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aliyun-qwen-asraliyun Qwen ASR 命令行

Agent Skill

aliyun-qwen-asr 用于辅助部署、云资源、容器和基础设施运维,适合在 OpenClaw 中需要检查配置、整理部署步骤或排查环境问题时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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2,995

周安装

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GitHub Stars

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下载量

970
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:aliyun-qwen-asr(aliyun Qwen ASR 命令行)
来源仓库:https://github.com/cinience/aliyun-qwen-asr
安装命令:
openclaw skills install aliyun-qwen-asr
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install aliyun-qwen-asr

简介

调用阿里云 Qwen ASR 模型转录非实时语音文件为文字。

  • 适用于会议纪要、字幕生成与语音数据结构化转换。
  • 上传音频文件,返回时间戳对齐的文本转录结果。
  • 安装命令:openclaw skills install aliyun-qwen-asr;支持多种音频格式但音质影响识别率。
  • 长音频建议分段处理,避免单次请求超时或费用过高。

SKILL.md

name
aliyun-qwen-asr
description
Use when transcribing non-realtime speech with Alibaba Cloud Model Studio Qwen ASR models (qwen3-asr-flash, qwen-audio-asr, qwen3-asr-flash-filetrans). Use when converting recorded audio files to text, generating transcripts with timestamps, or documenting DashScope/OpenAI-compatible ASR request and response fields.
version
1.0.0

Category: provider

Model Studio Qwen ASR (Non-Realtime)

Validation

mkdir -p output/aliyun-qwen-asr
python -m py_compile skills/ai/audio/aliyun-qwen-asr/scripts/transcribe_audio.py && echo "py_compile_ok" > output/aliyun-qwen-asr/validate.txt

Pass criteria: command exits 0 and output/aliyun-qwen-asr/validate.txt is generated.

Output And Evidence

  • Store transcripts and API responses under output/aliyun-qwen-asr/.
  • Keep one command log or sample response per run.

Use Qwen ASR for recorded audio transcription (non-realtime), including short audio sync calls and long audio async jobs.

Critical model names

Use one of these exact model strings:

  • qwen3-asr-flash
  • qwen3-asr-flash-2026-02-10
  • qwen-audio-asr
  • qwen3-asr-flash-filetrans
  • qwen3-asr-flash-filetrans-2025-11-17

Selection guidance:

  • Use qwen3-asr-flash, qwen3-asr-flash-2026-02-10, or qwen-audio-asr for short/normal recordings (sync).
  • Use qwen3-asr-flash-filetrans or qwen3-asr-flash-filetrans-2025-11-17 for long-file transcription (async task workflow).

Prerequisites

  • Install SDK dependencies (script uses Python stdlib only):
python3 -m venv .venv
. .venv/bin/activate
  • Set DASHSCOPE_API_KEY in environment, or add dashscope_api_key to ~/.alibabacloud/credentials.

Normalized interface (asr.transcribe)

Request

  • audio (string, required): public URL or local file path.
  • model (string, optional): default qwen3-asr-flash.
  • language_hints (array<string>, optional): e.g. zh, en.
  • sample_rate (number, optional)
  • vocabulary_id (string, optional)
  • disfluency_removal_enabled (bool, optional)
  • timestamp_granularities (array<string>, optional): e.g. sentence.
  • async (bool, optional): default false for sync models, true for qwen3-asr-flash-filetrans.

Response

  • text (string): normalized transcript text.
  • task_id (string, optional): present for async submission.
  • status (string): SUCCEEDED or submission status.
  • raw (object): original API response.

Quick start (official HTTP API)

Sync transcription (OpenAI-compatible protocol):

curl -sS --location 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions' \
  --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "qwen3-asr-flash",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "input_audio",
            "input_audio": {
              "data": "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3"
            }
          }
        ]
      }
    ],
    "stream": false,
    "asr_options": {
      "enable_itn": false
    }
  }'

Async long-file transcription (DashScope protocol):

curl -sS --location 'https://dashscope.aliyuncs.com/api/v1/services/audio/asr/transcription' \
  --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
  --header 'X-DashScope-Async: enable' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "qwen3-asr-flash-filetrans",
    "input": {
      "file_url": "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3"
    }
  }'

Poll task result:

curl -sS --location "https://dashscope.aliyuncs.com/api/v1/tasks/<task_id>" \
  --header "Authorization: Bearer $DASHSCOPE_API_KEY"

Local helper script

Use the bundled script for URL/local-file input and optional async polling:

python skills/ai/audio/aliyun-qwen-asr/scripts/transcribe_audio.py \
  --audio "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3" \
  --model qwen3-asr-flash \
  --language-hints zh,en \
  --print-response

Long-file mode:

python skills/ai/audio/aliyun-qwen-asr/scripts/transcribe_audio.py \
  --audio "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3" \
  --model qwen3-asr-flash-filetrans \
  --async \
  --wait

Operational guidance

  • For local files, use input_audio.data (data URI) when direct URL is unavailable.
  • Keep language_hints minimal to reduce recognition ambiguity.
  • For async tasks, use 5-20s polling interval with max retry guard.
  • Save normalized outputs under output/aliyun-qwen-asr/transcripts/.

Output location

  • Default output: output/aliyun-qwen-asr/transcripts/
  • Override base dir with OUTPUT_DIR.

Workflow

1) Confirm user intent, region, identifiers, and whether the operation is read-only or mutating. 2) Run one minimal read-only query first to verify connectivity and permissions. 3) Execute the target operation with explicit parameters and bounded scope. 4) Verify results and save output/evidence files.

References

  • references/api_reference.md
  • references/sources.md
  • Realtime synthesis is provided by skills/ai/audio/aliyun-qwen-tts-realtime/.

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