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…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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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 @DarkLight1337 would you want that follow-up, or should I close this? |
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Let's just close it |
Purpose
Fixes #57730.
POST /tokenizewith a chat body whose assistant message has"content": nulland atool_callslist returns HTTP 400:Root cause:
ChatCompletionAssistantMessageParam.tool_callsis typedIterable[...]in the OpenAI SDK, so pydantic wraps it in a lazyValidatorIteratorwhen validating themessagesunion.ChatCompletionRequestalready handles this with amode="before"normalization pass (tool_calls iterables to lists,reasoning_contenttoreasoning; #34792, #42664) and amode="after"pass that converts the wrapper back into a plain list.TokenizeChatRequestand the poolingChatRequestMixincarry the samemessages: list[ChatCompletionMessageParam]field but had neither pass, so the wrapper reached the tokenizer, whichcopy.deepcopys the messages, anddeepcopypickles.Change:
vllm/entrypoints/chat_utils.py(normalize_chat_messages_before_validation,materialize_tool_calls_in_messages); bodies are unchanged.ChatCompletionRequestdelegates to them (no behavior change for/v1/chat/completions).TokenizeChatRequestand the poolingChatRequestMixin(base ofEmbeddingChatRequest,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 themessagesfield and the same failure.Test Plan
Regression tests added to
tests/entrypoints/openai/test_tool_calls_serialization.py(the file that guards #34792), parametrized overChatCompletionRequest,TokenizeChatRequest,EmbeddingChatRequest:test_tool_calls_materialised_for_all_chat_request_models: tool_calls is alist, survivescopy.deepcopy, and can be iterated twice.test_reasoning_content_normalised_for_all_chat_request_models: the deprecated alias is renamed on every model.Manual repro from the issue (Python API, no server):
Test Result
TokenizeChatRequestandEmbeddingChatRequest(ValidatorIterator,TypeError: cannot pickle ...) and pass forChatCompletionRequest, which is exactly the claim.main,type(req.messages[1]["tool_calls"])isValidatorIteratoranddeepcopyraises the reportedTypeError; with this PR it islistanddeepcopysucceeds.pre-commit runon 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;typosclean.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.