Fix current Hub loading and demo sampler values

examples/span_separation_workflow.json

@@ -65,7 +65,7 @@
         {"name": "residual", "type": "AUDIO", "links": [5], "slot_index": 1}
       ],
       "properties": {"Node name for S&R": "SAMAudioSpanSeparator"},
-      "widgets_values": ["car honking", 0, 32]
+      "widgets_values": ["car honking", 0, "fixed", 32]
     },
     {
       "id": 5,

examples/text_separation_workflow.json

@@ -49,7 +49,7 @@
         {"name": "residual", "type": "AUDIO", "links": [4], "slot_index": 1}
       ],
       "properties": {"Node name for S&R": "SAMAudioTextSeparator"},
-      "widgets_values": ["man speaking", false, 0, 32]
+      "widgets_values": ["man speaking", false, 0, "fixed", 32]
     },
     {
       "id": 4,

examples/visual_separation_workflow.json

@@ -67,7 +67,7 @@
         {"name": "residual", "type": "AUDIO", "links": [6], "slot_index": 1}
       ],
       "properties": {"Node name for S&R": "SAMAudioVisualSeparator"},
-      "widgets_values": ["", 0, 32]
+      "widgets_values": ["", 0, "fixed", 32]
     },
     {
       "id": 5,

nodes.py

@@ -41,6 +41,7 @@ def _sampling_inputs() -> dict[str, tuple[Any, ...]]:
                 "default": 0,
                 "min": 0,
                 "max": MAX_SEED,
+                "control_after_generate": True,
                 "tooltip": "Controls SAM-Audio's initial noise for reproducible separation.",
             },
         ),

sam_audio_comfy/runtime.py

@@ -320,6 +320,42 @@ def import_sam_audio() -> tuple[Any, Any]:
         ) from error
 
 
+def _load_sam_audio_checkpoint(SAMAudio: Any, model_path: Path) -> Any:
+    """Load a local checkpoint across old and new huggingface_hub call signatures."""
+    model_kwargs = {
+        "map_location": "cpu",
+        "strict": False,
+        "text_ranker": None,
+        "visual_ranker": None,
+    }
+    try:
+        return SAMAudio.from_pretrained(str(model_path), **model_kwargs)
+    except TypeError as error:
+        message = str(error)
+        if not (
+            "_from_pretrained()" in message
+            and "proxies" in message
+            and "resume_download" in message
+        ):
+            raise
+
+        LOGGER.info(
+            "Using SAM-Audio's legacy local-checkpoint loader with the current "
+            "huggingface_hub API"
+        )
+        return SAMAudio._from_pretrained(
+            model_id=str(model_path),
+            revision=None,
+            cache_dir=None,
+            force_download=False,
+            proxies=None,
+            resume_download=False,
+            local_files_only=True,
+            token=None,
+            **model_kwargs,
+        )
+
+
 def load_pipeline(
     model_name: str,
     folder_paths: Any,
@@ -334,13 +370,7 @@ def load_pipeline(
 
     LOGGER.info("Loading SAM-Audio model from %s", model_path)
     try:
-        model = SAMAudio.from_pretrained(
-            str(model_path),
-            map_location="cpu",
-            strict=False,
-            text_ranker=None,
-            visual_ranker=None,
-        )
+        model = _load_sam_audio_checkpoint(SAMAudio, model_path)
         processor = SAMAudioProcessor.from_pretrained(str(model_path))
     except Exception as error:
         raise RuntimeError(

tests/test_nodes.py

@@ -97,6 +97,10 @@ def test_text_node_runs_full_audio_batch_with_standard_shapes(monkeypatch, tmp_p
         "SAMAudioPipelineLoader"
     ].INPUT_TYPES()["required"]
     assert loader_inputs["attention_backend"][0] == ["pytorch", "comfy_kitchen"]
+    sampler_inputs = package.NODE_CLASS_MAPPINGS[
+        "SAMAudioTextSeparator"
+    ].INPUT_TYPES()["required"]
+    assert sampler_inputs["seed"][1]["control_after_generate"] is True
     assert set(package.NODE_CLASS_MAPPINGS) == {
         "SAMAudioPipelineLoader",
         "SAMAudioSpanPrompt",

tests/test_package.py

@@ -1,3 +1,4 @@
+import json
 import sys
 import types
 from pathlib import Path
@@ -38,6 +39,28 @@ def test_node_does_not_require_torchcodec():
         assert not any("torchcodec" in line for line in dependency_lines)
 
 
+def test_example_sampler_widgets_include_seed_control():
+    root = Path(__file__).parents[1]
+    expected = {
+        "text_separation_workflow.json": (
+            "SAMAudioTextSeparator",
+            ["man speaking", False, 0, "fixed", 32],
+        ),
+        "span_separation_workflow.json": (
+            "SAMAudioSpanSeparator",
+            ["car honking", 0, "fixed", 32],
+        ),
+        "visual_separation_workflow.json": (
+            "SAMAudioVisualSeparator",
+            ["", 0, "fixed", 32],
+        ),
+    }
+    for filename, (node_type, widget_values) in expected.items():
+        workflow = json.loads((root / "examples" / filename).read_text())
+        sampler = next(node for node in workflow["nodes"] if node["type"] == node_type)
+        assert sampler["widgets_values"] == widget_values
+
+
 def test_upstream_installer_uses_no_deps():
     root = Path(__file__).parents[1]
     installer = (root / "install.py").read_text().lower()

tests/test_runtime.py

@@ -141,6 +141,44 @@ def test_mirror_checksum_mismatch_is_rejected(tmp_path, monkeypatch):
         runtime._download_official_model("facebook/sam-audio-small", tmp_path)
 
 
+def test_local_checkpoint_falls_back_for_legacy_hub_signature(tmp_path):
+    calls = []
+
+    class FakeSAMAudio:
+        @classmethod
+        def from_pretrained(cls, model_id, **kwargs):
+            calls.append(("public", model_id, kwargs))
+            raise TypeError(
+                "BaseModel._from_pretrained() missing 2 required keyword-only "
+                "arguments: 'proxies' and 'resume_download'"
+            )
+
+        @classmethod
+        def _from_pretrained(cls, **kwargs):
+            calls.append(("legacy", kwargs))
+            return "model"
+
+    assert runtime._load_sam_audio_checkpoint(FakeSAMAudio, tmp_path) == "model"
+    assert calls[1][0] == "legacy"
+    assert calls[1][1]["model_id"] == str(tmp_path)
+    assert calls[1][1]["local_files_only"] is True
+    assert calls[1][1]["proxies"] is None
+    assert calls[1][1]["resume_download"] is False
+    assert calls[1][1]["strict"] is False
+    assert calls[1][1]["text_ranker"] is None
+    assert calls[1][1]["visual_ranker"] is None
+
+
+def test_local_checkpoint_does_not_hide_unrelated_type_errors(tmp_path):
+    class FakeSAMAudio:
+        @classmethod
+        def from_pretrained(cls, model_id, **kwargs):
+            raise TypeError("bad model config")
+
+    with pytest.raises(TypeError, match="bad model config"):
+        runtime._load_sam_audio_checkpoint(FakeSAMAudio, tmp_path)
+
+
 def test_ode_options_match_upstream_default():
     assert ode_options(32) == {
         "method": "midpoint",