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[Bugfix][Structured Output] Cap JSON schema nesting to prevent 500s and API-server stalls - #60036

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sfeng33 merged 5 commits into
vllm-project:mainfrom
Mazukiri:reject-overdeep-json-schema
Oct 6, 2026
Merged

sfeng33 merged 5 commits into
vllm-project:mainfrom
Mazukiri:reject-overdeep-json-schema

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@Mazukiri

@Mazukiri Mazukiri commented Oct 5, 2026 •

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Overview

A structured-output JSON schema or structural tag can be nested arbitrarily deep, and vLLM validates and converts it on the API server. That causes two problems:

  • Crash: past ~980 levels, the recursive schema walks (has_xgrammar_unsupported_json_features and similar) raise RecursionError. The request returns HTTP 500 with an empty message.
  • Freeze: below that, the schema is accepted, but xgr.Grammar.from_json_schema / from_structural_tag costs roughly size × depth² and runs synchronously on the event loop. One small request blocks every other request and /health for seconds; a depth-512 structural tag stalled the server for 34 s and still returned 200.

This PR rejects schemas nested more than 64 levels of objects and arrays with a 400, before any backend walks or converts them. OpenAI's spec allows 10 levels of schema nesting (max_nesting_depth: 10 in x-openai-structured-output-limits), so 64 leaves plenty of headroom.

The first commit caught RecursionError instead. That fixed the crash but not the freeze, so the second commit replaces it with the depth cap.

Test plan and results

End to end: NVIDIA H200, vllm serve Qwen/Qwen3-0.6B --max-model-len 4096 --enable-auto-tool-choice --tool-call-parser hermes --no-enable-prefix-caching. The same 42 requests were sent to main (55b80221ed) and to this change, measuring the worst concurrent /health latency during each request. Schema depth is the PR's original shape (2 JSON levels per step):

Request main This PR
response_format depth 30 (63 levels) 200 200, same output
response_format depth 31 (65 levels) 200 400
response_format depth 200 200, /health stalled 1.7 s 400, no stall
depth 512 on chat, structured_outputs, Responses, completions, Anthropic /v1/messages 500, "message": "" 400
structural tag depth 512 200 after 98.6 s, /health stalled 33.8 s 400, no stall
strict tool + tool_choice=auto + response_format depth 512 500, "maximum recursion depth exceeded" 400
strict tool parameters at 65 levels 200 200, same output
strict tool parameters at 123 levels 200 400

The other 23 requests produced identical output on both: shallow schemas, a realistic nested schema, json_object, and shallow and strict tool calls.

The 400 message is: The JSON schema is nested too deeply: objects and arrays may nest at most 64 levels.

…t a 500

The xgrammar and guidance schema checks walk a JSON schema recursively,
outside the try/except blocks that turn backend errors into validation
errors. A schema nested deeper than the interpreter's stack raises
RecursionError, which reaches the API layer as a 500 with an empty message.
Report it as a validation error when the request carries a JSON schema.

This change was prepared with AI assistance, which was also used to run
the measurements in the PR description. The author reviewed every
changed line.

Signed-off-by: Mazukiri <maihoangduc04@gmail.com>
Co-Authored-By: Claude Opus 5.5 <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.

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AI-assisted review by Codex. No blocking issue found in this static review.

Checked that the wrapper preserves backend validation and converts RecursionError to VLLMValidationError only when a JSON schema is present. Reviewed the auto-backend fallback and the new deep-schema/ordinary-schema cases. Backend validation and HTTP integration tests were not independently run locally.

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Thanks!

@sfeng33 sfeng33 closed this Oct 5, 2026
@sfeng33 sfeng33 reopened this Oct 5, 2026
Catching RecursionError turns the crash into a 400, but schemas nested just
under the recursion limit are still accepted, and xgrammar's grammar
conversion (roughly size x depth^2) then blocks the API server event loop:
a depth-512 structural tag stalled /health for 34 s on main.

Reject JSON schemas nested more than 64 levels of objects and arrays
(OpenAI allows 10 levels of schema nesting), and structural tags 16 levels
beyond that, since tags generated by tool parsers wrap the schema in up to
15 levels. The check runs before backend dispatch, in
validate_xgrammar_grammar (request-parse structural tags and the tool
parser's _xgrammar_supports call it first), in
validate_structural_tag_payload, and in the Cohere Command parser, which
compiles tool schemas itself.

Signed-off-by: sfeng33 <4florafeng@gmail.com>
@mergify mergify Bot added cohere Related to Cohere models frontend tool-calling labels Oct 5, 2026
@sfeng33 sfeng33 changed the title [Bugfix][Structured Output] Reject an over-deep schema with a 400, not a 500 [Bugfix][Structured Output] Cap JSON schema nesting to prevent 500s and API-server stalls Oct 5, 2026
Parsers convert the request's structured-output constraint in
adjust_request, before request validation. A JSON schema or structural tag
sent as a string nested deeper than json.loads can decode (~10,000 levels)
raised RecursionError there, so harmony, Mistral and Cohere Command models
still returned a 500 for it. Run check_json_nesting before each of those
json.loads calls.

Signed-off-by: sfeng33 <4florafeng@gmail.com>
@mergify mergify Bot added the mistral Related to Mistral models label Oct 5, 2026
@sfeng33 sfeng33 added the ready ONLY add when PR is ready to merge/full CI is needed label Oct 5, 2026
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✅ @Mazukiri, CI is now available for this PR.

  • /ci run starts upstream CI; /amd-ci run starts AMD CI only.
  • Your branch must contain every commit currently on its upstream target branch. Merge or rebase onto the latest target branch, then rerun the command. Append --allow-stale to a run command to test an outdated branch at your own risk.
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  • /ci cancel cancels scheduled or running CI builds for this PR branch; /amd-ci cancel does the same for AMD CI only.

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/ci run

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✅ Triggered Buildkite CI #92958 for commit ef44811f2373.

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CI selector (shadow): 130 test steps (163 jobs) instead of 62 (78 jobs)

Shadow mode: this changes nothing about what CI runs. It shows what the evidence-based selector would pick for this PR, next to today's rules. How it works.

Feedback welcome: reply here if it would skip a step this change needs, or runs something unrelated.

steps (jobs) Today's rules Selector Would skip Would add
NVIDIA, CPU and others 62 (78) 130 (163) 11 (17) 79 (102)
AMD mirrors 54 (65) 115 (149) 8 (11) 69 (95)
Selector would run (130)
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  • spec-decode-eagle-1-deepseek-qwen
  • spec-decode-eagle-2-llama3-qwen-vl-other
  • spec-decode-mtp-deepseek-mimo
  • spec-decode-mtp-gemma4
  • spec-decode-mtp-qwen3-5
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  • v1-others-cpu
  • v1-sample
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Would skip (today's rules run them) (11)
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  • pytorch-compilation-unit-tests-h100
Would add (today's rules do not run them) (79)
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  • fusion-e2e-tp2-quick-h100 (Python record)
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  • lm-eval-turboquant-t4nc (Python record)
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  • quantization ×4 (code map)
  • quantized-models-test (code map)
  • quantized-moe-test-b200 (Python record)
  • rayexecutorv2-4-gpus (code map)
  • replayssm-e2e (Python record)
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  • scale-out-ec-e2e-2-gpus (Python record)
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  • spec-decode-eagle-1-deepseek-qwen (code map)
  • spec-decode-eagle-2-llama3-qwen-vl-other (code map)
  • spec-decode-mtp-deepseek-mimo (code map)
  • spec-decode-mtp-gemma4 (code map)
  • spec-decode-mtp-qwen3-5 (code map)
  • spec-decode-ngram-suffix (code map)
  • spec-decode-speculators (code map)
  • v1-attention-b200 ×2 (code map)
  • v1-attention-h100-mi300 ×2 (code map)
AMD mirrors: would skip (8)
  • basic-models-tests-initialization
  • entrypoints-integration-pooling
  • kernels-fla-ops-test-b200
  • kernels-mhc-test-b200
  • multi-modal-processor ×4
  • platform-tests
  • pytorch-compilation-passes-unit-tests
  • pytorch-compilation-unit-tests-h100
AMD mirrors: would add (69)
  • batch-invariance-h100 (code map)
  • crosslayer-kv-layout-distributed-nixlconnector-pd-accuracy-tests-4-gpus (Python record)
  • cudagraph (Python record)
  • distributed-dp-tests-2-gpus (code map)
  • distributed-dp-tests-4-gpus (code map)
  • distributed-flashinfer-nixlconnector-pd-accuracy-4-gpus (Python record)
  • distributed-model-tests-2-gpus ×3 (code map)
  • distributed-mooncakeconnector-pd-accuracy-4-gpus (Python record)
  • distributed-nixlconnector-pd-accuracy-4-gpus (Python record)
  • distributed-tests-8xh100 (Python record)
  • distributed-torchrun-examples-4-gpus (code map)
  • distributed-torchrun-shutdown-tests-2-gpus (code map)
  • dp-ep-distributed-nixlconnector-pd-accuracy-tests-4-gpus (Python record)
  • engine (code map)
  • engine-1-gpu (code map)
  • extract-hidden-states-integration (code map)
  • extract-hidden-states-integration-2-gpus (code map)
  • fusion-and-compile-unit-tests-2xb200 (Python record)
  • fusion-e2e-config-sweep-h100 (Python record)
  • fusion-e2e-quick-h100 (Python record)
  • fusion-e2e-tp2-ar-rms-config-sweep-h100 (Python record)
  • fusion-e2e-tp2-asynctp-config-sweep-h100 (Python record)
  • fusion-e2e-tp2-b200 (Python record)
  • fusion-e2e-tp2-quick-h100 (Python record)
  • hybrid-ssm-nixlconnector-pd-accuracy-tests-4-gpus (Python record)
  • hybrid-ssm-nixlconnector-pd-prefix-cache-2-gpus (Python record)
  • jit-monitor-no-runtime-jit (Python record)
  • kernels-moe-test ×5 (Python record)
  • kernels-quantization-test ×6 (Python record)
  • kv-offload-large (Python record)
  • kv-offload-medium (Python record)
  • kv-offload-small (Python record)
  • language-models-tests-extra-standard ×2 (code map)
  • lm-eval-small-models (Python record)
  • lm-eval-turboquant-k3v4nc (Python record)
  • lm-eval-turboquant-k8v4 (Python record)
  • lm-eval-turboquant-t3nc (Python record)
  • lm-eval-turboquant-t4nc (Python record)
  • lora ×4 (code map)
  • lora-tp-distributed ×4 (code map)
  • model-executor (code map)
  • mooncake-ec-tcp-e2e-2-gpus (Python record)
  • mrcr-eval-small-models (Python record)
  • multi-modal-accuracy-eval-small-models (Python record)
  • multiconnector-nixl-offloading-pd-accuracy-2-gpus (Python record)
  • multiconnector-nixl-offloading-pd-edge-cases-2-gpus (Python record)
  • nixlconnector-pd-edge-cases-2-gpus (Python record)
  • nixlconnector-pd-spec-decode-acceptance-2-gpus (Python record)
  • openai-api-correctness (Python record)
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  • plugin-tests-2-gpus (code map)
  • push-nixlconnector-pp-prefill-pd-accuracy-4-gpus (Python record)
  • quantization ×4 (code map)
  • quantized-models-test (code map)
  • quantized-moe-test-b200 (Python record)
  • rayexecutorv2-4-gpus (code map)
  • samplers-multimodal-beam-search (code map)
  • samplers-test (code map)
  • scale-out-ec-e2e-2-gpus (Python record)
  • spec-decode-draft-model ×4 (code map)
  • spec-decode-eagle-1-deepseek-qwen (code map)
  • spec-decode-eagle-2-llama3-qwen-vl-other (code map)
  • spec-decode-mtp-deepseek-mimo (code map)
  • spec-decode-mtp-gemma4 (code map)
  • spec-decode-mtp-qwen3-5 (code map)
  • spec-decode-ngram-suffix (code map)
  • spec-decode-speculators (code map)
  • v1-attention-b200 ×2 (code map)
  • v1-attention-h100-mi300 ×2 (code map)

11 changed files · base 6dd813e0b7 · head 1b3a32ab33 · Python record: build 92838 at 92044241a0 · kernel record: table 9204424 (build 92838), map 9204424 · not counted: 10 build steps, 5 A100 steps the generator no longer emits, 119 optional steps the selector would also run

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sfeng33 commented Oct 5, 2026

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/ci retry

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github-actions Bot commented Oct 5, 2026

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✅ Triggered Buildkite CI #92981 for commit 1b3a32ab33b3, running 3 failed step(s) from Buildkite CI #92958.

@sfeng33
sfeng33 enabled auto-merge (squash) October 5, 2026 23:32
@sfeng33
sfeng33 merged commit 5cd8a26 into vllm-project:main Oct 6, 2026
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@Mazukiri

Mazukiri commented Oct 7, 2026

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Thank you so much for taking the time to review and help fix this.

michael-gpu pushed a commit to practical-inference/vllm-ampere-extended that referenced this pull request Oct 20, 2026
…nd API-server stalls (vllm-project#60036)

Signed-off-by: Mazukiri <maihoangduc04@gmail.com>
Signed-off-by: sfeng33 <4florafeng@gmail.com>
Co-authored-by: Flora Feng <4florafeng@gmail.com>
@arpera arpera removed this from Tool Calling Oct 21, 2026
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