Skill: cinience/alicloud-ai-audio-tts-realtime (version 1.0.1)

--- name: alicloud-ai-audio-tts-realtime description: Real-time speech synthesis with Alibaba Cloud Model Studio Qwen TTS Realtime models. Use when low-latency interactive speech is required, including instruction-controlled realtime synthesis. version: 1.0.0 --- Category: provider # Model Studio Qwen TTS Realtime Use realtime TTS models for low-latency streaming speech output. ## Critical model names Use one of these exact model strings: - `qwen3-tts-flash-realtime` - [REDACTED_SECRET] - [REDACTED_SECRET] - [REDACTED_SECRET] - [REDACTED_SECRET] ## Prerequisites - Install SDK in a virtual environment: ```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`. ## Normalized interface (tts.realtime) ### Request - `text` (string, required) - `voice` (string, required) - `instruction` (string, optional) - `sample_rate` (int, optional) ### Response - `audio_base64_pcm_chunks` (array<string>) - `sample_rate` (int) - `finish_reason` (string) ## Operational guidance - Use websocket or streaming endpoint for realtime mode. - Keep each utterance short for lower latency. - For instruction models, keep instruction explicit and concise. - Some SDK/runtime combinations may reject realtime model calls over `MultiModalConversation`; use the probe script below to verify compatibility. ## Local demo script Use the probe script to verify realtime compatibility in your current SDK/runtime, and optionally fallback to a non-realtime model for immediate output: ```bash .venv/bin/python skills/ai/audio/alicloud-ai-audio-tts-realtime/scripts/realtime_tts_demo.py \ --text "This is a realtime speech demo." \ --fallback \ --output output/ai-audio-tts-realtime/audio/fallback-demo.wav ``` Strict mode (for CI / gating): ```bash .venv/bin/python skills/ai/audio/alicloud-ai-audio-tts-realtime/scripts/realtime_tts_demo.py \ --text "realtime health check" \ --strict ``` ## Output location - Default output: [REDACTED_SECRET] - Override base dir with `OUTPUT_DIR`. ## Validation ```bash mkdir -p output/alicloud-ai-audio-tts-realtime for f in skills/ai/audio/alicloud-ai-audio-tts-realtime/scripts/*.py; do python3 -m py_compile "$f" done echo "py_compile_ok" > output/alicloud-ai-audio-tts-realtime/validate.txt ``` Pass criteria: command exits 0 and `output/alicloud-ai-audio-tts-realtime/validate.txt` is generated. ## Output And Evidence - Save artifacts, command outputs, and API response summaries under [REDACTED_SECRET]. - Include key parameters (region/resource id/time range) in evidence files for reproducibility. ## 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/sources.md`


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