
 import json
 import logging
 from abc import ABC, abstractmethod
+from collections.abc import Sequence
 from typing import TYPE_CHECKING, Union
 
 from openai_harmony import Author, Message, Role, StreamState, TextContent
@@ -67,15 +68,27 @@ def __init__(
 
         self.parser = get_streamable_parser_for_assistant()
         self.num_init_messages = len(messages)
-        # TODO(woosuk): Implement the following fields.
         self.num_prompt_tokens = 0
-        self.num_cached_tokens = 0
         self.num_output_tokens = 0
+        # TODO(woosuk): Implement the following fields.
+        self.num_cached_tokens = 0
         self.num_reasoning_tokens = 0
 
+    def _update_num_prompt_tokens(self, output: RequestOutput):
+        if output.prompt_token_ids and len(output.prompt_token_ids) > 0:
+            # NOTE: with built-in tools, there might be multiple rounds in
+            # the conversation, with the full conversation being resent
+            # as new prompt each time. Hence the sum.
+            self.num_prompt_tokens += len(output.prompt_token_ids)
+
+    def _update_num_output_tokens(self, token_ids: Sequence[int]):
+        self.num_output_tokens += len(token_ids)
+
     def append_output(self, output) -> None:
         if isinstance(output, RequestOutput):
+            self._update_num_prompt_tokens(output)
             output_token_ids = output.outputs[0].token_ids
+            self._update_num_output_tokens(output_token_ids)
             self.parser = get_streamable_parser_for_assistant()
             for token_id in output_token_ids:
                 self.parser.process(token_id)
@@ -158,15 +171,26 @@ def __init__(self, *args, **kwargs):
         self.parser = get_streamable_parser_for_assistant()
         self.encoding = get_encoding()
         self.last_tok = None
+        self.first_tok_of_message = True
 
     @property
     def messages(self) -> list:
         return self.parser.messages
 
     def append_output(self, output) -> None:
         if isinstance(output, RequestOutput):
+            # append_output is called for each output token in streaming case,
+            # so we only want to add the prompt tokens once for each message.
+            if self.first_tok_of_message:
+                self._update_num_prompt_tokens(output)
+            # Reset self.first_tok_of_message if needed:
+            # if the current token is the last one of the current message
+            # (finished=True), then the next token processed will mark the
+            # beginning of a new message
+            self.first_tok_of_message = output.finished
             tok = output.outputs[0].token_ids[0]
             self.parser.process(tok)
+            self._update_num_output_tokens(output.outputs[0].token_ids)
             self.last_tok = tok
         else:
             # Handle the case of tool output in direct message format