feat: SD 1.x向けScheduler対応を5種類に整理

generation.schedulerの正式対応値をdpmpp_2m_karras、dpmpp_2m_sde_karras、euler_a、ddim、lcmに限定し、既定値をdpmpp_2m_karrasへ変更する。旧dpmpp_2m、eulerおよび未知値は起動時の設定validationで拒否する。

Scheduler生成処理をPipelineFactoryへ集約する。DPM++ 2M系はDPMSolverMultistepSchedulerを共用し、algorithm_type、solver_order=2、use_karras_sigmas=Trueで通常版とSDE版を切り替える。Euler Ancestral、DDIM、LCMは現在のpipeline scheduler configを引き継いで構築する。

LCM-LoRAは既存のmodel.lora設定から通常のLoRAとして読み込み、LCM選択時にもstepsとcfg_scaleを自動調整せずTOML値をそのまま使用する。MCP Tool schemaにはscheduler入力を追加しない。

Specifications.md、Design.md、config.mdおよびconfig.example.tomlのenum、既定値、対応表、設定例を新仕様へ統一する。5 schedulerの変換、DPM++ constructor option、旧値と未知値の拒否、省略時の既定値、MCP schema非公開をテストで検証する。

検証: ruff check、ruff format --check、pyright、pytest（39 passed）、インストール済みDiffusersで5 schedulerの実インスタンス構築を確認。

2 files changed, 27 insertions, 12 deletions

diff --git a/src/mcp_sd15/config.py b/src/mcp_sd15/config.py
index 5bbe225..1a5a71d 100644
--- a/src/mcp_sd15/config.py
+++ b/src/mcp_sd15/config.py
@@ -11,7 +11,7 @@ from typing import Any
 from .errors import ConfigError
 
 VALID_SIZES = frozenset({"square_512", "landscape_512", "portrait_512"})
-VALID_SCHEDULERS = frozenset({"dpmpp_2m", "ddim", "euler", "euler_a"})
+VALID_SCHEDULERS = frozenset({"dpmpp_2m_karras", "dpmpp_2m_sde_karras", "euler_a", "ddim", "lcm"})
 
 
 @dataclass(frozen=True)
@@ -41,7 +41,7 @@ class ModelConfig:
 class GenerationConfig:
     steps: int = 25
     cfg_scale: float = 7.0
-    scheduler: str = "dpmpp_2m"
+    scheduler: str = "dpmpp_2m_karras"
     default_size: str = "square_512"
 
 
@@ -189,7 +189,7 @@ def load_config(path: str | Path, *, validate_paths: bool = True) -> AppConfig:
     cfg_scale = _number(generation_raw, "cfg_scale", 7.0)
     if not 0 <= cfg_scale <= 30:
         raise ConfigError("generation.cfg_scale must be between 0 and 30")
-    scheduler = _string(generation_raw, "scheduler") or "dpmpp_2m"
+    scheduler = _string(generation_raw, "scheduler") or "dpmpp_2m_karras"
     if scheduler not in VALID_SCHEDULERS:
         raise ConfigError(f"unsupported scheduler: {scheduler}")
     default_size = _string(generation_raw, "default_size") or "square_512"
diff --git a/src/mcp_sd15/pipeline_factory.py b/src/mcp_sd15/pipeline_factory.py
index 12d95ba..b0525ea 100644
--- a/src/mcp_sd15/pipeline_factory.py
+++ b/src/mcp_sd15/pipeline_factory.py
@@ -64,7 +64,7 @@ class PipelineFactory:
                 adapter_weights.append(item.weight)
             if adapter_names:
                 pipeline.set_adapters(adapter_names, adapter_weights=adapter_weights)
-            pipeline.scheduler = self._scheduler(pipeline.scheduler, diffusers)
+            pipeline.scheduler = self._create_scheduler(pipeline.scheduler, diffusers)
             pipeline.set_progress_bar_config(disable=True)
             return pipeline.to("cuda")
         except ConfigError:
@@ -130,14 +130,29 @@ class PipelineFactory:
         pipeline.set_progress_bar_config(disable=True)
         return pipeline.to("cuda")
 
-    def _scheduler(self, scheduler: Any, diffusers: Any) -> Any:
+    def _create_scheduler(self, current: Any, diffusers: Any) -> Any:
+        name = self.config.generation.scheduler
+        if name == "dpmpp_2m_karras":
+            return diffusers.DPMSolverMultistepScheduler.from_config(
+                current.config,
+                algorithm_type="dpmsolver++",
+                solver_order=2,
+                use_karras_sigmas=True,
+            )
+        if name == "dpmpp_2m_sde_karras":
+            return diffusers.DPMSolverMultistepScheduler.from_config(
+                current.config,
+                algorithm_type="sde-dpmsolver++",
+                solver_order=2,
+                use_karras_sigmas=True,
+            )
         classes = {
-            "dpmpp_2m": diffusers.DPMSolverMultistepScheduler,
-            "ddim": diffusers.DDIMScheduler,
-            "euler": diffusers.EulerDiscreteScheduler,
             "euler_a": diffusers.EulerAncestralDiscreteScheduler,
+            "ddim": diffusers.DDIMScheduler,
+            "lcm": diffusers.LCMScheduler,
         }
-        options = dict(scheduler.config)
-        if self.config.generation.scheduler == "dpmpp_2m":
-            options.update(algorithm_type="dpmsolver++", solver_order=2)
-        return classes[self.config.generation.scheduler].from_config(options)
+        try:
+            scheduler_class = classes[name]
+        except KeyError as exc:
+            raise ConfigError(f"unsupported scheduler: {name}") from exc
+        return scheduler_class.from_config(current.config)