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Walkthrough
ChangesAdditional tools support
Estimated code review effort: 3 (Moderate) | ~20 minutes Merge Risk: ⚪ Minimal · up to Responses requests can now supply tools through additional_tools without rendering those configuration items as conversation messages, including typed SDK inputs and requests without top-level tools. No concrete current-head merge risk remains. Suggested reviewers: 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches 💡 1🛠️ Fix failing CI checks 💡
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In `@vllm/entrypoints/openai/responses/protocol.py`:
- Line 610: Update the input handling around check_tool_usage and
input_item_parsing to normalize non-string iterables, including tuples and
ValidatorIterator values, into the list form before checking for and promoting
AdditionalTools. Ensure typed AdditionalTools entries are removed or handled
consistently and their tools are added to request.tools, then add a regression
test covering tuple or iterator input.
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I independently reviewed this PR after applying both commits cleanly on current main (114abd1c1). The valid path looks correct, and the two focused suites pass locally (57 tests total).
There is one fail-closed edge case worth fixing before merge: malformed additional_tools carriers are still accepted instead of reaching normal validation. For example:
request = ResponsesRequest.model_validate({
"model": "test",
"input": [
{
"id": "at_bad",
"type": "additional_tools",
"role": "developer",
"tools": [{"type": "function"}],
},
{"role": "user", "content": "hello"},
],
})This succeeds with request.tools == [] and leaves the carrier as a plain dict in request.input. The except ValidationError: input_items.append(item) path does not guarantee later rejection: the Responses input union accepts this shape, and current main now treats any dict containing role as a message. A malformed structural carrier can therefore be silently converted into conversation input.
Could this branch raise a VLLMValidationError when an item explicitly declares type == "additional_tools" but AdditionalTools(**item) fails, with a regression for a missing tool name or invalid parameters? That preserves the intended distinction between unsupported/malformed structural configuration and chat messages.
Minor library-facing point: the before-validator currently mutates the caller's input mapping in place (a tuple becomes a list, carriers are removed, and parsed tool objects can enter the original mapping). A shallow copy of data before normalization would avoid observable caller-side mutation.
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Purpose
Fixes #55659.
Treat Responses
additional_toolsinput items as structural requestconfiguration. Their tool definitions are appended to the effective top-level
tool list, and the items are removed from conversation input before chat or
Harmony rendering.
This supports clients such as Codex's Responses Lite path, which can send
client tool definitions only in an
additional_toolsinput item and omit thetop-level
toolsfield.Why this is not a duplicate
dict/model conversion. It does not handle
additional_toolsor expose itsdefinitions to tool preprocessing.
parser failures. It is not a mainline implementation of
additional_tools.additional_toolsandAdditionalToolsfound noexisting vLLM issue or PR before [Bug]: /v1/responses crashes on persisted additional_tools input items #55659 was opened.
Changes
AdditionalToolsinput items.ResponsesRequest.inputbefore messageconstruction.
Test Plan
Run the focused Responses request-parsing and message-construction suites, then
run every pre-commit hook applicable to the changed files.
No model evaluation is needed because this change only normalizes request
protocol data; it does not change model execution or output algorithms.
Test Result
The minimal reproducer was also run against unmodified upstream
mainated29dfae6e76235e01fcc0eca21cf0dcbfc40af1and failed with:With this change, the same request produces one user chat message and an
effective tool list containing
exec.AI assistance
This change was developed with OpenAI Codex assistance.
The human submitter reviewed every changed line, confirmed they understand the
request-normalization behavior, and approved the tested change before this PR
was submitted, as required by vLLM's contribution policy.