Qwen3-ASR Web Demo Suite

Web-based testing and demonstration tool for the Qwen3-ASR-1.7B speech recognition model deployed via vLLM.

Features

• Connection Test — Verify API endpoint, authentication, and model info
• Real-time Transcription — Live microphone capture with incremental text display
• File Upload — Transcribe audio files (WAV, MP3, MP4, M4A, OGG, FLAC, WEBM) with progress tracking
• Prompt Caching — Cache hit/miss badges and latency comparison tool
• WebSocket Streaming — Bidirectional audio streaming with auto-reconnect

Tech Stack

Layer	Tech
Frontend	React 19 + TypeScript + Vite + Tailwind CSS v4
Backend	FastAPI + OpenAI SDK + Uvicorn
Model	Qwen3-ASR-1.7B via vLLM (OpenAI-compatible API)

Quick Start

Prerequisites

• Node.js 18+
• Python 3.10+
• A running vLLM instance serving Qwen3-ASR-1.7B with OpenAI-compatible API

Backend

cd backend
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt

# Copy and configure environment
cp .env.example .env
# Edit .env with your vLLM endpoint and API key

# Start server
uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload

Frontend

cd frontend
npm install
npm run dev

Open http://localhost:5173 in your browser.

Environment Configuration

Copy backend/.env.example to backend/.env and configure:

Variable	Default	Description
API_BASE_URL	http://<your-vllm-host>:<port>/v1	vLLM API endpoint
API_KEY	test	API key for authentication
PORT	8000	Backend server port
CORS_ORIGINS	http://localhost:5173	Allowed CORS origins (comma-separated)
REQUEST_TIMEOUT	30	Request timeout in seconds
MODEL_NAME	(auto-detected)	Model name on vLLM

Project Structure

├── backend/
│   ├── app/
│   │   ├── main.py          # FastAPI app entry
│   │   ├── config.py         # Settings with pydantic-settings
│   │   ├── errors.py         # Error handling utilities
│   │   └── routers/          # API route handlers
│   │       ├── health.py     # Health check endpoint
│   │       ├── settings.py   # Settings endpoint
│   │       ├── transcribe.py # File upload transcription
│   │       └── streaming.py  # WebSocket/live streaming
│   ├── tests/
│   ├── requirements.txt
│   └── .env.example
├── frontend/
│   ├── src/
│   ├── package.json
│   └── vite.config.ts
└── README.md

Production Build

# Build frontend
cd frontend && npm run build

# Serve with backend
cd ../backend
uvicorn app.main:app --host 0.0.0.0 --port 8000

License

MIT