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[Bugfix][Frontend] Materialize tool_calls in /tokenize and pooling chat requests - #58503

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sohom-cs:fix/tokenize-chat-materialize-tool-calls
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sohom-cs:fix/tokenize-chat-materialize-tool-calls

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@sohom-cs sohom-cs commented Sep 24, 2026 •

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Purpose

Fixes #57730.

POST /tokenize with a chat body whose assistant message has "content": null and a tool_calls list returns HTTP 400:

cannot pickle 'pydantic_core._pydantic_core.ValidatorIterator' object

Root cause: ChatCompletionAssistantMessageParam.tool_calls is typed Iterable[...] in the OpenAI SDK, so pydantic wraps it in a lazy ValidatorIterator when validating the messages union. ChatCompletionRequest already handles this with a mode="before" normalization pass (tool_calls iterables to lists, reasoning_content to reasoning; #34792, #42664) and a mode="after" pass that converts the wrapper back into a plain list. TokenizeChatRequest and the pooling ChatRequestMixin carry the same messages: list[ChatCompletionMessageParam] field but had neither pass, so the wrapper reached the tokenizer, which copy.deepcopys the messages, and deepcopy pickles.

Change:

  • Move the two passes into shared helpers in vllm/entrypoints/chat_utils.py (normalize_chat_messages_before_validation, materialize_tool_calls_in_messages); bodies are unchanged.
  • ChatCompletionRequest delegates to them (no behavior change for /v1/chat/completions).
  • TokenizeChatRequest and the pooling ChatRequestMixin (base of EmbeddingChatRequest, ClassificationChatRequest, PoolingChatRequest) apply the same two validators.

Relation to #57814: #57814 (earlier, approved) fixes TokenizeChatRequest. This PR will be rebased after it merges to cover only the pooling chat requests (ChatRequestMixin: EmbeddingChatRequest, ClassificationChatRequest, PoolingChatRequest), which share the messages field and the same failure.

Test Plan

Regression tests added to tests/entrypoints/openai/test_tool_calls_serialization.py (the file that guards #34792), parametrized over ChatCompletionRequest, TokenizeChatRequest, EmbeddingChatRequest:

  • test_tool_calls_materialised_for_all_chat_request_models: tool_calls is a list, survives copy.deepcopy, and can be iterated twice.
  • test_reasoning_content_normalised_for_all_chat_request_models: the deprecated alias is renamed on every model.
.venv/bin/python -m pytest tests/entrypoints/openai/test_tool_calls_serialization.py \
    tests/entrypoints/unit_tests/test_non_object_body_validation.py \
    tests/entrypoints/openai/test_tool_choice_content_none.py -q
pre-commit run --files <changed files>
pre-commit run mypy-3.12 --hook-stage manual --files <changed files>

Manual repro from the issue (Python API, no server):

import copy
from vllm.entrypoints.serve.tokenize.protocol import TokenizeChatRequest
req = TokenizeChatRequest(model="m", messages=[
    {"role": "user", "content": "What is the weather in Shanghai tomorrow?"},
    {"role": "assistant", "content": None, "tool_calls": [{"id": "call_1", "type": "function",
        "function": {"name": "lookup_weather", "arguments": "{\"city\": \"Shanghai\"}"}}]},
    {"role": "tool", "tool_call_id": "call_1", "content": "{\"temp_c\": 24}"},
    {"role": "user", "content": "Do I need an umbrella?"},
])
copy.deepcopy(req.messages)

Test Result

  • 66 passed (the three files above).
  • With the source change stashed, the two new tests fail for TokenizeChatRequest and EmbeddingChatRequest (ValidatorIterator, TypeError: cannot pickle ...) and pass for ChatCompletionRequest, which is exactly the claim.
  • Manual repro: on main, type(req.messages[1]["tool_calls"]) is ValidatorIterator and deepcopy raises the reported TypeError; with this PR it is list and deepcopy succeeds.
  • pre-commit run on the changed files: ruff check, ruff format, mypy 3.10 and mypy 3.12 (manual stage), SPDX, forbidden-imports and the other repo hooks all pass; typos clean.

No model output is affected; no evals needed.

AI assistance: this change was developed with AI assistance (Claude) for the code, the tests and the analysis. I reviewed every changed line, ran the tests and hooks above locally, and take responsibility for the change.

…at requests

`ChatCompletionRequest` normalizes `messages` (tool_calls iterators -> lists,
`reasoning_content` -> `reasoning`) and re-materializes the lazy
`ValidatorIterator` pydantic wraps `tool_calls` in. `TokenizeChatRequest` and
the pooling `ChatRequestMixin` carry the same `messages` field but skipped
both passes, so an assistant message with `content: null` + `tool_calls` sent
to `/tokenize` reached the tokenizer as a `ValidatorIterator` and failed on
`copy.deepcopy` with "cannot pickle 'ValidatorIterator' object" (HTTP 400).

Move the two passes into shared helpers in `chat_utils` and apply them from
all three request models. Regression tests parametrize over the three models.

Fixes vllm-project#57730

Signed-off-by: Sohom Chakraborty <sohomchakraborty.iitkgp@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>

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Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

@mergify mergify Bot added the bug Something isn't working label Sep 24, 2026
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@sohom-cs
sohom-cs marked this pull request as draft September 24, 2026 03:13
@sohom-cs

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I missed #57814 when I opened this (it links #57738 rather than #57730, so my search didn't find it). It's earlier and already approved, so it should land first; converting this to a draft.

The part #57814 doesn't cover is the pooling ChatRequestMixin (base of EmbeddingChatRequest, ClassificationChatRequest, PoolingChatRequest). It has the same messages field and fails the same way on copy.deepcopy; the parametrized test in this PR fails for EmbeddingChatRequest on main. Once #57814 merges I can rebase this down to just that, and optionally move the then-three copies of the validators into shared helpers in chat_utils.

@DarkLight1337 would you want that follow-up, or should I close this?

@DarkLight1337

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Let's just close it

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