for message in messages:
    if not message.get("role"): message["role"] = "assistant"
    if message.get("tool_calls"):
        message["tool_calls"] = jsonify_tools(tools=message["tool_calls"])  # now List[dict]
    convert_msg_to_dict = cast(AllMessageValues, convert_to_dict(message))  # model_dump → warns

---

for message in messages:
    if isinstance(message, BaseModel): message = message.model_dump(exclude_none=True)
    else: message = dict(message)
    if not message.get("role"): message["role"] = "assistant"
    if message.get("tool_calls"):
        message["tool_calls"] = jsonify_tools(tools=message["tool_calls"])
    new_messages.append(cleanup_none_field_in_message(message=message))

---

import warnings, litellm
from litellm.types.utils import Message, ChatCompletionMessageToolCall
from litellm.types.utils import Function
from litellm.utils import validate_and_fix_openai_messages

warnings.filterwarnings('error', message='Pydantic serializer warnings')

tc = ChatCompletionMessageToolCall(id='toolu_1', type='function',
    function=Function(name='add', arguments='{"a":1,"b":2}'))
msg = Message(content='', role='assistant', tool_calls=[tc])

validate_and_fix_openai_messages([
    {'role': 'user', 'content': 'hi'},
    msg,
    {'role': 'tool', 'tool_call_id': 'toolu_1', 'content': '3'},
])

---

UserWarning: Pydantic serializer warnings:
  PydanticSerializationUnexpectedValue(Expected `ChatCompletionMessageToolCall` -
  serialized value may not be as expected
  [field_name='tool_calls', input_value={...}, input_type=dict])

---