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[Misc] clear and separate error messages for input too long and input + max-tokens too long (#22803)

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Signed-off-by: Roger Wang <hey@rogerw.me>
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Roger Wang 2025-08-13 07:22:56 -07:00 committed by GitHub
parent 19b927e52d
commit da2705198f
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1 changed files with 18 additions and 13 deletions
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31
vllm/entrypoints/openai/serving_engine.py
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@ -585,6 +585,8 @@ class OpenAIServing:
(EmbeddingChatRequest, EmbeddingCompletionRequest,
ScoreRequest, RerankRequest, ClassificationRequest)):
# Note: input length can be up to the entire model context length
# since these requests don't generate tokens.
if token_num > self.max_model_len:
operations: dict[type[AnyRequest], str] = {
ScoreRequest: "score",
@ -613,21 +615,24 @@ class OpenAIServing:
max_tokens = request.max_completion_tokens or request.max_tokens
else:
max_tokens = getattr(request, "max_tokens", None)
if max_tokens is None:
if token_num >= self.max_model_len:
raise ValueError(
f"This model's maximum context length is "
f"{self.max_model_len} tokens. However, you requested "
f"{token_num} tokens in the messages, "
f"Please reduce the length of the messages.")
elif token_num + max_tokens > self.max_model_len:
# Note: input length can be up to model context length - 1 for
# completion-like requests.
if token_num >= self.max_model_len:
raise ValueError(
f"This model's maximum context length is "
f"{self.max_model_len} tokens. However, you requested "
f"{max_tokens + token_num} tokens "
f"({token_num} in the messages, "
f"{max_tokens} in the completion). "
f"Please reduce the length of the messages or completion.")
f"{self.max_model_len} tokens. However, your request has "
f"{token_num} input tokens. Please reduce the length of "
"the input messages.")
if max_tokens is not None and \
token_num + max_tokens > self.max_model_len:
raise ValueError(
"'max_tokens' or 'max_completion_tokens' is too large: "
f"{max_tokens}. This model's maximum context length is "
f"{self.max_model_len} tokens and your request has "
f"{token_num} input tokens ({max_tokens} > {self.max_model_len}"
f" - {token_num}).")
return TextTokensPrompt(prompt=input_text, prompt_token_ids=input_ids)