Skill: cinience/aliyun-qwen-tts (version 1.0.0)

--- name: aliyun-qwen-tts description: Use when generating human-like speech audio with Model Studio DashScope Qwen TTS models (qwen3-tts-flash, qwen3-tts-instruct-flash). Use when converting text to speech, producing voice lines for short drama/news videos, or documenting TTS request/response fields for DashScope. version: 1.0.0 --- Category: provider # Model Studio Qwen TTS ## Validation ```bash mkdir -p output/aliyun-qwen-tts python -m py_compile skills/ai/audio/aliyun-qwen-tts/scripts/generate_tts.py && echo "py_compile_ok" > output/aliyun-qwen-tts/validate.txt ``` Pass criteria: command exits 0 and `output/aliyun-qwen-tts/validate.txt` is generated. ## Output And Evidence - Save generated audio links, sample audio files, and request payloads to `output/aliyun-qwen-tts/`. - Keep one validation log per execution. ## Critical model names Use one of the recommended models: - `qwen3-tts-flash` - `qwen3-tts-instruct-flash` - [REDACTED_SECRET] ## Prerequisites - Install SDK (recommended in a venv to avoid PEP 668 limits): ```bash python3 -m venv .venv . .venv/bin/activate python -m pip install dashscope ``` - Set `DASHSCOPE_API_KEY` in your environment, or add `dashscope_api_key` to `~/.alibabacloud/credentials` (env takes precedence). ## Normalized interface (tts.generate) ### Request - `text` (string, required) - `voice` (string, required) - `language_type` (string, optional; default `Auto`) - `instruction` (string, optional; recommended for instruct models) - `stream` (bool, optional; default false) ### Response - `audio_url` (string, when stream=false) - `audio_base64_pcm` (string, when stream=true) - `sample_rate` (int, 24000) - `format` (string, wav or pcm depending on mode) ## Quick start (Python + DashScope SDK) ```python import os import dashscope # Prefer env var for auth: export DASHSCOPE_API_KEY=... # Or use ~/.alibabacloud/credentials with dashscope_api_key under [default]. # Beijing region; for Singapore use: https://dashscope-intl.aliyuncs.com/api/v1 dashscope.base_http_api_url = "https://dashscope.aliyuncs.com/api/v1" text = "Hello, this is a short voice line." response = dashscope.MultiModalConversation.call( model="qwen3-tts-instruct-flash", [REDACTED_SECRET]"DASHSCOPE_API_KEY"), text=text, voice="Cherry", language_type="English", instruction="Warm and calm tone, slightly slower pace.", stream=False, ) audio_url = response.output.audio.url print(audio_url) ``` ## Streaming notes - `stream=True` returns Base64-encoded PCM chunks at 24kHz. - Decode chunks and play or concatenate to a pcm buffer. - The response contains `finish_reason == "stop"` when the stream ends. ## Operational guidance - Keep requests concise; split long text into multiple calls if you hit size or timeout errors. - Use `language_type` consistent with the text to improve pronunciation. - Use `instruction` only when you need explicit style/tone control. - Cache by `(text, voice, language_type)` to avoid repeat costs. ## Output location - Default output: `output/aliyun-qwen-tts/audio/` - 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` for parameter mapping and streaming example. - Realtime mode is provided by `skills/ai/audio/aliyun-qwen-tts-realtime/`. - Voice cloning/design are provided by `skills/ai/audio/aliyun-qwen-tts-voice-clone/` and `skills/ai/audio/aliyun-qwen-tts-voice-design/`. - Source list: `references/sources.md`


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