[Bugfix] Fix /v1/audio/speech usage token accounting for Qwen3-TTS (#4646) (#4673)

Signed-off-by: Yueqian Lin <linyueqian@outlook.com>
Co-authored-by: Sy03 <1370724210@qq.com>

vllm_omni/entrypoints/openai/protocol/audio.py

@@ -421,12 +421,65 @@ class BatchSpeechRequest(BaseModel):
     non_streaming_mode: bool | None = None
 
 
+class SpeechInputTokenDetails(BaseModel):
+    """Per-modality breakdown of the speech request's *input* tokens.
+
+    The aggregate ``input_tokens`` on :class:`SpeechTokenUsage` is the sum of
+    these. We surface the split (rather than one opaque number) for the same
+    reason OpenAI's realtime/chat usage does: text and audio inputs are billed
+    and reasoned about differently, and folding them together is misleading.
+
+    Fields:
+        text_tokens: Tokens of the text to synthesize. This is ``input`` plus
+            ``instructions`` (style/emotion prompt), because both are tokenized
+            into the model prefill. This is the number that should scale with
+            how much text the caller asked to speak.
+        audio_tokens: Reference-audio codec frames used as voice-cloning
+            conditioning. NON-ZERO only when in-context voice cloning is
+            actually active (Qwen3-TTS ``task_type='Base'`` ICL). It is 0 for
+            CustomVoice/VoiceDesign and for x-vector-only cloning, because those
+            paths put no reference codec frames into the prefill. See issue
+            #4646: this is the value that previously leaked into ``prompt_tokens``
+            and made Base usage look independent of the input text.
+    """
+
+    text_tokens: int = 0
+    audio_tokens: int = 0
+
+
+class SpeechTokenUsage(BaseModel):
+    """Token usage for a speech (TTS) request.
+
+    Field naming follows OpenAI's documented ``speech.audio.done`` event
+    (``input_tokens``/``output_tokens``/``total_tokens``), NOT chat's
+    ``prompt_tokens``/``completion_tokens``.
+
+    input_tokens  = text_tokens + audio_tokens   (see SpeechInputTokenDetails)
+    output_tokens = generated codec/audio tokens (stage-0 decode steps)
+    total_tokens  = input_tokens + output_tokens
+
+    IMPORTANT: ``input_tokens`` is computed from the *semantic* request inputs
+    (tokenized text + reference-audio frames), NOT from ``len(prompt_token_ids)``.
+    For staged TTS models that engine prompt is a ``[1] * prefill_len``
+    placeholder whose length mirrors the model prefill, so it is not a faithful
+    input-token count (issue #4646).
+    """
+
+    input_tokens: int = 0
+    output_tokens: int = 0
+    total_tokens: int = 0
+    input_token_details: SpeechInputTokenDetails = Field(default_factory=SpeechInputTokenDetails)
+
+
 class SpeechBatchItemResult(BaseModel):
     index: int
     status: Literal["success", "error"]
     audio_data: str | None = None
     media_type: str | None = None
     error: str | None = None
+    # Per-item token usage (input text + reference-audio conditioning, and
+    # generated audio tokens). None when the item errored before generation.
+    usage: SpeechTokenUsage | None = None
 
 
 class BatchSpeechResponse(BaseModel):