tidy up

Author: s-alexey

src/kaggle_benchmarks/actors/openai.py

@@ -14,7 +14,6 @@
 
 import itertools
 import json
-import logging
 from typing import Any, TypeVar
 
 import openai
@@ -77,19 +76,7 @@ def _invoke(
         if system:
             api_kwargs["instructions"] = system
 
-        try:
-            return self._call_api(raw_messages, **api_kwargs)
-        except openai.BadRequestError as e:
-            logging.warning(f"encounter {e}. Trying out disabling structured output.")
-            raise e
-            return self._simulate_structured_response(
-                messages=messages,
-                system=system,
-                schema_instructions=system,
-                temperature=temperature,
-                seed=seed,
-                tools=tools,
-            )
+        return self._call_api(raw_messages, **api_kwargs)
 
     def dump_image(self, image: images.ImageContent) -> list[dict]:
         """Serializes an image content object into an API-compatible format."""
@@ -304,7 +291,7 @@ def __init__(self, client: openai.OpenAI, model: str, **kwargs):
             }
         elif "deepseek" in model:
             kwargs["support_vision"] = False
-            kwargs["support_structured_outputs"] = False
+            kwargs["support_structured_outputs"] = True
         kwargs.setdefault("support_tool_calling", False)
         super().__init__(client, model, **kwargs)
 

src/kaggle_benchmarks/messages.py

@@ -17,6 +17,8 @@
 import warnings
 from typing import TYPE_CHECKING, Any, Generic, Iterable, TypeVar
 
+import pydantic
+
 from kaggle_benchmarks import events, utils
 
 if TYPE_CHECKING:
@@ -75,6 +77,8 @@ def usage(self):
     def payload(self) -> str | list[dict]:
         if hasattr(self.content, "get_payload"):
             return self.content.get_payload()
+        if isinstance(self.content, pydantic.BaseModel):
+            return self.content.model_dump_json()
         if dataclasses.is_dataclass(self.content) and not isinstance(
             self.content, type
         ):