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Déploiement et opérations · SKILL.md

deployment-serving

deployment-serving

Use PaddleSpeech server/client, HTTP and WebSocket APIs, offline and streaming configs, Paddle Inference, ONNX, C++ runtime, and deployment troubleshooting safely.

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Documentation de la Skill

GitHub

name: deployment-serving description: "Use PaddleSpeech server/client, HTTP and WebSocket APIs, offline and streaming configs, Paddle Inference, ONNX, C++ runtime, and deployment troubleshooting safely." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Deployment and Serving

Use this sub-skill for paddlespeech_server, paddlespeech_client, PaddleSpeech Serving config YAML, HTTP REST APIs, WebSocket streaming ASR/TTS, online TTS, ACS, Paddle Inference/static models, ONNX streaming, C++ runtime, mobile/ARM deployment orientation, and service troubleshooting.

Safe Serving Workflow

  1. Inspect the config before launch:

    python scripts/inspect_server_config.py --config application.yaml
    
  2. Confirm side effects: server startup downloads/warmups models, opens ports, and runs until stopped.

  3. Start only after approval:

    paddlespeech_server start --config_file application.yaml
    
  4. Use the matching client:

    paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
    paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "您好" --output output.wav
    paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol http --input "您好" --output output.wav
    

Route by Deployment Surface

  • Offline HTTP ASR/TTS/CLS/TEXT/VECTOR/ACS: read references/server-and-streaming.md and references/api-contracts.md.
  • Streaming ASR: WebSocket-only ASR endpoint; use a WebSocket config and paddlespeech_client asr_online.
  • Streaming TTS: HTTP or WebSocket depending on protocol; online or online-ONNX engine types.
  • Paddle Inference/static: use static model configs and predictor sections; do not mix dynamic checkpoints.
  • C++/mobile/Android/ARM/FastDeploy: read references/runtime-deployment.md; treat builds as toolchain workflows requiring approval.
  • Audio search / ACS / Milvus apps: use this sub-skill for service boundaries and external service planning; route embedding details to ../audio-analysis/SKILL.md.

References and Helper

  • references/server-and-streaming.md explains config fields, engine lists, protocols, and client commands.
  • references/api-contracts.md summarizes REST and WebSocket routes and payload expectations.
  • references/runtime-deployment.md covers static/Paddle Inference, ONNX, C++ runtime, Android/ARM, Docker, and audio-search boundaries.
  • references/troubleshooting.md covers ports, host binding, protocol mismatch, engine warmup, and service dependencies.
  • scripts/inspect_server_config.py safely validates YAML structure without starting a server.

Do Not Do by Default

  • Do not start server processes, Docker Compose, Milvus/MySQL, C++ builds, Android/ARM builds, or streaming demos without approval.
  • Do not claim server readiness from CLI help; warmup and model downloads are separate runtime checks.
  • Do not use HTTP clients against WebSocket streaming ASR configs or offline configs against online engine types.
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