Memory leak in parse_response usage of pydantic

src/openai/lib/_parsing/_responses.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import json
-from typing import TYPE_CHECKING, List, Iterable, cast
+from typing import TYPE_CHECKING, Any, List, Iterable, cast
 from typing_extensions import TypeVar, assert_never
 
 import pydantic
@@ -68,7 +68,7 @@ def parse_response(
 
                 content_list.append(
                     construct_type_unchecked(
-                        type_=ParsedResponseOutputText[TextFormatT],
+                        type_=cast(Any, ParsedResponseOutputText),
                         value={
                             **item.to_dict(),
                             "parsed": parse_text(item.text, text_format=text_format),
@@ -78,7 +78,7 @@ def parse_response(
 
             output_list.append(
                 construct_type_unchecked(
-                    type_=ParsedResponseOutputMessage[TextFormatT],
+                    type_=cast(Any, ParsedResponseOutputMessage),
                     value={
                         **output.to_dict(),
                         "content": content_list,
@@ -130,7 +130,7 @@ def parse_response(
             output_list.append(output)
 
     return construct_type_unchecked(
-        type_=ParsedResponse[TextFormatT],
+        type_=cast(Any, ParsedResponse),
         value={
             **response.to_dict(),
             "output": output_list,

tests/lib/responses/test_parsing.py

@@ -0,0 +1,65 @@
+from __future__ import annotations
+
+from typing import Any
+
+import pydantic
+
+import openai._models as models
+from openai.lib._parsing._responses import parse_response
+from openai.types.responses import Response
+
+
+_MOCK_RESPONSE_JSON: dict[str, Any] = {
+    "id": "resp_poc",
+    "object": "response",
+    "created_at": 1234567890.0,
+    "model": "gpt-5.4",
+    "parallel_tool_calls": True,
+    "status": "completed",
+    "tool_choice": "auto",
+    "tools": [],
+    "output": [
+        {
+            "type": "message",
+            "id": "msg_poc",
+            "status": "completed",
+            "role": "assistant",
+            "content": [
+                {
+                    "type": "output_text",
+                    "text": '{"message": "Hello! How can I help?"}',
+                    "annotations": [],
+                }
+            ],
+        }
+    ],
+    "text": {"format": {"type": "text"}},
+    "usage": {
+        "input_tokens": 10,
+        "output_tokens": 20,
+        "total_tokens": 30,
+        "input_tokens_details": {"cached_tokens": 0},
+        "output_tokens_details": {"reasoning_tokens": 0},
+    },
+}
+
+
+class ChatbotResponse(pydantic.BaseModel):
+    message: str
+    intent: str | None = None
+
+
+def test_parse_response_does_not_use_non_model_validation(monkeypatch: Any) -> None:
+    def fail_if_called(*, type_: Any, value: object) -> Any:
+        raise AssertionError(f"unexpected non-model validation for {type_}")
+
+    monkeypatch.setattr(models, "_validate_non_model_type", fail_if_called)
+
+    raw_response = Response.model_validate(_MOCK_RESPONSE_JSON)
+    parsed = parse_response(response=raw_response, text_format=ChatbotResponse, input_tools=None)
+
+    assert parsed.output[0].type == "message"
+    output_text = parsed.output[0].content[0]
+    assert output_text.type == "output_text"
+    assert output_text.parsed is not None
+    assert output_text.parsed.message == "Hello! How can I help?"