# FunASR realtime ASR demo

The project keeps the frontend and backend in separate directories. The frontend serves the original Tencent demo assets from frontend/static/ unchanged.

## Project layout

- backend/: FunASR WebSocket adapter, native engine launcher, CAM++ service, and backend code.
- frontend/: Tencent demo files and the static HTTP/WebSocket proxy.
- scripts/: shared model download tools.
- requirements.txt: combined dependencies for both ASR engines and the frontend.
- model_manifest.json: shared model registry.

## Install and download models

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.

~~~powershell
python -m pip install -r requirements.txt
if (-not (Test-Path .env)) { Copy-Item .env.funasr.example .env }
python scripts/download_models.py --funasr-runtime
~~~

## Start

Run the backend and frontend in separate terminals from the project root:

~~~powershell
python backend/run_backend.py
python frontend/run_frontend.py
~~~

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.