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Dashscope

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calesthio
dashscope

DashScope (Alibaba Cloud Bailian / 阿里云百炼) integration — image generation (qwen-image-2.0-pro), text-to-speech (qwen3-tts-flash), and ASR with word-level timestamps (qwen3-asr-flash-filetrans). Use when generating images via Qwen-Image, narrating via Qwen-TTS, or transcribing with word-level timestamps via Qwen-ASR.

Overview

Publishercalesthio
RepositoryOpenMontage
Skill namedashscope
Stars
67K
Forks
8.5K
Bundled files
Instructions only
LicenseAGPL-3.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by calesthio on GitHub. Read the source before you install it.

Installation

Install the Dashscope AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/dashscope
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/calesthio/OpenMontage.git /tmp/OpenMontage
mkdir -p .claude/skills
cp -r /tmp/OpenMontage/.agents/skills/dashscope .claude/skills/dashscope
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dashscope in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dashscope on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dashscope is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

DashScope

Requires DASHSCOPE_API_KEY in .env. Get one at https://dashscope.aliyun.com/.

Current API

CRITICAL: DashScope's /compatible-mode/v1/ only supports /chat/completions and /embeddings. Image generation, TTS, and ASR all use DashScope-native endpoints — not OpenAI-compatible paths.

All three tools use Authorization: Bearer $DASHSCOPE_API_KEY.

Image Generation

text
POST https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation
  • Model: qwen-image-2.0-pro (default), qwen-image-max, wan2.7-image, z-image-turbo
  • Body: {model, input: {messages: [{role: "user", content: [{text: "prompt"}]}]}, parameters: {size: "W*H", n, prompt_extend, watermark}}
  • Size format uses asterisk: "1024*1024" not "1024x1024"
  • Response: output.choices[0].message.content[0].image (URL, valid ~24h) — must download separately

Text-to-Speech

text
POST https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

Same endpoint as image gen, different body.

  • Model: qwen3-tts-flash (default), qwen3-tts-instruct-flash, qwen-tts-2025-05-22
  • Body: {model, input: {text, voice: "Cherry", language_type: "Auto"}}
  • Response: output.audio.url (WAV, valid ~24h) — must download separately

ASR with Word-Level Timestamps

text
POST https://dashscope.aliyuncs.com/api/v1/services/audio/asr/transcription
Header: X-DashScope-Async: enable
  • Model: qwen3-asr-flash-filetrans (NOT qwen3-asr-flash — the sync version has no word timestamps)
  • Body: {model, input: {file_url: "https://public-url/audio.mp3"}, parameters: {enable_words: true, language_hints: ["zh","en"]}}
  • Returns task_id → poll GET /api/v1/tasks/{task_id} until SUCCEEDED → download output.result.transcription_url → JSON with transcripts[].sentences[].words[]
  • Timestamps in begin_time/end_time are in milliseconds — the tool normalizes to seconds

OpenMontage Usage

Image via selector

python
from tools.graphics.image_selector import ImageSelector

result = ImageSelector().execute({
    "preferred_provider": "dashscope",
    "prompt": "一只猫坐在沙发上",
    "output_path": "projects/my-video/assets/images/cat.png",
})

TTS via selector

python
from tools.audio.tts_selector import TTSSelector

result = TTSSelector().execute({
    "preferred_provider": "dashscope",
    "text": "如果 AI 真的会改变未来,普通人到底该怎么参与?",
    "voice": "Cherry",
    "output_path": "projects/my-video/assets/audio/narration.wav",
})

ASR directly (word timestamps for subtitles)

python
from tools.analysis.dashscope_asr import DashscopeAsr

result = DashscopeAsr().execute({
    "audio_url": "https://example.com/narration.wav",
    "output_path": "projects/my-video/assets/audio/transcription.json",
})

# result.data["words"] is a flat list of {text, begin_time_seconds, end_time_seconds}

Recommended Workflow

  1. Image: Generate a sample first. Check prompt_extend: true (default) — DashScope rewrites your prompt for better results. Disable if you need literal prompt adherence.
  2. TTS: Generate a 10-15 second sample before full narration. Approve voice and pacing before committing to full generation.
  3. ASR: Audio must be at a publicly accessible URL. Upload to any public host (S3, etc.) first. Local paths are rejected with a clear error.
  4. Subtitles: Build from result.data["words"] — each word has begin_time_seconds and end_time_seconds. Group words into caption phrases by language semantics, not fixed character count.

Parameters

Image (dashscope_image)

  • prompt (required): text prompt
  • model: default qwen-image-2.0-pro
  • size: default "1024*1024" — asterisk separator, not "x"
  • n: 1-6 images
  • negative_prompt: things to avoid (max 500 chars)
  • prompt_extend: default true — auto-rewrite prompt for better results
  • watermark: default false
  • seed: for reproducibility

TTS (dashscope_tts)

  • text (required): text to synthesize (max 600 chars for qwen3-tts-flash)
  • model: default qwen3-tts-flash
  • voice: default "Cherry" — other voices: "Ethan", "Chelsie", etc.
  • language_type: default "Auto" — "Chinese", "English", "Japanese", "Korean"
  • instructions: natural language delivery instructions (only for qwen3-tts-instruct-flash)

ASR (dashscope_asr)

  • audio_url (required): must be publicly accessible URL
  • model: qwen3-asr-flash-filetrans (only model that supports word timestamps)
  • language_hints: default ["zh", "en"]
  • enable_words: default true — required for word-level timestamps
  • poll_interval_seconds: default 5.0
  • timeout_seconds: default 300

Troubleshooting

  • Image size error: Use "W*H" with asterisk, not "WxH". Example: "2048*2048".
  • TTS no audio URL: Check output.audio.url — if empty, the model name or voice may be wrong.
  • ASR "file not accessible": audio_url must be publicly reachable. DashScope servers fetch the file; local paths and auth-gated URLs don't work.
  • ASR poll timeout: Increase timeout_seconds (default 300). Long audio files take longer to transcribe.
  • ASR no word timestamps: Ensure enable_words: true and model is qwen3-asr-flash-filetrans (not the sync qwen3-asr-flash).
  • Auth error (401): Verify DASHSCOPE_API_KEY is set. Use Authorization: Bearer $KEY header.

Safety

Never print or write the API key to logs, metadata, patches, or project artifacts. .env.example should contain only empty variable names. The tool's _safe_error() method redacts the key from error messages.

Frequently asked questions

What does the Dashscope AI skill do?

DashScope (Alibaba Cloud Bailian / 阿里云百炼) integration — image generation (qwen-image-2.0-pro), text-to-speech (qwen3-tts-flash), and ASR with word-level timestamps (qwen3-asr-flash-filetrans). Use when generating images via Qwen-Image, narrating via Qwen-TTS, or transcribing with word-level timestamps via Qwen-ASR.

Why use Dashscope on TypingMind?

Because you install it once and use it with any model. Dashscope is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dashscope in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/dashscope. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dashscope?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dashscope?

As many as you like. As long as a model supports skills, you can use Dashscope with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dashscope AI skill free?

Yes. It is published on GitHub by calesthio under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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