Fa/fix json schema + tool calls

[faizsameerahmed96]

TODO

[claude]

Claude Code Review

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[github-actions]

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[gemini-code-assist]

Code Review

This pull request introduces logic to handle structured output constraints when 'thinking' mode is enabled for DeepSeek V3 models, ensuring the </think> tag remains reachable by wrapping JSON schemas in a structural tag. Review feedback identifies several critical issues: the implementation in the reasoning parser misses direct structured_outputs parameters and both parsers overwrite the StructuredOutputsParams object, which causes the loss of user-defined settings like whitespace patterns. Additionally, the tool parser's request adjustment explicitly excludes ResponsesRequest, which may break tool calls for that specific API. It is recommended to use vllm.config.utils.replace to update parameters while preserving existing configurations.

[gemini-code-assist]

The adjust_request implementation has two significant issues:

1. Missing structured_outputs support: It only checks request.response_format. If a user provides a JSON schema directly via the structured_outputs parameter (a common vLLM-specific usage), this logic is skipped, and the model will likely fail to close the reasoning block because the schema constraint will block the </think> tag.
2. State Overwrite: It overwrites the entire request.structured_outputs object with a new one. This causes the loss of any other structured output settings the user might have provided (e.g., disable_any_whitespace, whitespace_pattern).

You should check both response_format and structured_outputs, and use vllm.config.utils.replace to update the parameters while preserving existing settings.

        response_format = getattr(request, "response_format", None)
        structured_outputs = getattr(request, "structured_outputs", None)

        schema = None
        if response_format is not None:
            if response_format.type == "json_schema":
                json_schema = response_format.json_schema
                assert json_schema is not None
                schema = json_schema.json_schema
            elif response_format.type == "json_object":
                schema = {"type": "object"}

        if schema is None and structured_outputs is not None:
            schema = structured_outputs.json
            if isinstance(schema, str):
                schema = json.loads(schema)

        if schema is None:
            return request

        from vllm.config.utils import replace
        new_structured_outputs = replace(
            structured_outputs or StructuredOutputsParams(),
            json=None,
            json_object=None,
            structural_tag=json.dumps(
                {
                    "triggers": [_THINKING_END_TRIGGER],
                    "structures": [
                        {
                            "begin": _THINKING_END_BEGIN,
                            "schema": schema,
                            "end": "",
                        }
                    ],
                }
            )
        )
        setattr(request, "structured_outputs", new_structured_outputs)
        if response_format is not None:
            setattr(request, "response_format", None)

[gemini-code-assist]

The isinstance(request, ChatCompletionRequest) check explicitly excludes ResponsesRequest. Since ResponsesRequest is a supported type for tool parsing in the base ToolParser class, this exclusion means tool calls will remain broken (the </think> tag will be unreachable in the constrained vocabulary) when using the Responses API with thinking enabled. If ResponsesRequest does not yet support structural_tag, this limitation should be addressed or at least documented.

[gemini-code-assist]

Overwriting request.structured_outputs with a new StructuredOutputsParams object will lose any other parameters set by the user (e.g., disable_any_whitespace). Use vllm.config.utils.replace to preserve existing settings while switching the constraint from json to structural_tag.

Suggested change

	request.structured_outputs = StructuredOutputsParams(
	structural_tag=json.dumps(
	{
	"triggers": [_THINKING_END_TRIGGER],
	"structures": [
	{
	"begin": _THINKING_END_BEGIN,
	"schema": schema,
	"end": "",
	}
	],
	}
	)
	)
	from vllm.config.utils import replace
	request.structured_outputs = replace(
	request.structured_outputs,
	json=None,
	structural_tag=json.dumps(
	{
	"triggers": [_THINKING_END_TRIGGER],
	"structures": [
	{
	"begin": _THINKING_END_BEGIN,
	"schema": schema,
	"end": "",
	}
	],
	}
	)
	)