chore: import upstream snapshot with attribution

tests/test_streaming_logging.py

@@ -0,0 +1,59 @@
+from __future__ import annotations
+
+import logging
+
+import pytest
+
+import agents._debug as _debug
+from agents import Agent, RunConfig
+from agents.items import ToolCallOutputItem
+from agents.run import AgentRunner
+from agents.run_context import RunContextWrapper
+from agents.run_state import RunState
+from tests.fake_model import FakeModel
+from tests.test_responses import get_text_message
+
+
+@pytest.mark.asyncio
+async def test_run_streamed_resume_omits_tool_output_in_log_when_dont_log(
+    monkeypatch, caplog
+) -> None:
+    monkeypatch.setattr(_debug, "DONT_LOG_TOOL_DATA", True)
+
+    model = FakeModel()
+    model.set_next_output([get_text_message("ok")])
+    agent = Agent(name="log-agent", model=model)
+    context_wrapper: RunContextWrapper[dict[str, str]] = RunContextWrapper(context={})
+    state = RunState(
+        context=context_wrapper,
+        original_input="hi",
+        starting_agent=agent,
+        max_turns=1,
+    )
+
+    raw_output = {
+        "type": "function_call_output",
+        "call_id": "call-1",
+        "output": "secret",
+    }
+    state._generated_items = [ToolCallOutputItem(agent=agent, raw_item=raw_output, output="secret")]
+
+    caplog.set_level(logging.DEBUG, logger="openai.agents")
+
+    runner = AgentRunner()
+    streamed_result = runner.run_streamed(agent, state, run_config=RunConfig())
+    async for _event in streamed_result.stream_events():
+        pass
+
+    record = next(
+        (
+            rec
+            for rec in caplog.records
+            if "Resuming from RunState in run_streaming()" in rec.message
+        ),
+        None,
+    )
+    assert record is not None
+    details = getattr(record, "generated_items_details", [])
+    assert details
+    assert "output" not in details[0]