feat: Stable Diffusion 1.x MCPサーバを実装

仕様書・設計書に基づき、ローカルCUDA GPU上のStable Diffusion 1.x互換モデルをMCP経由で利用するサーバを新規実装。

実装内容:
- generate_image、generate_guided_image、inpaint_imageの3ツールをMCP SDK v2で公開
- TOMLからcheckpoint、VAE、複数LoRAと重み、ControlNet、生成設定を読み込み
- モデル種別ごとの固定ディレクトリ解決と起動時の設定・ファイル存在検証を追加
- Depth/MiDaS、OpenPose body/full、ControlNet Inpaintの前処理とパイプライン切替を実装
- FP16/CUDA、1枚固定生成、ControlNetオンデマンドロード、単一GPU直列実行を実装
- Base64 PNG/JPEG入力の形式・サイズ検証と任意のdata URI入力に対応
- seed、サイズ、モード、時刻、処理時間をPNG metadataへ記録
- 任意のローカルPNG保存、生成エラー分類、CUDA OOM後のキャッシュ回復を追加
- --configと--versionを備えたstdio CLIエントリポイントを追加

開発・運用:
- Python 3.11およびuvによる依存・lock管理を構成
- config.example.tomlとセットアップ・運用手順をREADMEへ追加
- Ruff、Pyright、pytestの設定を追加
- 設定、パス解決、schema、画像検証、サービスルーティング、排他制御、MCP画像返却をテスト

検証結果:
- pytest: 30 passed
- Ruff lint/format: passed
- Pyright: 0 errors, 0 warnings
- CLI versionおよびMCPクライアント経由のPNG返却を確認
- 実GPU smoke testはCUDA GPUとモデルファイルがないため対象外

1 files changed, 122 insertions, 0 deletions

diff --git a/tests/test_config.py b/tests/test_config.py
new file mode 100644
index 0000000..5e4341a
--- /dev/null
+++ b/tests/test_config.py
@@ -0,0 +1,122 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+import pytest
+
+from mcp_sd15.config import ConfigError, load_config
+
+
+def make_models(root: Path) -> None:
+    for folder, names in {
+        "checkpoints": ["base.safetensors"],
+        "vae": ["vae.safetensors"],
+        "lora": ["a.safetensors", "b.safetensors"],
+        "controlnet": ["depth.safetensors", "pose.safetensors", "inpaint.safetensors"],
+    }.items():
+        destination = root / folder
+        destination.mkdir(parents=True)
+        for name in names:
+            (destination / name).touch()
+
+
+def valid_toml(root: Path) -> str:
+    return f'''[model]
+root = "{root.as_posix()}"
+checkpoint = "base.safetensors"
+vae = "vae.safetensors"
+[[model.lora]]
+file = "a.safetensors"
+weight = 0.8
+[[model.lora]]
+file = "b.safetensors"
+weight = -0.2
+[generation]
+steps = 20
+cfg_scale = 6.5
+scheduler = "euler_a"
+default_size = "portrait_512"
+[controlnet.depth]
+enabled = true
+model = "depth.safetensors"
+preprocessor = "midas"
+[controlnet.openpose]
+enabled = true
+model = "pose.safetensors"
+[controlnet.inpaint]
+enabled = true
+model = "inpaint.safetensors"
+[output]
+enabled = true
+directory = "generated"
+'''
+
+
+def test_loads_and_resolves_all_model_paths(tmp_path: Path) -> None:
+    root = tmp_path / "models"
+    make_models(root)
+    path = tmp_path / "config.toml"
+    path.write_text(valid_toml(root), encoding="utf-8")
+
+    config = load_config(path)
+
+    assert config.model.checkpoint_path() == root / "checkpoints" / "base.safetensors"
+    assert config.model.vae_path() == root / "vae" / "vae.safetensors"
+    assert config.model.lora_paths() == (
+        root / "lora" / "a.safetensors",
+        root / "lora" / "b.safetensors",
+    )
+    assert config.generation.default_size == "portrait_512"
+    assert config.output.directory == tmp_path / "generated"
+    assert config.controlnet_path("openpose_full") == root / "controlnet" / "pose.safetensors"
+
+
+@pytest.mark.parametrize(
+    "line, message",
+    [
+        ('checkpoint = "../base.safetensors"', "file name"),
+        ("steps = 0", "steps"),
+        ('scheduler = "unknown"', "scheduler"),
+        ('default_size = "1024"', "default_size"),
+        ('preprocessor = "zoe"', "preprocessor"),
+    ],
+)
+def test_rejects_invalid_values(tmp_path: Path, line: str, message: str) -> None:
+    root = tmp_path / "models"
+    make_models(root)
+    text = valid_toml(root)
+    if line.startswith("checkpoint"):
+        text = text.replace('checkpoint = "base.safetensors"', line)
+    elif line.startswith("steps"):
+        text = text.replace("steps = 20", line)
+    elif line.startswith("scheduler"):
+        text = text.replace('scheduler = "euler_a"', line)
+    elif line.startswith("default_size"):
+        text = text.replace('default_size = "portrait_512"', line)
+    else:
+        text = text.replace('preprocessor = "midas"', line)
+    path = tmp_path / "bad.toml"
+    path.write_text(text, encoding="utf-8")
+
+    with pytest.raises(ConfigError, match=message):
+        load_config(path)
+
+
+def test_missing_model_fails_startup_validation(tmp_path: Path) -> None:
+    root = tmp_path / "models"
+    make_models(root)
+    (root / "controlnet" / "depth.safetensors").unlink()
+    path = tmp_path / "config.toml"
+    path.write_text(valid_toml(root), encoding="utf-8")
+
+    with pytest.raises(ConfigError, match=r"depth\.safetensors"):
+        load_config(path)
+
+
+def test_can_skip_path_checks_for_schema_only_use(tmp_path: Path) -> None:
+    path = tmp_path / "config.toml"
+    path.write_text(
+        '[model]\nroot = "missing"\ncheckpoint = "base.safetensors"\n', encoding="utf-8"
+    )
+    config = load_config(path, validate_paths=False)
+    assert config.model.root == (tmp_path / "missing").resolve()