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[Misc] Use VLLMValidationError consistently in completion and chat completion protocol #35666

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[Misc] Use VLLMValidationError consistently in completion and chat completion protocol #35666

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81 changes: 53 additions & 28 deletions vllm/entrypoints/openai/chat_completion/protocol.py
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Original file line number Diff line number Diff line change
Expand Up @@ -616,19 +616,22 @@ def check_structured_outputs_count(cls, data):
)
# you can only use one kind of constraints for structured outputs
if count > 1:
raise ValueError(
"You can only use one kind of constraints for structured "
"outputs ('json', 'regex' or 'choice')."
raise VLLMValidationError(
"You can only use one kind of constraints "
"for structured outputs "
"('json', 'regex' or 'choice').",
parameter="structured_outputs",
)
# you can only either use structured outputs or tools, not both
if count > 1 and data.get("tool_choice", "none") not in (
"none",
"auto",
"required",
):
raise ValueError(
"You can only either use constraints for structured outputs "
"or tools, not both."
raise VLLMValidationError(
"You can only either use constraints for "
"structured outputs or tools, not both.",
parameter="structured_outputs",
)
return data

Expand All @@ -648,17 +651,24 @@ def check_tool_usage(cls, data):
if "tool_choice" in data and data["tool_choice"] is not None:
# ensure that if "tool choice" is specified, tools are present
if "tools" not in data or data["tools"] is None:
raise ValueError("When using `tool_choice`, `tools` must be set.")
raise VLLMValidationError(
"When using `tool_choice`, `tools` must be set.",
parameter="tool_choice",
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@DarkLight1337 DarkLight1337 Mar 18, 2026

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The parameter here should be tools

value=data.get("tool_choice"),
)

# make sure that tool choice is either a named tool
# OR that it's set to "auto" or "required"
if data["tool_choice"] not in ["auto", "required"] and not isinstance(
data["tool_choice"], dict
):
raise ValueError(
f"Invalid value for `tool_choice`: {data['tool_choice']}! "
'Only named tools, "none", "auto" or "required" '
"are supported."
raise VLLMValidationError(
"Invalid value for `tool_choice`: "
f"{data['tool_choice']}! "
'Only named tools, "none", "auto" '
'or "required" are supported.',
parameter="tool_choice",
value=data.get("tool_choice"),
)

# if tool_choice is "required" but the "tools" list is empty,
Expand All @@ -683,39 +693,52 @@ def check_tool_usage(cls, data):
valid_tool = False
function = data["tool_choice"].get("function")
if not isinstance(function, dict):
raise ValueError(
f"Invalid value for `function`: `{function}` in "
f"`tool_choice`! {correct_usage_message}"
raise VLLMValidationError(
"Invalid value for `function`: "
f"`{function}` in `tool_choice`! "
f"{correct_usage_message}",
parameter="tool_choice",
value=data.get("tool_choice"),
)
if "name" not in function:
raise ValueError(
f"Expected field `name` in `function` in "
f"`tool_choice`! {correct_usage_message}"
raise VLLMValidationError(
"Expected field `name` in `function`"
f" in `tool_choice`! "
f"{correct_usage_message}",
parameter="tool_choice",
value=data.get("tool_choice"),
)
function_name = function["name"]
if not isinstance(function_name, str) or len(function_name) == 0:
raise ValueError(
f"Invalid `name` in `function`: `{function_name}`"
f" in `tool_choice`! {correct_usage_message}"
raise VLLMValidationError(
"Invalid `name` in `function`: "
f"`{function_name}` in "
f"`tool_choice`! "
f"{correct_usage_message}",
parameter="tool_choice",
value=data.get("tool_choice"),
)
for tool in data["tools"]:
if tool["function"]["name"] == function_name:
valid_tool = True
break
if not valid_tool:
raise ValueError(
"The tool specified in `tool_choice` does not match any"
" of the specified `tools`"
raise VLLMValidationError(
"The tool specified in `tool_choice` "
"does not match any of the "
"specified `tools`.",
parameter="tool_choice",
value=data.get("tool_choice"),
)
return data

@model_validator(mode="before")
@classmethod
def check_generation_prompt(cls, data):
if data.get("continue_final_message") and data.get("add_generation_prompt"):
raise ValueError(
"Cannot set both `continue_final_message` and "
"`add_generation_prompt` to True."
raise VLLMValidationError(
"Cannot set both `continue_final_message` "
"and `add_generation_prompt` to True.",
)
Comment on lines +739 to 742
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@gemini-code-assist gemini-code-assist bot Mar 1, 2026

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high

For consistency with the other changes in this PR, it would be better to specify which parameter is causing the validation error. Since this is a conflict between two parameters, you can pick one to report. add_generation_prompt seems like a reasonable choice.

Suggested change
raise VLLMValidationError(
"Cannot set both `continue_final_message` "
"and `add_generation_prompt` to True.",
)
raise VLLMValidationError(
"Cannot set both `continue_final_message` "
"and `add_generation_prompt` to True.",
parameter="add_generation_prompt",
)

return data

Expand All @@ -725,8 +748,10 @@ def check_cache_salt_support(cls, data):
if data.get("cache_salt") is not None and (
not isinstance(data["cache_salt"], str) or not data["cache_salt"]
):
raise ValueError(
"Parameter 'cache_salt' must be a non-empty string if provided."
raise VLLMValidationError(
"Parameter 'cache_salt' must be a non-empty string if provided.",
parameter="cache_salt",
value=data.get("cache_salt"),
)
return data

Expand Down
10 changes: 6 additions & 4 deletions vllm/entrypoints/openai/completion/protocol.py
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Original file line number Diff line number Diff line change
Expand Up @@ -427,8 +427,8 @@ def validate_prompt_and_prompt_embeds(cls, data):
)

if prompt_is_empty and embeds_is_empty:
raise ValueError(
"Either prompt or prompt_embeds must be provided and non-empty."
raise VLLMValidationError(
"Either prompt or prompt_embeds must be provided and non-empty.",
)
Comment on lines +430 to 432
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@gemini-code-assist gemini-code-assist bot Mar 1, 2026

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high

For consistency with the goal of this PR to provide structured error context, it's a good idea to include the parameter that failed validation. In this case, since either prompt or prompt_embeds is required, you can specify prompt as the parameter.

Suggested change
raise VLLMValidationError(
"Either prompt or prompt_embeds must be "
"provided and non-empty.",
)
raise VLLMValidationError(
"Either prompt or prompt_embeds must be "
"provided and non-empty.",
parameter="prompt",
)


return data
Expand All @@ -439,8 +439,10 @@ def check_cache_salt_support(cls, data):
if data.get("cache_salt") is not None and (
not isinstance(data["cache_salt"], str) or not data["cache_salt"]
):
raise ValueError(
"Parameter 'cache_salt' must be a non-empty string if provided."
raise VLLMValidationError(
"Parameter 'cache_salt' must be a non-empty string if provided.",
parameter="cache_salt",
value=data.get("cache_salt"),
)
return data

Expand Down
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