feat: Qwen3-TTS proxy with HIP graph + CPU decoder optimisations

- OpenAI-compatible Flask proxy (POST /audio/speech, GET /models)
- faster-qwen3-tts HIP graph acceleration: GPU LLM at 1.78x RTF
- CPU speech tokenizer decoder: bypasses MIOpen ConvDirectNaiveConvFwd,
  eliminates 4-40s per-request decode overhead
- attn_implementation=sdpa for transformer attention
- AOTRITON env var toggle (off=short sentences, on=long-form/novel chapters)
- HIP_GRAPHS env var toggle (default on)
- Startup warmup with HIP graph capture (~5s)
- CORS support for browser extension requests
- RTF: 0.9-1.5x on AMD RX 7900 XTX (gfx1100, ROCm 6.3)

Performance vs baseline (CPU-only, ~3 min/sentence):
  12c: 3.2s | 44c: 2.7s | 115c: 6.6s

README.md

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+# qwen3-tts-ra
+
+Qwen3-TTS with Read-Aloud browser extension integration.
+
+## Components
+
+- `qwen3-proxy/` — OpenAI-compatible TTS proxy (`POST /audio/speech`)
+- `Qwen3-TTS/` — Qwen3-TTS library (submodule / clone)
+- `read-aloud/` — Read-Aloud browser extension (submodule / clone)
+- `setup_qwen3_readaloud.sh` — Initial environment setup script
+
+## Architecture
+
+```
+Read-Aloud extension
+  → POST http://localhost:5000/audio/speech
+    → qwen3-proxy/app.py (Flask, OpenAI-compatible API)
+      → faster-qwen3-tts (HIP graph acceleration, AMD gfx1100)
+        → GPU: LLM token generation at ~1.78x RTF
+        → CPU: speech tokenizer decode (bypasses MIOpen)
+```
+
+## Performance (AMD Radeon RX 7900 XTX, gfx1100)
+
+| Input | Audio | Time | RTF |
+|-------|-------|------|-----|
+| 12c "Hello world." | ~2s | ~3s | ~0.9x |
+| 44c sentence | ~4s | ~3s | **1.5x** |
+| 115c paragraph | ~10s | ~7s | **1.5x** |
+
+RTF > 1.0 = generates faster than real-time.
+
+## Key optimisations
+
+1. **HIP Graphs** (`faster-qwen3-tts`) — captures autoregressive decode loop as a static GPU program, eliminating Python overhead per token
+2. **CPU speech decoder** — moves `speech_tokenizer.model` to CPU, bypassing MIOpen's slow `ConvDirectNaiveConvFwd` fallback entirely
+3. **`attn_implementation=sdpa`** — PyTorch native SDPA for transformer attention
+4. **`MIOPEN_USER_DB_PATH`** — persistent MIOpen find-DB for LLM-side convolutions
+
+## Setup
+
+```bash
+# Install Python venv + deps
+./setup_qwen3_readaloud.sh
+
+# Start the proxy service
+systemctl --user start qwen3-tts-proxy.service
+
+# Watch logs
+journalctl --user -u qwen3-tts-proxy.service -f
+```
+
+## Read-Aloud Extension Settings
+
+In Read-Aloud → Settings → OpenAI:
+
+| Field | Value |
+|-------|-------|
+| URL | `http://127.0.0.1:5000` |
+| API Key | *(leave blank)* |
+| Voice list | see below |
+
+```json
+[
+  {"voice": "alloy",   "lang": "en-US", "model": "tts-1"},
+  {"voice": "echo",    "lang": "en-US", "model": "tts-1"},
+  {"voice": "fable",   "lang": "en-US", "model": "tts-1"},
+  {"voice": "onyx",    "lang": "en-US", "model": "tts-1"},
+  {"voice": "nova",    "lang": "zh-CN", "model": "tts-1"},
+  {"voice": "shimmer", "lang": "zh-CN", "model": "tts-1"}
+]
+```
+
+## Env vars (systemd service)
+
+| Variable | Default | Notes |
+|----------|---------|-------|
+| `QWEN_MODEL` | `Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice` | HF model id or local path |
+| `DEVICE` | `cuda:0` | GPU device |
+| `HIP_GRAPHS` | `1` | Enable faster-qwen3-tts HIP graphs |
+| `AOTRITON` | `0` | AOTriton flash attention — faster for long text (>80 chars), slower for short sentences |
+| `PROXY_PORT` | `5000` | Listening port |