A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 8, 02:30 UTC
Fix empty tool_call_id in Anthropic messages API tool result conversion (#34745)
Signed-off-by: <> Signed-off-by: sfeng33 <4florafeng@gmail.com> Co-authored-by: Flora Feng <sfeng33@h100-01.nemg-001.lab.rdu2.dc.redhat.com> Co-authored-by: Nicolò Lucchesi <nlucches@redhat.com>
Flora Feng committed
Feb 18, 2026 at 17:31 UTC
8d9babd4dea934fdd47b5a20a73ef0e04ff0e22e
2 files changed
+2
-1
vllm/entrypoints/anthropic/protocol.py
+1
@@ -40,6 +40,7 @@ class AnthropicContentBlock(BaseModel):
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source: dict[str, Any] | None = None
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# For tool use/result
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id: str | None = None
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+ tool_use_id: str | None = None
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name: str | None = None
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input: dict[str, Any] | None = None
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content: str | list[dict[str, Any]] | None = None
vllm/entrypoints/anthropic/serving.py
+1
-1
@@ -139,7 +139,7 @@ class AnthropicServingMessages(OpenAIServingChat):
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openai_messages.append(
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{
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"role": "tool",
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- "tool_call_id": block.id or "",
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+ "tool_call_id": block.tool_use_id or "",
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"content": str(block.content)
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if block.content
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else "",