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fix: add timeout handling for Docker operations and improve error messages

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- Add SandboxInitializationError exception for sandbox/Docker failures
- Add 60-second timeout to Docker client initialization
- Add _exec_run_with_timeout() method using ThreadPoolExecutor for exec_run calls
- Catch ConnectionError and Timeout exceptions from requests library
- Add _handle_sandbox_error() and _handle_llm_error() methods in base_agent.py
- Handle sandbox_error_details tool in TUI for displaying errors
- Increase TUI truncation limits for better error visibility
- Update all Docker error messages with helpful hint:
  'Please ensure Docker Desktop is installed and running, and try running strix again.'
This commit is contained in:
0xallam
2026-01-08 16:11:15 -08:00
committed by Ahmed Allam
parent c327ce621f
commit 740fb3ed40
5 changed files with 193 additions and 80 deletions
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strix/agents/base_agent.py
+96 -50
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@@ -16,6 +16,7 @@ from jinja2 import (
from strix.llm import LLM, LLMConfig, LLMRequestFailedError
from strix.llm.utils import clean_content
from strix.runtime import SandboxInitializationError
from strix.tools import process_tool_invocations
from .state import AgentState
@@ -145,18 +146,16 @@ class BaseAgent(metaclass=AgentMeta):
if self.state.parent_id is None and agents_graph_actions._root_agent_id is None:
agents_graph_actions._root_agent_id = self.state.agent_id
def cancel_current_execution(self) -> None:
if self._current_task and not self._current_task.done():
self._current_task.cancel()
self._current_task = None
async def agent_loop(self, task: str) -> dict[str, Any]: # noqa: PLR0912, PLR0915
await self._initialize_sandbox_and_state(task)
from strix.telemetry.tracer import get_global_tracer
tracer = get_global_tracer()
try:
await self._initialize_sandbox_and_state(task)
except SandboxInitializationError as e:
return self._handle_sandbox_error(e, tracer)
while True:
self._check_agent_messages(self.state)
@@ -232,37 +231,9 @@ class BaseAgent(metaclass=AgentMeta):
continue
except LLMRequestFailedError as e:
error_msg = str(e)
error_details = getattr(e, "details", None)
self.state.add_error(error_msg)
if self.non_interactive:
self.state.set_completed({"success": False, "error": error_msg})
if tracer:
tracer.update_agent_status(self.state.agent_id, "failed", error_msg)
if error_details:
tracer.log_tool_execution_start(
self.state.agent_id,
"llm_error_details",
{"error": error_msg, "details": error_details},
)
tracer.update_tool_execution(
tracer._next_execution_id - 1, "failed", error_details
)
return {"success": False, "error": error_msg}
self.state.enter_waiting_state(llm_failed=True)
if tracer:
tracer.update_agent_status(self.state.agent_id, "llm_failed", error_msg)
if error_details:
tracer.log_tool_execution_start(
self.state.agent_id,
"llm_error_details",
{"error": error_msg, "details": error_details},
)
tracer.update_tool_execution(
tracer._next_execution_id - 1, "failed", error_details
)
result = self._handle_llm_error(e, tracer)
if result is not None:
return result
continue
except (RuntimeError, ValueError, TypeError) as e:
@@ -439,18 +410,6 @@ class BaseAgent(metaclass=AgentMeta):
return False
async def _handle_iteration_error(
self,
error: RuntimeError | ValueError | TypeError | asyncio.CancelledError,
tracer: Optional["Tracer"],
) -> bool:
error_msg = f"Error in iteration {self.state.iteration}: {error!s}"
logger.exception(error_msg)
self.state.add_error(error_msg)
if tracer:
tracer.update_agent_status(self.state.agent_id, "error")
return True
def _check_agent_messages(self, state: AgentState) -> None: # noqa: PLR0912
try:
from strix.tools.agents_graph.agents_graph_actions import _agent_graph, _agent_messages
@@ -535,3 +494,90 @@ class BaseAgent(metaclass=AgentMeta):
logger = logging.getLogger(__name__)
logger.warning(f"Error checking agent messages: {e}")
return
def _handle_sandbox_error(
self,
error: SandboxInitializationError,
tracer: Optional["Tracer"],
) -> dict[str, Any]:
error_msg = str(error.message)
error_details = error.details
self.state.add_error(error_msg)
if self.non_interactive:
self.state.set_completed({"success": False, "error": error_msg})
if tracer:
tracer.update_agent_status(self.state.agent_id, "failed", error_msg)
if error_details:
exec_id = tracer.log_tool_execution_start(
self.state.agent_id,
"sandbox_error_details",
{"error": error_msg, "details": error_details},
)
tracer.update_tool_execution(exec_id, "failed", {"details": error_details})
return {"success": False, "error": error_msg, "details": error_details}
self.state.enter_waiting_state()
if tracer:
tracer.update_agent_status(self.state.agent_id, "sandbox_failed", error_msg)
if error_details:
exec_id = tracer.log_tool_execution_start(
self.state.agent_id,
"sandbox_error_details",
{"error": error_msg, "details": error_details},
)
tracer.update_tool_execution(exec_id, "failed", {"details": error_details})
return {"success": False, "error": error_msg, "details": error_details}
def _handle_llm_error(
self,
error: LLMRequestFailedError,
tracer: Optional["Tracer"],
) -> dict[str, Any] | None:
error_msg = str(error)
error_details = getattr(error, "details", None)
self.state.add_error(error_msg)
if self.non_interactive:
self.state.set_completed({"success": False, "error": error_msg})
if tracer:
tracer.update_agent_status(self.state.agent_id, "failed", error_msg)
if error_details:
exec_id = tracer.log_tool_execution_start(
self.state.agent_id,
"llm_error_details",
{"error": error_msg, "details": error_details},
)
tracer.update_tool_execution(exec_id, "failed", {"details": error_details})
return {"success": False, "error": error_msg}
self.state.enter_waiting_state(llm_failed=True)
if tracer:
tracer.update_agent_status(self.state.agent_id, "llm_failed", error_msg)
if error_details:
exec_id = tracer.log_tool_execution_start(
self.state.agent_id,
"llm_error_details",
{"error": error_msg, "details": error_details},
)
tracer.update_tool_execution(exec_id, "failed", {"details": error_details})
return None
async def _handle_iteration_error(
self,
error: RuntimeError | ValueError | TypeError | asyncio.CancelledError,
tracer: Optional["Tracer"],
) -> bool:
error_msg = f"Error in iteration {self.state.iteration}: {error!s}"
logger.exception(error_msg)
self.state.add_error(error_msg)
if tracer:
tracer.update_agent_status(self.state.agent_id, "error")
return True
def cancel_current_execution(self) -> None:
if self._current_task and not self._current_task.done():
self._current_task.cancel()
self._current_task = None