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Fix GLM47 required tool call parsing - #48103
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Skip JSON structured output constraints for GLM47 forced tool choices so native XML-like tool calls remain parseable. Co-authored-by: OpenAI Codex <codex@openai.com> Signed-off-by: leo <yaoliu548926@gmail.com>
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July 9, 2026 08:25
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GLM required-tool structural decoding can emit <tool_call> and </tool_call> as ordinary subtokens rather than their dedicated special-token IDs. Once any token IDs have appeared, the streaming parser intentionally demotes text-matched token-ID terminals to content. The GLM tool parser then leaks raw tool markup into message.content and emits no tool_calls. Preserve strict token-ID matching by default. Add an explicit lexical fallback and enable it only for GLM TOOL_START and TOOL_END while processing tool_choice="required". Auto and plain GLM generations retain the existing literal-marker protection, and other parser-engine models are unchanged. Configure the fallback through GLM's request-aware tool-parsing hook so both direct ParserEngine streams and ParserEngineToolAdapter streams use it. Add coverage for the default strict behavior, the explicit fallback, and the GLM tool-adapter path that exposed the bug. Duplicate-work check: - vllm-project#48095 reports the same v0.24 user-visible failure. - vllm-project#47175 and vllm-project#47146 address non-strict JSON-guided generation, not streamed marker classification. - vllm-project#48103 was closed and changed request grammar selection rather than parser routing. - No open PR was found for GLM lexical marker routing. Validation: - pre-commit passed for all changed files, including ruff and mypy. - git diff --check passed. - A vLLM 0.24 image carrying the same runtime changes passed all four targeted GLM-5.2 tool-contract tests and produced a full Maru result of 40 passed, 1 unrelated structured-output multipleOf failure, and 4 skipped. - Targeted pytest could not collect in the current lightweight local environment because numpy is not installed; no dependencies were added to the shared environment. AI assistance was used to inspect parser routing, prepare the patch and tests, and run the listed validation. The human submitter must review and defend the change end to end before proposing it upstream. Assisted-by: OpenAI Codex Signed-off-by: Ace Eldeib <aeldeib@coreweave.com>
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Purpose
Fixes #48095.
GLM-5.2 / GLM-4.7-style tool calls can leak raw
<tool_call>...text intomessage.contentwith emptymessage.tool_callswhentool_choice="required"is used with theglm47tool parser.The issue is that
Glm47MoeModelToolParserdeclaressupports_required_and_named = False, so required/named tool choices shouldfall back to the model-native parser. However, the base
ToolParser.adjust_request()still installs JSONstructured_outputsfor forced tool choices, which conflicts with GLM's native XML-like tool-call format.
Changes
Glm47MoeModelToolParser.adjust_request().tool_choice="required"and named tool choices, skip the base JSON structured-output constraint.skip_special_tokens=Falseso GLM native tool-call markers remain visible to the parser.requiredand named tool choices.Duplicate-work check
Checked open PRs:
This PR is materially different from those approaches: it keeps GLM forced tool choices on the native XML-like parser path by
avoiding conflicting JSON
structured_outputs, matching the existing pattern used by native-format parsers such as Gemma4/Poolside. It does not change the GLM
supports_required_and_namedflag or add a JSON-schema forced-call path.Testing
Passed:
.venv/bin/python -m py_compile vllm/tool_parsers/glm47_moe_tool_parser.py tests/tool_parsers/test_glm47_moe_tool_parser.py/mnt/data1/models/zai-org/GLM-5.2-FP8VLLM_ENFORCE_STRICT_TOOL_CALLING=0fullParserManager(glm47 + glm45)validation:structured_outputsremainsNonegit diff --check