#!/usr/bin/env python3 """Prepare and optionally upload current ModelScope model-card guidance. The script keeps high-traffic ModelScope cards aligned with the FunASR GitHub README and PyPI release guidance. By default it writes patched README files to a local output directory. Use --upload with a ModelScope access token to publish only those README files back to their model repositories. """ from __future__ import annotations import argparse from dataclasses import dataclass from pathlib import Path from typing import Iterable DEFAULT_SOURCE_ROOT = Path( "/cpfs_speech/user/zhifu.gzf/.cache/funasr-ops/modelscope-card-audit-20260723/models" ) DEFAULT_OUTPUT_ROOT = Path( "/cpfs_speech/user/zhifu.gzf/.cache/funasr-ops/modelscope-card-sync-20260723" ) @dataclass(frozen=True) class CardPatch: repo_id: str source: Path path_in_repo: str replacements: tuple[tuple[str, str], ...] markers: tuple[str, ...] def output_path(self, output_root: Path) -> Path: return output_root / self.repo_id.replace("/", "__") / self.path_in_repo def _patches(source_root: Path) -> tuple[CardPatch, ...]: nano_en_env_old = """# Environment Setup 🐍 ```shell git clone https://github.com/QwenAudio/Fun-ASR.git cd Fun-ASR pip install -r requirements.txt ```""" nano_en_env_new = """# Environment Setup 🐍 Use FunASR v1.3.26 or newer for the current ModelScope hub path, OpenAI-compatible server, and vLLM fallback fixes: ```shell python -m pip install -U "funasr>=1.3.26" modelscope ``` For GPU inference, install the PyTorch / torchaudio CUDA wheels that match your driver from [pytorch.org](https://pytorch.org/get-started/locally/) and verify CUDA before using `device="cuda"`: ```python import torch print(torch.__version__, torch.version.cuda, torch.cuda.is_available()) ``` Optional demo repository setup: ```shell git clone https://github.com/QwenAudio/Fun-ASR.git cd Fun-ASR pip install -r requirements.txt ```""" nano_zh_env_old = """# 环境安装 🐍 ```shell git clone https://github.com/QwenAudio/Fun-ASR.git cd Fun-ASR pip install -r requirements.txt ```""" nano_zh_env_new = """# 环境安装 🐍 推荐使用 FunASR v1.3.26 或更新版本，以获得当前 ModelScope hub 路径、OpenAI 兼容服务和 vLLM fallback 修复： ```shell python -m pip install -U "funasr>=1.3.26" modelscope ``` GPU 推理前，请按 [PyTorch 官网](https://pytorch.org/get-started/locally/)安装与你驱动匹配的 PyTorch / torchaudio CUDA wheel，并先确认 CUDA 可见： ```python import torch print(torch.__version__, torch.version.cuda, torch.cuda.is_available()) ``` 如需运行 demo 仓库，可再执行： ```shell git clone https://github.com/QwenAudio/Fun-ASR.git cd Fun-ASR pip install -r requirements.txt ```""" sensevoice_env_old = """推理之前，请务必更新funasr与modelscope版本 ```shell pip install -U funasr modelscope ```""" sensevoice_env_new = """推理之前，请务必更新 funasr 与 modelscope 版本。推荐使用 FunASR v1.3.26 或更新版本，以获得当前命令行、OpenAI 兼容服务、字幕输出和 ModelScope hub 路径修复： ```shell python -m pip install -U "funasr>=1.3.26" modelscope ``` GPU 推理前，请按 [PyTorch 官网](https://pytorch.org/get-started/locally/)安装与你驱动匹配的 PyTorch / torchaudio CUDA wheel，并先确认 CUDA 可见： ```python import torch print(torch.__version__, torch.version.cuda, torch.cuda.is_available()) ```""" return ( CardPatch( repo_id="FunAudioLLM/Fun-ASR-Nano-2512", source=source_root / "FunAudioLLM--Fun-ASR-Nano-2512/snapshots/master/README.md", path_in_repo="README.md", replacements=( (nano_en_env_old, nano_en_env_new), ( "## Quick start via ModelScope\n```shell\npip install -U funasr modelscope\n```", "## Quick start via ModelScope\n```shell\npython -m pip install -U \"funasr>=1.3.26\" modelscope\n```", ), ), markers=("funasr>=1.3.26", "torch.cuda.is_available()", "Quick start via ModelScope"), ), CardPatch( repo_id="FunAudioLLM/Fun-ASR-Nano-2512", source=source_root / "FunAudioLLM--Fun-ASR-Nano-2512/snapshots/master/README_zh.md", path_in_repo="README_zh.md", replacements=((nano_zh_env_old, nano_zh_env_new),), markers=("funasr>=1.3.26", "torch.cuda.is_available()", "环境安装"), ), CardPatch( repo_id="iic/SenseVoiceSmall", source=source_root / "iic--SenseVoiceSmall/snapshots/master/README.md", path_in_repo="README.md", replacements=( (sensevoice_env_old, sensevoice_env_new), ( "#安装ModelScope\npip install modelscope", "# 安装 ModelScope 与 FunASR\npython -m pip install -U \"funasr>=1.3.26\" modelscope", ), ), markers=("funasr>=1.3.26", "torch.cuda.is_available()", "OpenAI 兼容"), ), ) def prepare_cards(source_root: Path, output_root: Path) -> list[CardPatch]: prepared: list[CardPatch] = [] for patch in _patches(source_root): if not patch.source.exists(): raise FileNotFoundError(f"missing source card: {patch.source}") text = patch.source.read_text() for old, new in patch.replacements: if old not in text: raise ValueError(f"expected text not found in {patch.source}: {old[:80]!r}") text = text.replace(old, new) missing = [marker for marker in patch.markers if marker not in text] if missing: raise ValueError(f"prepared {patch.repo_id}:{patch.path_in_repo} missing {missing}") destination = patch.output_path(output_root) destination.parent.mkdir(parents=True, exist_ok=True) destination.write_text(text) prepared.append(patch) return prepared def upload_cards(prepared: Iterable[CardPatch], output_root: Path, token: str) -> None: try: from modelscope.hub.api import HubApi except ImportError as exc: # pragma: no cover - depends on ops environment raise SystemExit("Install modelscope before using --upload") from exc api = HubApi() for patch in prepared: local_path = patch.output_path(output_root) print(f"uploading {patch.repo_id}:{patch.path_in_repo}") api.upload_file( repo_id=patch.repo_id, path_or_fileobj=str(local_path), path_in_repo=patch.path_in_repo, repo_type="model", token=token, commit_message="Update FunASR quickstart guidance", commit_description=( "Sync model-card install guidance to funasr>=1.3.26 and add " "CUDA wheel verification notes." ), revision="master", disable_tqdm=True, ) def parse_args() -> argparse.Namespace: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("--source-root", type=Path, default=DEFAULT_SOURCE_ROOT) parser.add_argument("--output-root", type=Path, default=DEFAULT_OUTPUT_ROOT) parser.add_argument("--upload", action="store_true", help="upload prepared README files to ModelScope") parser.add_argument("--token-file", type=Path, help="ModelScope access token file for --upload") parser.add_argument("--token", help="ModelScope access token for --upload") return parser.parse_args() def main() -> int: args = parse_args() prepared = prepare_cards(args.source_root, args.output_root) for patch in prepared: print(f"prepared {patch.repo_id}:{patch.path_in_repo} -> {patch.output_path(args.output_root)}") if args.upload: token = args.token or (args.token_file.read_text().strip() if args.token_file else "") if not token: raise SystemExit("--upload requires --token or --token-file") upload_cards(prepared, args.output_root, token) return 0 if __name__ == "__main__": raise SystemExit(main())