NAM model integration: rewrite nam_host.py with full inference pipeline

- NAMHost: process(), warm_up(), avg_inference_ms, model cache, crossfade
- ModelSwitchMode enum (INSTANT/CROSSFADE/PAUSE) with pipeline wiring
- list_available_models(), available_models(), process_with_model()
- Fixed pipeline.py type typo (NAMIHost -> NAMHost)
- Crossfade support wired through pipeline NAM_AMP route
- 25/25 NAM tests + 41/41 integration tests pass
- download_models.sh generates 10 verified Linear .nam models

src/dsp/pipeline.py

@@ -21,7 +21,7 @@ from typing import Optional
 import numpy as np
 from scipy.signal import lfilter
 
-from .nam_host import NAMHost, NAMModel
+from .nam_host import NAMHost, NAMModel, ModelSwitchMode
 from .ir_loader import IRLoader, IRFile
 from ..presets.types import FXBlock, FXType, Preset
 
@@ -230,7 +230,7 @@ class AudioPipeline:
 
     def __init__(
         self,
-        nam_host: Optional[NAMIHost] = None,
+        nam_host: Optional[NAMHost] = None,
         ir_loader: Optional[IRLoader] = None,
     ):
         self.nam = nam_host or NAMHost()
@@ -336,6 +336,9 @@ class AudioPipeline:
                 case FXType.NAM_AMP:
                     if self.nam.is_loaded:
                         buf = self.nam.process(buf)
+                        # Apply crossfade if a model switch is in progress
+                        if self.nam._crossfade_buf is not None:
+                            buf = self.nam.apply_crossfade(buf)
                 case FXType.IR_CAB:
                     if self.ir.is_loaded:
                         buf = self._apply_ir_cab(buf, params, fx_state)