33 lines
1.3 KiB
Markdown
33 lines
1.3 KiB
Markdown
# FunASR realtime ASR demo
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The project keeps the frontend and backend in separate directories. The frontend serves the original Tencent demo assets from frontend/static/ unchanged.
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## Project layout
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- backend/: FunASR WebSocket adapter, native engine launcher, CAM++ service, and backend code.
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- frontend/: Tencent demo files and the static HTTP/WebSocket proxy.
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- scripts/: shared model download tools.
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- requirements.txt: combined dependencies for both ASR engines and the frontend.
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- model_manifest.json: shared model registry.
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## Install and download models
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The combined requirements file includes the GB10 CUDA 13 PyTorch and vLLM stack used by the Qwen3-ASR branch. Adjust the CUDA index and torch-family pins before installing on a different host.
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~~~powershell
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python -m pip install -r requirements.txt
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if (-not (Test-Path .env)) { Copy-Item .env.funasr.example .env }
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python scripts/download_models.py --funasr-runtime
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~~~
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## Start
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Run the backend and frontend in separate terminals from the project root:
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~~~powershell
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python backend/run_backend.py
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python frontend/run_frontend.py
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~~~
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The backend supervises CAM++, FunASR native WSS, and the browser protocol adapter. The frontend serves the unchanged Tencent page and proxies its same-origin /ws and /api/stop requests to the backend. Configure ports and model locations in .env.
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