vivek/fix-dynamic-schema-serialization

examples/examples/simple/core/testing-ameasure.py

@@ -43,22 +43,14 @@ def example_response(user):
 pipeline = pipeline_by_slug
 
 
-async def measure_func(user):
-    return example_response(user)
+async def measure_func(x=None):
+    return x
 
 
 async def example_handler(pipeline_run_test_case):
     (runner, test_case) = pipeline_run_test_case
-    user = User(
-        id=1,
-        name="John Doe",
-        email="john@example.com",
-        age=30,
-    )
-    await runner.ameasure(
-        measure_func,
-        user=user
-    )
+    result = await runner.ameasure(measure_func, x=test_case)
+    return result
 
 
 async def main():

examples/pyproject.toml

@@ -11,7 +11,7 @@ openai = "1.13.3"
 pinecone-client = "^2.2.1"
 python = "^3.8.1"
 python-dotenv = "^1.0.0"
-gentrace-py = {path = "../package/dist/gentrace_py-0.31.5.tar.gz", develop = true}
+gentrace-py = {path = "../package/dist/gentrace_py-0.31.6.tar.gz", develop = true}
 
 [tool.poetry.group.lint.dependencies]
 black = "^23.3.0"

package/gentrace/providers/step_run.py

@@ -22,16 +22,25 @@ def __init__(
         self.elapsed_time = elapsed_time
         self.start_time = start_time
         self.end_time = end_time
-        self.inputs = self._convert_to_dict(copy.deepcopy(inputs))
+        self.inputs = self._convert_to_dict(inputs)
         self.model_params = model_params
-        self.outputs = self._convert_to_dict(copy.deepcopy(outputs))
-        self.context = copy.deepcopy(context or {})
+        self.outputs = self._convert_to_dict(outputs)
+        self.context = self._convert_to_dict(context or {})
 
     def _convert_to_dict(self, obj: Any) -> Any:
         if hasattr(obj, '__dict__'):
+            # Check for DynamicSchema Gentrace custom types
+            if hasattr(obj, 'from_openapi_data_oapg'):
+                # Primitive type
+                if not hasattr(obj, 'items'):
+                    return obj
+                obj = {k: self._convert_to_dict(v) for k, v in obj.items()}
+                return obj
+
             # Check for model_dump first (works for both v1 and v2)
             if hasattr(obj, 'model_dump'):
                 return obj.model_dump()
+
             # Fallback to dict() if model_dump is not available
             elif hasattr(obj, 'dict'):
                 return obj.dict()