fix: handle JSONDecodeError when parsing JSON tensors in model output conversion

src/opengradient/client/_conversions.py

@@ -156,7 +156,10 @@ def convert_to_model_output(event_data: AttributeDict) -> Dict[str, np.ndarray]:
             if isinstance(tensor, (AttributeDict, dict)):
                 name = tensor.get("name")
                 value = tensor.get("value")
-                output_dict[name] = np.array(json.loads(value))
+                try:
+                    output_dict[name] = np.array(json.loads(value))
+                except (json.JSONDecodeError, TypeError, ValueError) as e:
+                    logging.warning(f"Failed to parse JSON tensor '{name}': {e} (raw value: {value!r})")
             else:
                 logging.warning(f"Unexpected tensor type: {type(tensor)}")
 
@@ -203,11 +206,15 @@ def convert_array_to_model_output(array_data: List) -> ModelOutput:
     for tensor in array_data[2]:
         name = tensor[0]
         value = tensor[1]
-        json_data[name] = np.array(json.loads(value))
+        try:
+            json_data[name] = np.array(json.loads(value))
+        except (json.JSONDecodeError, TypeError, ValueError) as e:
+            logging.warning(f"Failed to parse JSON tensor '{name}': {e} (raw value: {value!r})")
 
     return ModelOutput(
         numbers=number_data,
         strings=string_data,
         jsons=json_data,
         is_simulation_result=array_data[3],
     )
+

tests/utils_test.py

@@ -68,17 +68,31 @@ def test_convert_array_empty():
     assert result.is_simulation_result is False
 
 
-def test_convert_array_invalid_json():
-    """Test handling of invalid JSON data"""
+def test_convert_array_invalid_json(caplog):
+    """Test that invalid JSON tensor data is skipped with a warning instead of crashing.
+
+    Previously json.loads() was unguarded and would crash the entire conversion.
+    After the fix, malformed JSON tensors are skipped and logged as warnings so
+    all other valid tensors in the same response are still returned.
+    """
+    import logging
+
     invalid_json_data = [
         [],  # Empty number tensors
         [],  # Empty string tensors
         [["invalid_json", '{"key": invalid}']],  # Invalid JSON
         False,
     ]
 
-    with pytest.raises(json.JSONDecodeError):
-        utils.convert_array_to_model_output(invalid_json_data)
+    with caplog.at_level(logging.WARNING):
+        result = utils.convert_array_to_model_output(invalid_json_data)
+
+    # Should not raise; malformed tensor is skipped
+    assert isinstance(result, types.ModelOutput)
+    assert result.jsons == {}
+
+    # A warning should have been emitted mentioning the tensor name
+    assert any("invalid_json" in record.message for record in caplog.records)
 
 
 def test_convert_array_invalid_shape():