[computer-use-demo] Tool execution hangs with timeout error

[JoshuaAIHAHA]

Root Cause Analysis The tool execution hang appears to stem from several implementation issues:

bash.py Implementation Issues: Hard-coded 120-second timeout (_timeout = 120.0) Inefficient buffer handling (polling with 0.2s delay) Entire buffer decoded at once No streaming/chunking of large outputs Current problematic implementation:

Current inefficient approach in bash.py

async def run(self, command: str):

Entire output loaded into memory at once

returncode, output, error = await run(
    command,
    timeout=120.0  # Hard-coded timeout
)
return CLIResult(output=output, error=error)  # No chunking

Impact on Users This issue severely impacts users when:

Listing directories with >1000 files (output >16KB) Reading large log files Running system queries that return substantial data Users must refresh the page every 5 minutes, breaking their workflow and losing command history. Base Architecture Findings: ToolResult class supports output combination No built-in streaming support Error handling focuses on immediate failures rather than timeouts Proposed Solutions Buffer Handling (Priority 1): Example implementation approach:

async def run(self, command: str): CHUNK_SIZE = 8000 async for chunk in stream_command(command): if len(chunk) > CHUNK_SIZE: yield process_chunk(chunk) else: yield chunk

Implement chunked reading instead of full buffer decode Add output streaming capabilities Consider increasing timeout for known large operations Add buffer size monitoring Error Handling (Priority 2): Add specific timeout recovery mechanisms Implement automatic retry logic for buffer overflows Add progress indicators for long-running operations Result Management (Priority 3): Add streaming result support to ToolResult class Implement progressive output updates Add memory usage monitoring Alternative Approaches Considered: Process spawning: Split large commands into smaller sub-processes Output pagination: Add --max-output flag to limit initial output Client-side caching: Store partial results to prevent complete reruns Looking forward to feedback on these approaches, particularly the chunked implementation example.

[JoshuaAIHAHA]

Update: I need to correct my initial analysis - further investigation revealed a different root cause.

The timeout issues were not related to buffer handling or large outputs as initially suspected, but rather stemmed from event loop management. Here's what I found:

ACTUAL ROOT CAUSE:

• Random timeout errors were occurring due to premature event loop closure
• Issue manifested as "timed out: bash has not returned in 120.0 seconds and must be restarted"
• Problem occurred with both small and large outputs, indicating it wasn't buffer-related

  The Fix

The solution was much simpler than my original proposal. The key change was making the stop() method properly async and awaiting process termination:

async def stop(self):
    if self._process.returncode is None:
        self._process.terminate()
        await self._process.wait()  # Ensure process termination

Testing Results The fix has been tested with various scenarios including:

Background processes Multiple parallel processes Mixed stdout/stderr operations Rapid successive commands Complex process management All tests passed without timeout errors, regardless of output size.

Retracting Original Proposal Therefore, I'm retracting my original buffer handling improvement proposal as it was addressing the wrong problem. The simpler event loop management fix appears to have resolved the timeout issues.

I apologize for any confusion my initial analysis may have caused. This is a good reminder that thorough investigation can sometimes reveal simpler solutions than initially suspected.