docs: add SGLang Omni community integration

Add SGLang Omni to the English and Chinese community integrations pages with links to its Fun-ASR cookbook, runtime implementation, and merged upstream support PR.

docs/community_projects.md

@@ -29,6 +29,7 @@ These integrations are community-maintained. Their release cadence, hardware sup
 |---|---|---|
 | [Xinference](https://github.com/xorbitsai/inference) | Built-in audio model specifications for SenseVoiceSmall, Fun-ASR-Nano-2512, and Fun-ASR-MLT-Nano-2512 through Xinference's unified inference API. | [Audio model specifications](https://github.com/xorbitsai/inference/blob/main/xinference/model/audio/model_spec.json) and the FunASR 1.3 compatibility update in merged [#5140](https://github.com/xorbitsai/inference/pull/5140). |
 | [Optimum Intel](https://github.com/huggingface/optimum-intel) | OpenVINO export and inference support for Fun-ASR models through Hugging Face Optimum Intel, including FunASR-specific modeling and ASR/export/quantization coverage. | [FunASR OpenVINO modeling](https://github.com/huggingface/optimum-intel/blob/main/optimum/intel/openvino/modeling_funasr.py), [supported models docs](https://github.com/huggingface/optimum-intel/blob/main/docs/source/openvino/models.mdx), and merged [#1801](https://github.com/huggingface/optimum-intel/pull/1801). |
+| [SGLang Omni](https://github.com/sgl-project/sglang-omni) | A multi-stage pipeline runtime for omni models with built-in Fun-ASR model support, OpenAI-compatible serving, cookbook docs, and benchmark tasks. | [Fun-ASR cookbook](https://github.com/sgl-project/sglang-omni/blob/main/docs/cookbook/fun_asr.md), [Fun-ASR model runtime](https://github.com/sgl-project/sglang-omni/tree/main/sglang_omni/models/fun_asr), and merged [#1078](https://github.com/sgl-project/sglang-omni/pull/1078). |
 | [Fun-ASR-vLLM](https://github.com/yuekaizhang/Fun-ASR-vllm) | Community vLLM inference for Fun-ASR-Nano and Fun-ASR-MLT-Nano, including batch evaluation and NVIDIA Triton deployment. | [Setup and benchmarks](https://github.com/yuekaizhang/Fun-ASR-vllm#readme) and the deterministic ASR decoding fix in merged [#20](https://github.com/yuekaizhang/Fun-ASR-vllm/pull/20). |
 | [vad-burn](https://github.com/di-osc/vad-burn) | FSMN VAD inference in pure Rust with Python bindings, including offline, streaming, and CPU-only modes. | [Project README](https://github.com/di-osc/vad-burn#readme) and the FunASR showcase in [#3106](https://github.com/modelscope/FunASR/issues/3106). |
 

docs/community_projects_zh.md

@@ -29,6 +29,7 @@
 |---|---|---|
 | [Xinference](https://github.com/xorbitsai/inference) | 通过 Xinference 统一推理 API 提供 SenseVoiceSmall、Fun-ASR-Nano-2512 和 Fun-ASR-MLT-Nano-2512 内置音频模型规格。 | [音频模型规格](https://github.com/xorbitsai/inference/blob/main/xinference/model/audio/model_spec.json) 和已合并 [#5140](https://github.com/xorbitsai/inference/pull/5140) 中的 FunASR 1.3 兼容性更新。 |
 | [Optimum Intel](https://github.com/huggingface/optimum-intel) | 通过 Hugging Face Optimum Intel 支持 Fun-ASR 模型的 OpenVINO 导出与推理，包括 FunASR 专用 modeling 代码以及 ASR、export、quantization 覆盖。 | [FunASR OpenVINO modeling](https://github.com/huggingface/optimum-intel/blob/main/optimum/intel/openvino/modeling_funasr.py)、[支持模型文档](https://github.com/huggingface/optimum-intel/blob/main/docs/source/openvino/models.mdx) 和已合并 [#1801](https://github.com/huggingface/optimum-intel/pull/1801)。 |
+| [SGLang Omni](https://github.com/sgl-project/sglang-omni) | 面向 omni models 的 multi-stage pipeline runtime，已内置 Fun-ASR 模型支持、OpenAI 兼容服务、cookbook 文档和 benchmark 任务。 | [Fun-ASR cookbook](https://github.com/sgl-project/sglang-omni/blob/main/docs/cookbook/fun_asr.md)、[Fun-ASR 模型 runtime](https://github.com/sgl-project/sglang-omni/tree/main/sglang_omni/models/fun_asr) 和已合并 [#1078](https://github.com/sgl-project/sglang-omni/pull/1078)。 |
 | [Fun-ASR-vLLM](https://github.com/yuekaizhang/Fun-ASR-vllm) | 面向 Fun-ASR-Nano 和 Fun-ASR-MLT-Nano 的社区 vLLM 推理实现，包含批量评测和 NVIDIA Triton 部署。 | [安装与 Benchmark](https://github.com/yuekaizhang/Fun-ASR-vllm#readme) 和已合并 [#20](https://github.com/yuekaizhang/Fun-ASR-vllm/pull/20) 中的确定性 ASR 解码修复。 |
 | [vad-burn](https://github.com/di-osc/vad-burn) | 纯 Rust FSMN VAD 推理与 Python binding，支持离线、流式和纯 CPU 模式。 | [项目 README](https://github.com/di-osc/vad-burn#readme) 和 FunASR showcase [#3106](https://github.com/modelscope/FunASR/issues/3106)。 |