diff --git a/demo/simple/vectoradd_jax/tesseract_api.py b/demo/simple/vectoradd_jax/tesseract_api.py
index 9aecff7..5451902 100644
--- a/demo/simple/vectoradd_jax/tesseract_api.py
+++ b/demo/simple/vectoradd_jax/tesseract_api.py
@@ -86,16 +86,16 @@ def apply(inputs: InputSchema) -> OutputSchema:
 
 def abstract_eval(abstract_inputs):
     """Calculate output shape of apply from the shape of its inputs."""
-    is_shapedtye_dict = lambda x: type(x) is dict and (x.keys() == {"shape", "dtype"})
-    is_shapedtye_struct = lambda x: isinstance(x, jax.ShapeDtypeStruct)
+    is_shapedtype_dict = lambda x: type(x) is dict and (x.keys() == {"shape", "dtype"})
+    is_shapedtype_struct = lambda x: isinstance(x, jax.ShapeDtypeStruct)
 
     jaxified_inputs = jax.tree.map(
-        lambda x: jax.ShapeDtypeStruct(**x) if is_shapedtye_dict(x) else x,
+        lambda x: jax.ShapeDtypeStruct(**x) if is_shapedtype_dict(x) else x,
         abstract_inputs.model_dump(),
-        is_leaf=is_shapedtye_dict,
+        is_leaf=is_shapedtype_dict,
     )
     dynamic_inputs, static_inputs = eqx.partition(
-        jaxified_inputs, filter_spec=is_shapedtye_struct
+        jaxified_inputs, filter_spec=is_shapedtype_struct
     )
 
     def wrapped_apply(dynamic_inputs):
@@ -105,10 +105,10 @@ def wrapped_apply(dynamic_inputs):
     jax_shapes = jax.eval_shape(wrapped_apply, dynamic_inputs)
     return jax.tree.map(
         lambda x: {"shape": x.shape, "dtype": str(x.dtype)}
-        if is_shapedtye_struct(x)
+        if is_shapedtype_struct(x)
         else x,
         jax_shapes,
-        is_leaf=is_shapedtye_struct,
+        is_leaf=is_shapedtype_struct,
     )