feat(moss): add SGLang AutoModel backend

docs/deployment_matrix.md

@@ -15,7 +15,7 @@ Use this page to choose the shortest deployment path for a product, demo, benchm
 | Runtime WebSocket service | Live captions, meetings, call-center streams | [Runtime service docs](../runtime/readme.md) | Use when partial results, endpointing, or long-lived audio streams matter. |
 | ONNX/C++ runtime | High-concurrency CPU services or embedded realtime ASR | [ONNX runtime docs](../runtime/onnxruntime/readme.md) | Keep this path when latency/concurrency is already proven; add text post-processing for fixed business terms before moving to GPU LLMs. |
 | vLLM acceleration | Higher-throughput LLM-based ASR with Fun-ASR-Nano | [vLLM guide](./vllm_guide.md) | Use for LLM decoder throughput; does not apply to non-autoregressive Paraformer. |
-| MOSS-Transcribe-Diarize | Long-form multi-speaker transcription with timestamps and speaker labels | [Third-party MOSS deployment guide](./moss_transcribe_diarize.md) | OpenMOSS Apache-2.0 model integrated with FunASR `AutoModel`; choose local HF (`backend="hf"`) or vLLM (`backend="vllm"`), or serve it independently through native SGLang Omni. SGLang Omni is not an `AutoModel` backend. The model remains published and maintained by OpenMOSS. |
+| MOSS-Transcribe-Diarize | Long-form multi-speaker transcription with timestamps and speaker labels | [Third-party MOSS deployment guide](./moss_transcribe_diarize.md) | OpenMOSS Apache-2.0 model integrated with FunASR `AutoModel`; choose local HF (`backend="hf"`), vLLM (`backend="vllm"`), or SGLang Omni (`backend="sglang"`). The model remains published and maintained by OpenMOSS. |
 | MCP server | Claude/Cursor/desktop agent speech tools | [MCP example](../examples/mcp_server/) | Good when the ASR result should be exposed as a local tool. |
 | Subtitle generator | SRT/VTT from long audio or video | [Subtitle example](../examples/subtitle/) | Use verbose segments and speaker labels when readability matters. |
 | Batch ASR script | Archives, meetings, datasets, repeated offline runs | [Batch example](../examples/batch_asr_improved.py) | Add queueing, manifests, and retry logs for production use. |

docs/deployment_matrix_ja.md

@@ -13,7 +13,7 @@
 | Kubernetes API | Cluster service 向け internal speech API | [Kubernetes template](../examples/openai_api/kubernetes/) | private `ClusterIP` から開始。公開範囲を広げる前に auth、TLS、network policy、GPU scheduling を追加します。 |
 | Runtime WebSocket service | Live captions、meeting、call-center stream | [Runtime service docs](../runtime/readme.md) | partial result、endpointing、long-lived audio stream が重要な場合に使います。 |
 | vLLM acceleration | Fun-ASR-Nano の LLM-based ASR throughput 向上 | [vLLM guide](./vllm_guide.md) | LLM decoder throughput 向け。non-autoregressive Paraformer には適用しません。 |
-| MOSS-Transcribe-Diarize | 長時間の複数話者 transcription、timestamp、speaker label | [Third-party MOSS guide](./moss_transcribe_diarize.md) | OpenMOSS の Apache-2.0 model を FunASR `AutoModel` に統合済みです。local HF（`backend="hf"`）または vLLM（`backend="vllm"`）を選択でき、native SGLang Omni から独立して serve することもできます。SGLang Omni は `AutoModel` backend ではなく、model の公開・保守主体は OpenMOSS のままです。 |
+| MOSS-Transcribe-Diarize | 長時間の複数話者 transcription、timestamp、speaker label | [Third-party MOSS guide](./moss_transcribe_diarize.md) | OpenMOSS の Apache-2.0 model を FunASR `AutoModel` に統合済みです。local HF（`backend="hf"`）、vLLM（`backend="vllm"`）、または SGLang Omni（`backend="sglang"`）を選択できます。model の公開・保守主体は OpenMOSS のままです。 |
 | MCP server | Claude/Cursor/desktop agent の speech tool | [MCP example](../examples/mcp_server/) | ASR 結果を local tool として Agent に渡したい場合に便利です。 |
 | Subtitle generator | 長時間 audio/video から SRT/VTT 作成 | [Subtitle example](../examples/subtitle/) | readability が重要な場合は verbose segment と speaker label を使います。 |
 | Batch ASR script | Archive、meeting、dataset、繰り返し offline run | [Batch example](../examples/batch_asr_improved.py) | production では queue、manifest、retry log を追加してください。 |

docs/deployment_matrix_ko.md

@@ -13,7 +13,7 @@
 | Kubernetes API | Cluster service용 internal speech API | [Kubernetes template](../examples/openai_api/kubernetes/) | private `ClusterIP`부터 시작합니다. 범위를 넓히기 전에 auth, TLS, network policy, GPU scheduling을 추가하세요. |
 | Runtime WebSocket service | Live captions, meeting, call-center stream | [Runtime service docs](../runtime/readme.md) | partial result, endpointing, long-lived audio stream이 중요할 때 사용합니다. |
 | vLLM acceleration | Fun-ASR-Nano의 LLM-based ASR throughput 향상 | [vLLM guide](./vllm_guide.md) | LLM decoder throughput용입니다. non-autoregressive Paraformer에는 적용되지 않습니다. |
-| MOSS-Transcribe-Diarize | 긴 다중 화자 transcription, timestamp, speaker label | [Third-party MOSS guide](./moss_transcribe_diarize.md) | OpenMOSS의 Apache-2.0 model이며 FunASR `AutoModel`에 통합되어 있습니다. local HF(`backend="hf"`) 또는 vLLM(`backend="vllm"`)을 선택하거나 native SGLang Omni에서 독립적으로 serve할 수 있습니다. SGLang Omni는 `AutoModel` backend가 아니며, model의 공개 및 유지 관리는 계속 OpenMOSS가 담당합니다. |
+| MOSS-Transcribe-Diarize | 긴 다중 화자 transcription, timestamp, speaker label | [Third-party MOSS guide](./moss_transcribe_diarize.md) | OpenMOSS의 Apache-2.0 model이며 FunASR `AutoModel`에 통합되어 있습니다. local HF(`backend="hf"`), vLLM(`backend="vllm"`) 또는 SGLang Omni(`backend="sglang"`)를 선택할 수 있습니다. model의 공개 및 유지 관리는 계속 OpenMOSS가 담당합니다. |
 | MCP server | Claude/Cursor/desktop agent speech tool | [MCP example](../examples/mcp_server/) | ASR 결과를 local tool로 Agent에 전달할 때 유용합니다. |
 | Subtitle generator | 긴 audio/video에서 SRT/VTT 생성 | [Subtitle example](../examples/subtitle/) | readability가 중요하면 verbose segment와 speaker label을 사용합니다. |
 | Batch ASR script | Archive, meeting, dataset, 반복 offline run | [Batch example](../examples/batch_asr_improved.py) | production에서는 queue, manifest, retry log를 추가하세요. |

docs/deployment_matrix_zh.md

@@ -15,7 +15,7 @@
 | Runtime WebSocket 服务 | 实时字幕、会议、客服流式音频 | [Runtime 服务文档](../runtime/readme_cn.md) | 需要中间结果、断句或长连接音频流时选择。 |
 | ONNX/C++ Runtime | 高并发 CPU 服务或嵌入式实时 ASR | [ONNX Runtime 文档](../runtime/onnxruntime/readme.md) | 如果延迟和并发已经验证，不要轻易替换；固定业务词优先做文本后处理。 |
 | vLLM 加速 | Fun-ASR-Nano 等 LLM-based ASR 高吞吐 | [vLLM 指南](./vllm_guide.md) | 适合 LLM 解码吞吐；不适用于非自回归 Paraformer。 |
-| MOSS-Transcribe-Diarize | 长音频多人转写、时间戳和说话人标签 | [第三方 MOSS 部署指南](./moss_transcribe_diarize.md) | OpenMOSS Apache-2.0 模型，已接入 FunASR `AutoModel`；可选本地 HF（`backend="hf"`）或 vLLM（`backend="vllm"`），也可通过原生 SGLang Omni 独立服务。SGLang Omni 不是 `AutoModel` backend。模型仍由 OpenMOSS 发布和维护。 |
+| MOSS-Transcribe-Diarize | 长音频多人转写、时间戳和说话人标签 | [第三方 MOSS 部署指南](./moss_transcribe_diarize.md) | OpenMOSS Apache-2.0 模型，已接入 FunASR `AutoModel`；可选本地 HF（`backend="hf"`）、vLLM（`backend="vllm"`）或 SGLang Omni（`backend="sglang"`）。模型仍由 OpenMOSS 发布和维护。 |
 | MCP 服务 | Claude/Cursor/桌面 Agent 语音工具 | [MCP 示例](../examples/mcp_server/) | 适合把 ASR 结果暴露成一个本地工具。 |
 | 字幕生成 | 从长音频或视频生成 SRT/VTT | [字幕示例](../examples/subtitle/) | 需要可读性时使用 verbose segments 和说话人标签。 |
 | 批处理脚本 | 录音归档、会议纪要、数据集处理 | [批处理示例](../examples/batch_asr_improved.py) | 生产使用时建议增加队列、manifest 和重试日志。 |

docs/moss_transcribe_diarize.md

@@ -6,8 +6,8 @@ This guide connects the third-party
 [OpenMOSS/MOSS-Transcribe-Diarize](https://github.com/OpenMOSS/MOSS-Transcribe-Diarize)
 model to the FunASR deployment ecosystem. The model is published by OpenMOSS
 under Apache-2.0; it is not a FunASR model. FunASR provides an adapter for its
-public Transformers and vLLM interfaces while retaining the OpenMOSS model
-name, license, and upstream revision.
+public Transformers, vLLM, and SGLang Omni interfaces while retaining the
+OpenMOSS model name, license, and upstream revision.
 
 MOSS-Transcribe-Diarize jointly generates transcription, timestamps, and
 speaker labels such as `[S01]`. An application therefore does not need to
@@ -259,6 +259,16 @@ claims as measurements of your host.
 Follow the pinned upstream SGLang Omni installation guide for CUDA 13, then
 download the immutable model snapshot and serve the local directory:
 
+```bash
+git clone https://github.com/sgl-project/sglang-omni.git
+git -C sglang-omni checkout 3f819f9cdae3d4eeec22f73306c9067a1ec2542e
+```
+
+This source pin includes the transcription API's `max_new_tokens` forwarding.
+The original #914 merge predates that request field, so it is not sufficient
+for the long-audio command below even though its published H100 benchmark
+remains useful upstream evidence.
+
 ```bash
 hf download OpenMOSS-Team/MOSS-Transcribe-Diarize \
   --revision e8681d68e7042738ffca8ac8212bc8fcb1131ab8 \
@@ -287,6 +297,31 @@ current `verbose_json` contract, the speaker identifier is retained as the
 Parse and validate that prefix before wiring the response into subtitles,
 meeting notes, or analytics.
 
+The FunASR adapter performs that validation and maps the official SGLang
+segments into the same `sentence_info` contract as the HF and vLLM paths:
+
+```python
+from funasr import AutoModel
+
+model = AutoModel(
+    model="OpenMOSS-Team/MOSS-Transcribe-Diarize",
+    backend="sglang",
+    sglang_base_url="http://127.0.0.1:8898/v1",
+    sglang_model="OpenMOSS-Team/MOSS-Transcribe-Diarize",
+    max_new_tokens=65536,
+    disable_update=True,
+)
+result = model.generate(input="audio.wav", max_new_tokens=65536)[0]
+for segment in result["sentence_info"]:
+    print(segment["start"], segment["end"], segment["spk"], segment["text"])
+```
+
+Do not pass `vad_model` or `spk_model`: MOSS performs segmentation and
+anonymous speaker attribution jointly, and external splitting can destroy
+speaker consistency across long turns. The adapter preserves the upstream
+tagged transcript in `raw_text`, strips only the validated `[Sxx]` prefix from
+each normalized segment, and fails closed if SGLang omits that prefix.
+
 The native runtime was merged in SGLang Omni
 [#914](https://github.com/sgl-project/sglang-omni/pull/914). Its single-H100
 Seed-TTS EN benchmark completed 1088/1088 clips with no request failures. WER

docs/moss_transcribe_diarize_zh.md

@@ -5,8 +5,8 @@
 本文把第三方
 [OpenMOSS/MOSS-Transcribe-Diarize](https://github.com/OpenMOSS/MOSS-Transcribe-Diarize)
 模型接入 FunASR 部署生态。模型由 OpenMOSS 以 Apache-2.0 发布，不是 FunASR
-自有模型。FunASR 只为其公开的 Transformers 与 vLLM 接口提供适配器，并保留
-OpenMOSS 模型名称、许可证和上游 revision。
+自有模型。FunASR 为其公开的 Transformers、vLLM 与 SGLang Omni 接口提供适配器，
+并保留 OpenMOSS 模型名称、许可证和上游 revision。
 
 MOSS-Transcribe-Diarize 会联合生成转写、时间戳和 `[S01]` 等说话人标签，应用侧
 不必再拼接外部 VAD、ASR 和 diarization 管线。这里描述的是部署形态，不表示模型
@@ -231,6 +231,15 @@ LocalAI `master@a7cc5873ef5b7c909fc9ff7d349d51738ba9bb05` 已包含
 
 按固定上游 SGLang Omni 安装指南准备 CUDA 13 环境，然后下载不可变模型快照并从本地目录启动：
 
+```bash
+git clone https://github.com/sgl-project/sglang-omni.git
+git -C sglang-omni checkout 3f819f9cdae3d4eeec22f73306c9067a1ec2542e
+```
+
+该源码 pin 已把 `max_new_tokens` 传入 transcription 生成请求。最初的 #914
+merge 早于这个请求字段，因此虽然它的 H100 benchmark 仍可作为上游证据，却不能
+支撑下方长音频命令。
+
 ```bash
 hf download OpenMOSS-Team/MOSS-Transcribe-Diarize \
   --revision e8681d68e7042738ffca8ac8212bc8fcb1131ab8 \
@@ -257,6 +266,30 @@ curl -fsS http://127.0.0.1:8898/v1/audio/transcriptions \
 `verbose_json` 合同把说话人编号保留为 `segments[].text` 的 `[Sxx]` 前缀，
 并没有单独的 `speaker` 字段。接入字幕、会议纪要或分析系统前，应解析并校验此前缀。
 
+FunASR 适配器会完成该校验，并把 SGLang 官方 segments 映射为与 HF、vLLM
+一致的 `sentence_info` 合同：
+
+```python
+from funasr import AutoModel
+
+model = AutoModel(
+    model="OpenMOSS-Team/MOSS-Transcribe-Diarize",
+    backend="sglang",
+    sglang_base_url="http://127.0.0.1:8898/v1",
+    sglang_model="OpenMOSS-Team/MOSS-Transcribe-Diarize",
+    max_new_tokens=65536,
+    disable_update=True,
+)
+result = model.generate(input="audio.wav", max_new_tokens=65536)[0]
+for segment in result["sentence_info"]:
+    print(segment["start"], segment["end"], segment["spk"], segment["text"])
+```
+
+不要传入 `vad_model` 或 `spk_model`：MOSS 在一次生成中联合完成分段和匿名说话人
+归属，外部分段会破坏长轮次中的说话人一致性。适配器把上游带标签原文保存在
+`raw_text`，只从标准化 segment 中移除已经校验的 `[Sxx]` 前缀；如果 SGLang
+没有返回此前缀，则明确失败，不会伪造说话人身份。
+
 原生 runtime 已通过 SGLang Omni
 [#914](https://github.com/sgl-project/sglang-omni/pull/914) 合并。其单张 H100
 Seed-TTS EN benchmark 完成 1088/1088 条请求且无请求失败。WER 是在移除