初始提交：3 款纯音频游戏 + 共享引擎 + 完整文档与资产管线

- 共享引擎（app/src/main）：GestureEngine 6 手势识别、AudioEngine 三层音频
  （ExoPlayer BGM 交叉淡入 / 对白 ducking / SoundPool 低延迟）、Game/GameEngine
  状态机接口、MainActivity 全屏封面 + TalkBack
- 《声命线》storyline：末世互动广播剧，3 幕 8 抉择点 4 结局
- 《声东击西》reflex：听声辨位反应，12 波战斗 + BGM 三档 BPM 变速
- 《暗室》escape：3x3 网格密室逃脱，钥匙→铁柜→保险丝→电箱→大门谜题链
- 文档：setup（从零搭建）/ architecture（架构）/ engine-api（引擎 API）/
  asset-pipeline（资产流水线）/ games/*（三款游戏设计文档）
- 资产管线：Qwen3-TTS 对白 + 程序合成音效/BGM + Mureka BGM 的 gen 脚本与台账，
  全部 ogg 资产入库可复现
- env.d 环境脚本：android/tts 入库；sfx/mureka 含密钥不入库，仅提交 .example.sh 模板

tools/stable-audio-3/tests/test_lora.py

@@ -0,0 +1,72 @@
+import pytest
+import torch
+from functools import partial
+
+from stable_audio_3 import StableAudioModel
+from stable_audio_3.models.lora import (
+    LoRAParametrization,
+    add_lora,
+    get_lora_state_dict,
+    save_lora_safetensors,
+)
+from tests.conftest import ACCEL_DEVICE
+
+_LORA_RANK = 4
+_LORA_ALPHA = 4.0
+
+
+def _lora_cfg(rank, alpha):
+    return {
+        torch.nn.Linear: {
+            "weight": partial(
+                LoRAParametrization.from_linear,
+                rank=rank,
+                lora_alpha=alpha,
+                adapter_type="lora",
+            ),
+        },
+        torch.nn.Conv1d: {
+            "weight": partial(
+                LoRAParametrization.from_conv1d,
+                rank=rank,
+                lora_alpha=alpha,
+                adapter_type="lora",
+            ),
+        },
+    }
+
+
+@pytest.fixture(scope="session")
+def synthetic_lora_ckpt(tmp_path_factory):
+    """Build and save a minimal LoRA checkpoint from the small-music model for testing."""
+    model = StableAudioModel.from_pretrained("small-music", device=ACCEL_DEVICE)
+    add_lora(model.model.model, _lora_cfg(_LORA_RANK, _LORA_ALPHA))
+    add_lora(model.model.conditioner, _lora_cfg(_LORA_RANK, _LORA_ALPHA))
+    state_dict = {
+        **get_lora_state_dict(model.model.model),
+        **get_lora_state_dict(model.model.conditioner),
+    }
+    config = {"rank": _LORA_RANK, "alpha": _LORA_ALPHA, "adapter_type": "lora"}
+    ckpt_path = tmp_path_factory.mktemp("lora") / "synthetic.safetensors"
+    save_lora_safetensors(state_dict, config, ckpt_path)
+    del model
+    return ckpt_path
+
+
+@pytest.fixture(scope="session")
+def lora_model(synthetic_lora_ckpt):
+    """Small-music model with a synthetic LoRA checkpoint loaded."""
+    model = StableAudioModel.from_pretrained("small-music", device=ACCEL_DEVICE)
+    model.load_lora([str(synthetic_lora_ckpt)])
+    return model
+
+
+def test_lora_inference(lora_model, maybe_save_audio):
+    audio = lora_model.generate(prompt="drums", duration=1.0, steps=4, seed=42)
+
+    assert isinstance(audio, torch.Tensor)
+    assert audio.ndim == 3  # (batch, channels, samples)
+    assert audio.shape[0] == 1
+    assert audio.shape[-1] > 0
+
+    maybe_save_audio(audio, lora_model.model.sample_rate, "lora_drums")