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]: llama3_json, jamba and ernie45 tool parsers drop tool calls when the whole message arrives in a single streaming delta
- [RFC] LoRA Adapter Lifecycle for RL Training
- Revert "[Perf] fuse more rmsnorm and all-reduce in qwen3.5" (#46998)
- [RFC] Training-Inference Consistency for RL
- [RFC] RL Information Retrieval: APIs & Introspection
- [RFC] Sleep/Wake Correctness for RL
- [RFC] Engine Sleep/Wake/Drain Lifecycle for RL
- [RFC] Weight Reload Correctness for RL
- [Bug]: Mistral v11 streaming parser merges parallel tool calls into one when content precedes [TOOL_CALLS] in a single delta
- [Bug]: Responses API: explicit "background": null or "truncation": null fails response construction (confusing 400 / broken SSE stream)
- Docs
- Python not yet supported