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fix(agent): nudge once before the housekeeping empty-follow-up shortcut #65674

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fix(agent): nudge once before the housekeeping empty-follow-up shortcut #65674

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80 changes: 52 additions & 28 deletions agent/conversation_loop.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6586,18 +6586,54 @@ def _perform_api_call(next_api_kwargs):
agent._response_was_previewed = False
break

# Nudge availability is computed up front because it gates
# the housekeeping fallback shortcut below (#65600): a
# single empty completion after a housekeeping-only turn is
# NOT a reliable "the model is done" signal — weak/quantized
# local models intermittently choke and return empty right
# after a housekeeping call. Spend the one nudge retry
# first; the shortcut then handles the SECOND consecutive
# empty, which is a much stronger done signal.
_prior_was_tool = any(
m.get("role") == "tool"
for m in messages[-5:] # check recent messages
)
# Detect Qwen3/Ollama-style in-content thinking blocks.
# Ollama puts <think> in the content field (not in
# reasoning_content), so _has_structured below would
# miss it. We check here so thinking-only responses
# after tool calls route to prefill instead of nudge.
_has_inline_thinking = bool(
re.search(
r'<think>|<thinking>|<reasoning>',
final_response or "",
re.IGNORECASE,
)
)
_nudge_available = (
_prior_was_tool
and not getattr(agent, "_post_tool_empty_retried", False)
and not _has_inline_thinking # thinking model still working — let prefill handle
)

# If the previous turn already delivered real content alongside
# HOUSEKEEPING tool calls (e.g. "You're welcome!" + memory save),
# the model has nothing more to say. Use the earlier content
# immediately instead of wasting API calls on retries.
# instead of wasting API calls on retries.
# NOTE: Only use this shortcut when ALL tools in that turn were
# housekeeping (memory, todo, etc.). When substantive tools
# were called (terminal, search_files, etc.), the content was
# likely mid-task narration ("I'll scan the directory...") and
# the empty follow-up means the model choked — let the
# post-tool nudge below handle that instead of exiting early.
# The `not _nudge_available` gate defers the shortcut past
# one nudge attempt (#65600) — see the comment above.
fallback = getattr(agent, '_last_content_with_tools', None)
if fallback and getattr(agent, '_last_content_tools_all_housekeeping', False):
if (
fallback
and getattr(agent, '_last_content_tools_all_housekeeping', False)
and not _nudge_available
):
_turn_exit_reason = "fallback_prior_turn_content"
logger.info("Empty follow-up after tool calls — using prior turn content as final response")
agent._emit_status("↻ Empty response after tool calls — using earlier content as final answer")
Expand All @@ -6614,43 +6650,31 @@ def _perform_api_call(next_api_kwargs):

# ── Post-tool-call empty response nudge ───────────
# The model returned empty after executing tool calls.
# This covers two cases:
# This covers three cases:
# (a) No prior-turn content at all — model went silent
# (b) Prior turn had content + SUBSTANTIVE tools (the
# fallback above was skipped because the content
# was mid-task narration, not a final answer)
# (c) Prior turn was housekeeping-only — the fallback
# above is deferred until this one nudge is spent,
# so a choked weak model gets a chance to finish
# instead of silently ending the turn (#65600)
# Instead of giving up, nudge the model to continue by
# appending a user-level hint. This is the #9400 case:
# weaker models (mimo-v2-pro, GLM-5, etc.) sometimes
# return empty after tool results instead of continuing
# to the next step. One retry with a nudge usually
# fixes it.
_prior_was_tool = any(
m.get("role") == "tool"
for m in messages[-5:] # check recent messages
)
# Detect Qwen3/Ollama-style in-content thinking blocks.
# Ollama puts <think> in the content field (not in
# reasoning_content), so _has_structured below would
# miss it. We check here so thinking-only responses
# after tool calls route to prefill instead of nudge.
_has_inline_thinking = bool(
re.search(
r'<think>|<thinking>|<reasoning>',
final_response or "",
re.IGNORECASE,
)
)
if (
_prior_was_tool
and not getattr(agent, "_post_tool_empty_retried", False)
and not _has_inline_thinking # thinking model still working — let prefill handle
):
if _nudge_available:
agent._post_tool_empty_retried = True
# Clear stale narration so it doesn't resurface
# on a later empty response after the nudge.
agent._last_content_with_tools = None
agent._last_content_tools_all_housekeeping = False
# Clear stale substantive narration so it doesn't
# resurface on a later empty response after the nudge.
# A HOUSEKEEPING fallback is deliberately preserved:
# if the nudge also comes back empty, the shortcut
# above still delivers the prior content instead of
# dead-ending in empty-response retries (#65600).
if not getattr(agent, '_last_content_tools_all_housekeeping', False):
agent._last_content_with_tools = None
logger.info(
"Empty response after tool calls — nudging model "
"to continue processing"
Expand Down
137 changes: 137 additions & 0 deletions tests/run_agent/test_conversation_fallback_state.py
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Original file line number Diff line number Diff line change
Expand Up @@ -205,3 +205,140 @@ def test_bare_tool_marker_is_not_reused_as_final_response():
f"Expected 3 API calls (including nudge), got: {result['api_calls']}."
)


def test_housekeeping_only_turn_still_sets_fallback():
"""Regression: pure housekeeping turns (content + only housekeeping tools)
must still set the fallback so the post-response mute path works. This
verifies the fix doesn't break the original use case the fallback was
designed for.

Since #65600 the shortcut is deferred past one nudge retry: the first
empty completion gets a nudge, and only a SECOND consecutive empty is
treated as "the model is done" and served the fallback content.
"""
with (
patch("run_agent.get_tool_definitions", return_value=_tool_defs("memory")),
patch("run_agent.check_toolset_requirements", return_value={}),
patch("run_agent.OpenAI"),
):
agent = AIAgent(
api_key="test-key",
base_url="https://openrouter.ai/api/v1/",
quiet_mode=True,
skip_context_files=True,
skip_memory=True,
)

agent._cached_system_prompt = "You are helpful."
agent._use_prompt_caching = False
agent.tool_delay = 0
agent.compression_enabled = False
agent.save_trajectories = False
agent.valid_tool_names = {"memory"}
agent.client = MagicMock()
agent.client.chat.completions.create.side_effect = [
# Turn 1: Content + housekeeping tool (should set fallback)
_response(
content="You're welcome!",
finish_reason="tool_calls",
tool_calls=[_tool_call("memory", "mem1")],
),
# Turn 2: Empty response (should spend the one nudge retry)
_response(content="", finish_reason="stop"),
# Turn 3: Empty again (nudge spent — NOW use the housekeeping fallback)
_response(content="", finish_reason="stop"),
]

with (
patch("run_agent.handle_function_call", return_value="ok"),
patch.object(agent, "_persist_session"),
patch.object(agent, "_save_trajectory"),
patch.object(agent, "_cleanup_task_resources"),
):
result = agent.run_conversation("save this")

assert result["final_response"] == "You're welcome!", (
f"Expected housekeeping fallback content, got: {result['final_response']}. "
f"Pure housekeeping turns should still set the fallback."
)
assert "fallback_prior_turn_content" in result.get("turn_exit_reason", ""), (
f"Expected fallback_prior_turn_content exit, got: {result['turn_exit_reason']}."
)
assert result["api_calls"] == 3, (
f"Expected 3 API calls (housekeeping turn, empty, nudged empty), "
f"got: {result['api_calls']}."
)


def test_housekeeping_empty_follow_up_gets_one_nudge_before_fallback():
"""
Regression test for #65600.

An empty completion right after a housekeeping-only tool turn is not
always "the model has nothing more to say" — weak/quantized local models
intermittently choke and return empty mid-task. The shortcut used to
fire immediately, recycling the prior turn's narration as the final
response and silently ending the turn.

Test sequence:
1. Content + skill_manage (housekeeping) → sets fallback
2. Empty completion → must get the standard post-tool nudge, NOT the
immediate fallback shortcut
3. Model recovers with real content → that content is the final response

Before the fix: step 2 took the shortcut, the final response was the
recycled step-1 narration, and the model never got a chance to finish
(2 API calls, reason=fallback_prior_turn_content).
"""
with (
patch("run_agent.get_tool_definitions", return_value=_tool_defs("skill_manage")),
patch("run_agent.check_toolset_requirements", return_value={}),
patch("run_agent.OpenAI"),
):
agent = AIAgent(
api_key="test-key",
base_url="https://openrouter.ai/api/v1/",
quiet_mode=True,
skip_context_files=True,
skip_memory=True,
)

agent._cached_system_prompt = "You are helpful."
agent._use_prompt_caching = False
agent.tool_delay = 0
agent.compression_enabled = False
agent.save_trajectories = False
agent.valid_tool_names = {"skill_manage"}
agent.client = MagicMock()
agent.client.chat.completions.create.side_effect = [
# Turn 1: Mid-task narration + housekeeping tool (sets fallback)
_response(
content="Reviewing the skill library now.",
finish_reason="tool_calls",
tool_calls=[_tool_call("skill_manage", "skill1")],
),
# Turn 2: Model chokes — genuinely empty, but NOT done
_response(content="", finish_reason="stop"),
# Turn 3: Nudge lands, model finishes the task for real
_response(content="Skill library updated with two new entries.", finish_reason="stop"),
]

with (
patch("run_agent.handle_function_call", return_value="ok"),
patch.object(agent, "_persist_session"),
patch.object(agent, "_save_trajectory"),
patch.object(agent, "_cleanup_task_resources"),
):
result = agent.run_conversation("review the skill library")

assert result["final_response"] == "Skill library updated with two new entries.", (
f"Expected the post-nudge recovery response, got: {result['final_response']}. "
f"The housekeeping fallback shortcut fired before the nudge retry."
)
assert result["api_calls"] == 3, (
f"Expected 3 API calls (housekeeping turn, choke, nudge recovery), "
f"got: {result['api_calls']}. 2 means the shortcut bypassed the nudge."
)
assert result["turn_exit_reason"].startswith("text_response"), (
f"Expected text_response exit, got: {result['turn_exit_reason']}."
)
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