/install aliyun-qwen-tts-realtime
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-realtimeqwen3-tts-instruct-flash-realtimeqwen3-tts-instruct-flash-realtime-2026-01-22qwen3-tts-vd-realtime-2026-01-15qwen3-tts-vc-realtime-2026-01-15
Prerequisites
- Install SDK in a virtual environment:
python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope
- Set
DASHSCOPE_API_KEYin your environment, or adddashscope_api_keyto~/.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\x3Cstring>)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:
.venv/bin/python skills/ai/audio/aliyun-qwen-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):
.venv/bin/python skills/ai/audio/aliyun-qwen-tts-realtime/scripts/realtime_tts_demo.py \
--text "realtime health check" \
--strict
Output location
- Default output:
output/ai-audio-tts-realtime/audio/ - Override base dir with
OUTPUT_DIR.
Validation
mkdir -p output/aliyun-qwen-tts-realtime
for f in skills/ai/audio/aliyun-qwen-tts-realtime/scripts/*.py; do
python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/aliyun-qwen-tts-realtime/validate.txt
Pass criteria: command exits 0 and output/aliyun-qwen-tts-realtime/validate.txt is generated.
Output And Evidence
- Save artifacts, command outputs, and API response summaries under
output/aliyun-qwen-tts-realtime/. - Include key parameters (region/resource id/time range) in evidence files for reproducibility.
Workflow
- Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
- Run one minimal read-only query first to verify connectivity and permissions.
- Execute the target operation with explicit parameters and bounded scope.
- Verify results and save output/evidence files.
References
references/sources.md
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install aliyun-qwen-tts-realtime - After installation, invoke the skill by name or use
/aliyun-qwen-tts-realtime - Provide required inputs per the skill's parameter spec and get structured output
What is Aliyun Qwen Tts Realtime?
Use when real-time speech synthesis is needed with Alibaba Cloud Model Studio Qwen TTS Realtime models. Use when low-latency interactive speech is required,... It is an AI Agent Skill for Claude Code / OpenClaw, with 94 downloads so far.
How do I install Aliyun Qwen Tts Realtime?
Run "/install aliyun-qwen-tts-realtime" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Aliyun Qwen Tts Realtime free?
Yes, Aliyun Qwen Tts Realtime is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Aliyun Qwen Tts Realtime support?
Aliyun Qwen Tts Realtime is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Aliyun Qwen Tts Realtime?
It is built and maintained by cinience (@cinience); the current version is v1.0.0.