diff --git a/kani/engines/openai/client.py b/kani/engines/openai/client.py
index 8b5d8ee..cfc03b7 100644
--- a/kani/engines/openai/client.py
+++ b/kani/engines/openai/client.py
@@ -167,7 +167,7 @@ async def create_chat_completion(
             "/chat/completions",
             json={
                 "model": model,
-                "messages": [cm.model_dump(exclude_defaults=True, mode="json") for cm in messages],
+                "messages": [cm.model_dump(exclude_none=True, mode="json") for cm in messages],
                 **kwargs,
             },
         )
diff --git a/kani/engines/openai/engine.py b/kani/engines/openai/engine.py
index 933604e..fca0074 100644
--- a/kani/engines/openai/engine.py
+++ b/kani/engines/openai/engine.py
@@ -110,17 +110,18 @@ def message_len(self, message: ChatMessage) -> int:
             mlen += len(self.tokenizer.encode(message.function_call.arguments))
         return mlen
 
-    async def predict(
-        self, messages: list[ChatMessage], functions: list[AIFunction] | None = None, **hyperparams
-    ) -> ChatCompletion:
-        if functions:
-            tool_specs = [
-                ToolSpec.from_function(FunctionSpec(name=f.name, description=f.desc, parameters=f.json_schema))
-                for f in functions
-            ]
-        else:
-            tool_specs = None
-        # translate to openai spec - group any tool messages together and ensure all free ToolCall IDs are bound
+    # translation helpers
+    @staticmethod
+    def translate_functions(functions: list[AIFunction], cls: type[ToolSpec] = ToolSpec) -> list[ToolSpec]:
+        return [
+            cls.from_function(FunctionSpec(name=f.name, description=f.desc, parameters=f.json_schema))
+            for f in functions
+        ]
+
+    @staticmethod
+    def translate_messages(
+        messages: list[ChatMessage], cls: type[OpenAIChatMessage] = OpenAIChatMessage
+    ) -> list[OpenAIChatMessage]:
         translated_messages = []
         free_toolcall_ids = set()
         for m in messages:
@@ -148,11 +149,22 @@ async def predict(
                             "Got a FUNCTION message with no tool_call_id but multiple tool calls are pending"
                             f" ({free_toolcall_ids})! Set the tool_call_id to resolve the pending tool requests."
                         )
-            translated_messages.append(OpenAIChatMessage.from_chatmessage(m))
+            translated_messages.append(cls.from_chatmessage(m))
         # if the translated messages start with a hanging TOOL call, strip it (openai limitation)
         # though hanging FUNCTION messages are OK
         while translated_messages and translated_messages[0].role == "tool":
             translated_messages.pop(0)
+        return translated_messages
+
+    async def predict(
+        self, messages: list[ChatMessage], functions: list[AIFunction] | None = None, **hyperparams
+    ) -> ChatCompletion:
+        if functions:
+            tool_specs = self.translate_functions(functions)
+        else:
+            tool_specs = None
+        # translate to openai spec - group any tool messages together and ensure all free ToolCall IDs are bound
+        translated_messages = self.translate_messages(messages)
         # make API call
         completion = await self.client.create_chat_completion(
             model=self.model, messages=translated_messages, tools=tool_specs, **self.hyperparams, **hyperparams