vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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- Issues
- [Bug]: xlam and hunyuan_a13b tool parsers drop the arguments of any tool call that follows an empty-argument call (streaming)
- [Bug]: A tool call truncated by max_tokens diverges between streaming and non-streaming, and leaks raw <tool_call> markup into content (non-streaming)
- [Bugfix] Fix Gemma4 engine parser returning bare values as strings
- [Bug]: DFlash/DSpark draft acceptance collapses with automatic prefix caching enabled
- [MoE] Add flashinfer.moe_ep (NCCL-EP) all2all backends: flashinfer_ep_low_latency / flashinfer_ep_high_throughput
- [LoRA] Skip empty-LoRA path in eager mode when no adapter is active
- [Bugfix][Frontend] Anchor empty-args detection to the current tool in xlam and hunyuan_a13b streaming parsers
- [Bugfix] Report finish_reason='length' for tool calls truncated by max_tokens in streaming
- [Bugfix][Tool Parser] Return early for unlisted tool names in InternLM2 parser
- [Bug]: vLLM embedding hang with Qwen3-Embedding when chunked prefill is enabled
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