Handle replayed response output items

Author: raashish1601

src/openai/resources/responses/_input.py

@@ -0,0 +1,20 @@
+from __future__ import annotations
+
+from typing import Any, Iterable
+
+from ..._types import Omit, omit
+from ..._models import BaseModel
+
+
+def sanitize_response_input(
+    input: str | Iterable[Any] | None | Omit,
+) -> str | list[Any] | None | Omit:
+    if input is omit or input is None or isinstance(input, str):
+        return input
+
+    return [
+        item.to_dict(mode="json", exclude_unset=True, exclude_none=True)
+        if isinstance(item, BaseModel)
+        else item
+        for item in input
+    ]

src/openai/resources/responses/input_tokens.py

@@ -8,6 +8,7 @@
 import httpx
 
 from ... import _legacy_response
+from ._input import sanitize_response_input
 from ..._types import Body, Omit, Query, Headers, NotGiven, omit, not_given
 from ..._utils import maybe_transform, async_maybe_transform
 from ..._compat import cached_property
@@ -129,7 +130,7 @@ def count(
             body=maybe_transform(
                 {
                     "conversation": conversation,
-                    "input": input,
+                    "input": sanitize_response_input(input),
                     "instructions": instructions,
                     "model": model,
                     "parallel_tool_calls": parallel_tool_calls,
@@ -255,7 +256,7 @@ async def count(
             body=await async_maybe_transform(
                 {
                     "conversation": conversation,
-                    "input": input,
+                    "input": sanitize_response_input(input),
                     "instructions": instructions,
                     "model": model,
                     "parallel_tool_calls": parallel_tool_calls,

src/openai/resources/responses/responses.py

@@ -14,6 +14,7 @@
 from pydantic import BaseModel
 
 from ... import _legacy_response
+from ._input import sanitize_response_input
 from ..._types import NOT_GIVEN, Body, Omit, Query, Headers, NoneType, NotGiven, omit, not_given
 from ..._utils import is_given, path_template, maybe_transform, strip_not_given, async_maybe_transform
 from ..._compat import cached_property
@@ -903,7 +904,7 @@ def create(
                     "context_management": context_management,
                     "conversation": conversation,
                     "include": include,
-                    "input": input,
+                    "input": sanitize_response_input(input),
                     "instructions": instructions,
                     "max_output_tokens": max_output_tokens,
                     "max_tool_calls": max_tool_calls,
@@ -1217,7 +1218,7 @@ def parser(raw_response: Response) -> ParsedResponse[TextFormatT]:
                     "context_management": context_management,
                     "conversation": conversation,
                     "include": include,
-                    "input": input,
+                    "input": sanitize_response_input(input),
                     "instructions": instructions,
                     "max_output_tokens": max_output_tokens,
                     "max_tool_calls": max_tool_calls,
@@ -1717,7 +1718,7 @@ def compact(
             body=maybe_transform(
                 {
                     "model": model,
-                    "input": input,
+                    "input": sanitize_response_input(input),
                     "instructions": instructions,
                     "previous_response_id": previous_response_id,
                     "prompt_cache_key": prompt_cache_key,
@@ -2570,7 +2571,7 @@ async def create(
                     "context_management": context_management,
                     "conversation": conversation,
                     "include": include,
-                    "input": input,
+                    "input": sanitize_response_input(input),
                     "instructions": instructions,
                     "max_output_tokens": max_output_tokens,
                     "max_tool_calls": max_tool_calls,
@@ -2888,7 +2889,7 @@ def parser(raw_response: Response) -> ParsedResponse[TextFormatT]:
                     "context_management": context_management,
                     "conversation": conversation,
                     "include": include,
-                    "input": input,
+                    "input": sanitize_response_input(input),
                     "instructions": instructions,
                     "max_output_tokens": max_output_tokens,
                     "max_tool_calls": max_tool_calls,
@@ -3388,7 +3389,7 @@ async def compact(
             body=await async_maybe_transform(
                 {
                     "model": model,
-                    "input": input,
+                    "input": sanitize_response_input(input),
                     "instructions": instructions,
                     "previous_response_id": previous_response_id,
                     "prompt_cache_key": prompt_cache_key,

tests/lib/responses/test_responses.py

@@ -1,13 +1,19 @@
 from __future__ import annotations
 
+import json
 from typing_extensions import TypeVar
 
+import httpx
 import pytest
 from respx import MockRouter
 from inline_snapshot import snapshot
 
 from openai import OpenAI, AsyncOpenAI
 from openai._utils import assert_signatures_in_sync
+from openai._compat import parse_obj
+from openai.types.responses.response import Response
+from openai.types.responses.response_reasoning_item import ResponseReasoningItem
+from openai.types.responses.response_function_tool_call import ResponseFunctionToolCall
 
 from ...conftest import base_url
 from ..snapshots import make_snapshot_request
@@ -41,6 +47,73 @@ def test_output_text(client: OpenAI, respx_mock: MockRouter) -> None:
     )
 
 
+@pytest.mark.respx(base_url=base_url)
+def test_response_output_items_can_be_replayed_without_null_only_fields(
+    client: OpenAI,
+    respx_mock: MockRouter,
+) -> None:
+    route = respx_mock.post("/responses").mock(
+        return_value=httpx.Response(
+            200,
+            json={
+                "id": "resp_123",
+                "object": "response",
+                "created_at": 0,
+                "model": "gpt-4o-mini",
+                "output": [],
+                "parallel_tool_calls": True,
+                "tool_choice": "auto",
+                "tools": [],
+            },
+        )
+    )
+
+    reasoning = parse_obj(
+        ResponseReasoningItem,
+        {
+            "id": "rs_123",
+            "type": "reasoning",
+            "summary": [],
+            "encrypted_content": None,
+            "status": None,
+        },
+    )
+    function_call = parse_obj(
+        ResponseFunctionToolCall,
+        {
+            "arguments": "{}",
+            "call_id": "call_123",
+            "name": "weather",
+            "type": "function_call",
+            "id": "fc_123",
+            "status": None,
+        },
+    )
+
+    response = client.responses.create(
+        model="gpt-4o-mini",
+        input=[reasoning, function_call],
+    )
+
+    assert isinstance(response, Response)
+
+    request_body = json.loads(route.calls[0].request.content.decode("utf-8"))
+    assert request_body["input"] == [
+        {
+            "id": "rs_123",
+            "summary": [],
+            "type": "reasoning",
+        },
+        {
+            "arguments": "{}",
+            "call_id": "call_123",
+            "id": "fc_123",
+            "name": "weather",
+            "type": "function_call",
+        },
+    ]
+
+
 @pytest.mark.parametrize("sync", [True, False], ids=["sync", "async"])
 def test_stream_method_definition_in_sync(sync: bool, client: OpenAI, async_client: AsyncOpenAI) -> None:
     checking_client: OpenAI | AsyncOpenAI = client if sync else async_client