fix(agent): time out no-tools model requests

nanobot/agent/runner.py

@@ -922,18 +922,7 @@ class AgentRunner:
         conversation_state: ProviderConversationStateController,
         provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
-        timeout_s: float | None = spec.llm_timeout_s
-        if timeout_s is None:
-            # Default to a finite timeout to avoid per-session lock starvation when an LLM
-            # request hangs indefinitely (e.g. gateway/network stall).
-            # Set NANOBOT_LLM_TIMEOUT_S=0 to disable.
-            raw = os.environ.get("NANOBOT_LLM_TIMEOUT_S", "300").strip()
-            try:
-                timeout_s = float(raw)
-            except (TypeError, ValueError):
-                timeout_s = 300.0
-        if timeout_s <= 0:
-            timeout_s = None
+        timeout_s = self._resolve_llm_timeout_s(spec)
 
         kwargs = self._build_request_kwargs(
             spec,
@@ -1302,10 +1291,38 @@ class AgentRunner:
             messages,
             tools=None,
         )
-        return await spec.runtime.provider.chat_with_retry(
+        coro = spec.runtime.provider.chat_with_retry(
             **kwargs,
             provider_context=provider_context,
         )
+        timeout_s = self._resolve_llm_timeout_s(spec)
+        try:
+            return (
+                await coro
+                if timeout_s is None
+                else await asyncio.wait_for(coro, timeout=timeout_s)
+            )
+        except asyncio.TimeoutError:
+            return LLMResponse(
+                content=f"Error calling LLM: timed out after {timeout_s:g}s",
+                finish_reason="error",
+                error_kind="timeout",
+            )
+
+    @staticmethod
+    def _resolve_llm_timeout_s(spec: AgentRunSpec) -> float | None:
+        """Resolve the wall-clock limit shared by every model request path."""
+        timeout_s = spec.llm_timeout_s
+        if timeout_s is None:
+            # Default to a finite timeout to avoid per-session lock starvation when an LLM
+            # request hangs indefinitely (e.g. gateway/network stall).
+            # Set NANOBOT_LLM_TIMEOUT_S=0 to disable.
+            raw = os.environ.get("NANOBOT_LLM_TIMEOUT_S", "300").strip()
+            try:
+                timeout_s = float(raw)
+            except (TypeError, ValueError):
+                timeout_s = 300.0
+        return timeout_s if timeout_s > 0 else None
 
     @staticmethod
     def _budget_exhausted_finalization_messages(

tests/agent/test_runner_core.py

@@ -499,6 +499,55 @@ async def test_runner_times_out_hung_llm_request():
     assert "timed out" in (result.final_content or "").lower()
 
 
+@pytest.mark.asyncio
+async def test_runner_times_out_hung_max_iteration_finalization():
+    from nanobot.agent.runner import AgentRunner
+
+    provider = MagicMock()
+    calls = 0
+
+    async def chat_with_retry(**kwargs):
+        nonlocal calls
+        calls += 1
+        if calls == 1:
+            return LLMResponse(
+                content="",
+                tool_calls=[
+                    ToolCallRequest(
+                        id="call_1",
+                        name="probe",
+                        arguments={},
+                    )
+                ],
+                finish_reason="tool_calls",
+            )
+        await asyncio.Event().wait()
+
+    provider.chat_with_retry = chat_with_retry
+    tools = MagicMock()
+    tools.get_definitions.return_value = []
+    tools.execute = AsyncMock(return_value="ok")
+
+    result = await asyncio.wait_for(
+        AgentRunner().run(make_run_spec(
+            provider,
+            initial_messages=[{"role": "user", "content": "run the probe"}],
+            tools=tools,
+            model="test-model",
+            max_iterations=1,
+            max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
+            max_iterations_message="fallback after {max_iterations} iteration",
+            llm_timeout_s=0.01,
+        )),
+        timeout=1.0,
+    )
+
+    assert calls == 2
+    assert result.stop_reason == "max_iterations"
+    assert result.error is None
+    assert result.final_content == "fallback after 1 iteration"
+
+
 @pytest.mark.asyncio
 async def test_runner_applies_outer_wall_timeout_to_streaming_requests():
     from nanobot.agent.hook import AgentHook, AgentHookContext