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

.gitignore

@@ -0,0 +1,49 @@
+# Python
+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+.Python
+*.egg-info/
+dist/
+build/
+*.egg
+.eggs/
+
+# Virtual envs
+venv/
+.venv/
+env/
+*.venv
+
+# Model weights / audio output
+*.wav
+*.mp3
+*.bin
+*.safetensors
+*.pt
+*.pth
+
+# HuggingFace cache
+.cache/
+
+# Test artifacts
+test_output.*
+test_simple.py
+
+# OS
+.DS_Store
+Thumbs.db
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+
+# Submodule source trees (large, checked out separately)
+Qwen3-TTS/
+read-aloud/
+
+# Systemd units are user-specific, generated by setup script
+${HOME_DIR}/