raise clean error on malformed sam_configuration.json

Author: grzegorz-roboflow

inference_models/inference_models/models/sam3/sam3_torch.py

@@ -102,7 +102,15 @@ def from_pretrained(
             model_name_or_path, "sam_configuration.json"
         )
         if os.path.exists(sam_configuration_path):
-            version = decode_sam_version(config_path=sam_configuration_path)
+            try:
+                version = decode_sam_version(config_path=sam_configuration_path)
+            except (KeyError, ValueError) as error:
+                raise CorruptedModelPackageError(
+                    message="Could not decode sam_configuration.json in SAM3 model package. "
+                    "If you run inference locally, verify the correctness of SAM3 model package. "
+                    "If you see the error running on Roboflow platform - contact us to get help.",
+                    help_url="https://todo",
+                ) from error
             if version not in SUPPORTED_VERSIONS:
                 raise CorruptedModelPackageError(
                     message=f"Detected unsupported version of SAM3 model: {version}. Supported versions: "

inference_models/tests/unit_tests/models/test_sam3_torch.py

@@ -194,3 +194,21 @@ def test_from_pretrained_rejects_unsupported_sam_configuration_version(
             model_name_or_path=str(tmp_path),
             device=torch.device("cpu"),
         )
+
+
+def test_from_pretrained_rejects_malformed_sam_configuration(
+    sam3_torch_module: ModuleType, tmp_path
+) -> None:
+    # given - config present but missing the "version" key
+    from inference_models.errors import CorruptedModelPackageError
+
+    (tmp_path / "weights.pt").touch()
+    (tmp_path / "bpe_simple_vocab_16e6.txt.gz").touch()
+    (tmp_path / "sam_configuration.json").write_text('{"unexpected": "content"}')
+
+    # when / then
+    with pytest.raises(CorruptedModelPackageError):
+        sam3_torch_module.SAM3Torch.from_pretrained(
+            model_name_or_path=str(tmp_path),
+            device=torch.device("cpu"),
+        )