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fix(chat): always persist reasoning_content on assistant event_payload

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Non-thinking profiles previously wrote model reasoning only as separate
event_type=reasoning rows whose event_payload held chunk_index metadata, so
JSON inspection showed tool payloads but no reasoning_content key.

Store the full merged reasoning blob on the primary assistant row whenever
present (same shape as thinking mode). Update instruction-leak filtering to
scan event_payload.reasoning_content as well as legacy reasoning rows.

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
oliver 2026-05-12 23:02:38 +08:00
parent c938147fdb
commit 5efac74f87
3 changed files with 35 additions and 19 deletions
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20
runtime/direct_loop.py
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@ -1008,7 +1008,6 @@ def _persist_assistant_step(
assistant_text: str,
reasoning_text: str,
llm_tool_calls: list[Any],
thinking_mode_enabled: bool = False,
) -> _LoopStepResult:
stored_tool_calls = []
for tc in llm_tool_calls:
@ -1025,16 +1024,11 @@ def _persist_assistant_step(
reasoning_full = "\n".join([str(x or "").strip() for x in reasoning_chunks if str(x or "").strip()]).strip()
# Keep empty body as-is when model returns nothing and there are no tool calls.
# The UI should treat this as an invisible intermediate/final empty response.
if not thinking_mode_enabled:
for idx, chunk in enumerate(reasoning_chunks):
store.add_message(
session_id=session_id,
role="assistant",
content=chunk,
turn_uuid=turn_uuid,
event_type="reasoning",
event_payload={"chunk_index": int(idx), "chunk_count": len(reasoning_chunks)},
)
#
# Persist full reasoning on the primary assistant row's ``event_payload.reasoning_content`` for
# both thinking and non-thinking profiles. Previously non-thinking used separate
# ``event_type=reasoning`` rows with only chunk_index in payload, so JSON inspection looked
# like "no reasoning_content anywhere" while tools carried rich ``event_payload``.
assistant_row = store.add_message(
session_id=session_id,
role="assistant",
@ -1042,7 +1036,7 @@ def _persist_assistant_step(
tool_calls=stored_tool_calls or None,
turn_uuid=turn_uuid,
event_type="tool_call" if stored_tool_calls else "assistant_text",
event_payload=({"reasoning_content": reasoning_full} if (thinking_mode_enabled and reasoning_full) else None),
event_payload=({"reasoning_content": reasoning_full} if reasoning_full else None),
)
return _LoopStepResult(
assistant_text=assistant_body,
@ -1453,7 +1447,6 @@ def run_oclaw_direct_loop(
assistant_text=assistant_text,
reasoning_text=reasoning_text,
llm_tool_calls=llm_tool_calls,
thinking_mode_enabled=bool(getattr(model, "thinking_mode_enabled", False)),
)
final_text = step.assistant_text
if not step.llm_tool_calls:
@ -1559,7 +1552,6 @@ def run_oclaw_direct_loop(
assistant_text=str(getattr(resp, "content", "") or ""),
reasoning_text=str(getattr(resp, "reasoning_content", "") or ""),
llm_tool_calls=[],
thinking_mode_enabled=bool(getattr(model, "thinking_mode_enabled", False)),
)
final_text = step.assistant_text