release: prepare v1.4.14

Signed-off-by: zhifu.gzf <[email protected]>

README.md

@@ -341,7 +341,7 @@ inference on physical Blackwell hardware.
 ## What's new
 
 - **MOSS-Transcribe-Diarize** brings long-form ASR, timestamps, and anonymous speaker labels to FunASR services, Docker, Kubernetes, vLLM/SGLang workflows, and FunClip. [Deploy MOSS ->](./docs/moss_transcribe_diarize.md)
-- **FunASR 1.4.13** pins the core NumPy dependency below 2 to prevent binary ABI import failures. Install with `python -m pip install -U "funasr==1.4.13"`. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.13)
+- **FunASR 1.4.14** completes MOSS service and Model Zoo discovery, and improves realtime serving stability while retaining the NumPy ABI safeguard. Install with `python -m pip install -U "funasr==1.4.14"`. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.14)
 - **Production deployment** now includes faster, more resilient realtime serving and verified llama.cpp archives for ten Linux, macOS, and Windows targets. [GPU services ->](./docs/vllm_guide.md) · [CPU/edge packages ->](https://www.funasr.com/en/deploy/llama-cpp.html)
 
 > See [GitHub Releases](https://github.com/modelscope/FunASR/releases) for the complete changelog and downloadable assets.

README_ja.md

@@ -100,7 +100,7 @@ Whisper は単一モデルですが、**FunASR はツールキット**です—
 ## 最新情報
 
 - **MOSS-Transcribe-Diarize** を FunASR service、Docker、Kubernetes、vLLM/SGLang workflow、FunClip に統合し、長時間 ASR、timestamp、匿名 speaker label を一度に処理できます。[MOSS をデプロイ ->](./docs/moss_transcribe_diarize.md)
-- **FunASR 1.4.13** は、バイナリ ABI の import 失敗を避けるため、core NumPy 依存を 2 未満に固定します。`python -m pip install -U "funasr==1.4.13"`。[Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.13)
+- **FunASR 1.4.14** は MOSS の service / Model Zoo 導線を完成させ、realtime serving の安定性を改善しつつ NumPy ABI 保護を維持します。`python -m pip install -U "funasr==1.4.14"`。[Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.14)
 - **Production deployment** に、より高速で安定した realtime serving と、Linux、macOS、Windows の 10 target 向け llama.cpp package を追加しました。[GPU service ->](./docs/vllm_guide.md) · [CPU / edge package ->](https://www.funasr.com/en/deploy/llama-cpp.html) · [v0.2.6 binaries ->](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.6)
 
 > 完全な変更履歴と download asset は [GitHub Releases](https://github.com/modelscope/FunASR/releases) を参照してください。

README_ko.md

@@ -100,7 +100,7 @@ Whisper는 단일 모델이지만, **FunASR는 툴킷**입니다. 용도에 맞
 ## 최신 소식
 
 - **MOSS-Transcribe-Diarize**를 FunASR service, Docker, Kubernetes, vLLM/SGLang workflow, FunClip에 통합해 긴 오디오 ASR, timestamp, 익명 speaker label을 한 번에 처리합니다. [MOSS 배포 ->](./docs/moss_transcribe_diarize.md)
-- **FunASR 1.4.13**은 바이너리 ABI import 실패를 막기 위해 core NumPy 의존성을 2 미만으로 고정합니다. `python -m pip install -U "funasr==1.4.13"`. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.13)
+- **FunASR 1.4.14**는 MOSS service / Model Zoo 진입점을 완성하고 realtime serving 안정성을 개선하며 NumPy ABI 보호를 유지합니다. `python -m pip install -U "funasr==1.4.14"`. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.14)
 - **Production deployment**에 더 빠르고 안정적인 realtime serving과 Linux, macOS, Windows 10개 target용 llama.cpp package를 추가했습니다. [GPU service ->](./docs/vllm_guide.md) · [CPU / edge package ->](https://www.funasr.com/en/deploy/llama-cpp.html) · [v0.2.6 binaries ->](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.6)
 
 > 전체 변경 기록과 download asset은 [GitHub Releases](https://github.com/modelscope/FunASR/releases)에서 확인할 수 있습니다.

README_zh.md

@@ -152,7 +152,7 @@ Whisper 是单个模型，**FunASR 是一个工具箱**——按场景挑模型
 ## 最新动态
 
 - **MOSS-Transcribe-Diarize** 已接入 FunASR 服务、Docker、Kubernetes、vLLM/SGLang 工作流和 FunClip，一次完成长音频转写、时间戳与匿名说话人标注。[部署 MOSS ->](./docs/moss_transcribe_diarize_zh.md)
-- **FunASR 1.4.13** 将核心 NumPy 依赖限定在 2 以下，避免二进制 ABI 导入失败。升级命令：`python -m pip install -U "funasr==1.4.13"`。[发布页 ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.13)
+- **FunASR 1.4.14** 补齐 MOSS 服务与 Model Zoo 入口，提升实时服务稳定性，并保留 NumPy ABI 兼容保护。升级命令：`python -m pip install -U "funasr==1.4.14"`。[发布页 ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.14)
 - **工业部署** 新增更快、更稳定的实时服务，以及覆盖 Linux、macOS、Windows 十种目标的 llama.cpp 预编译包。[GPU 服务 ->](./docs/vllm_guide_zh.md) · [CPU/端侧包 ->](https://www.funasr.com/deploy/llama-cpp.html)
 
 > 完整改动记录和可下载资产请查看 [GitHub Releases](https://github.com/modelscope/FunASR/releases)。

docs/repository_roles.md

@@ -5,7 +5,7 @@ This document explains the responsibility boundaries, user entry points, and iss
 > **Directional roadmap, not a release promise.**
 > This document records shipped capabilities and active work, but does not commit to
 > future version numbers or dates. The current Python release is
-> [`funasr==1.4.13`](https://github.com/modelscope/FunASR/releases/tag/v1.4.13).
+> [`funasr==1.4.14`](https://github.com/modelscope/FunASR/releases/tag/v1.4.14).
 > Any future breaking release still requires a maintainer-approved milestone and
 > migration plan.
 

docs/repository_roles_zh.md

@@ -4,7 +4,7 @@
 
 > **方向性路线图，不是版本承诺。**
 > 本文档记录已交付能力与正在推进的工作，但不承诺未来版本号或日期。当前 Python
-> 版本是 [`funasr==1.4.13`](https://github.com/modelscope/FunASR/releases/tag/v1.4.13)。
+> 版本是 [`funasr==1.4.14`](https://github.com/modelscope/FunASR/releases/tag/v1.4.14)。
 > 任何未来的 breaking release 仍需 maintainer 确认 milestone 与迁移方案。
 
 ---

funasr/version.txt

@@ -1 +1 @@
-1.4.13
+1.4.14

tests/test_release_version_contract.py

@@ -2,7 +2,7 @@ from pathlib import Path
 
 
 ROOT = Path(__file__).resolve().parents[1]
-RELEASE_VERSION = "1.4.13"
+RELEASE_VERSION = "1.4.14"
 README_FILES = ("README.md", "README_zh.md", "README_ja.md", "README_ko.md")
 REPOSITORY_ROLE_FILES = ("docs/repository_roles.md", "docs/repository_roles_zh.md")