Enhance tool execution and logging in HermesAgentLoop
- Increased thread pool size for tool execution from 8 to 128 to improve concurrency and prevent starvation. - Added a function to resize the tool executor dynamically based on configuration. - Enhanced logging to track API call durations and tool execution times, including warnings for slow tools. - Improved overall performance monitoring by logging detailed information for each turn in the agent loop.
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teknium
@@ -15,6 +15,7 @@ import asyncio
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import concurrent.futures
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import json
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import logging
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import os
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import uuid
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from dataclasses import dataclass, field
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from typing import Any, Dict, List, Optional, Set
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@@ -24,7 +25,22 @@ from model_tools import handle_function_call
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# Thread pool for running sync tool calls that internally use asyncio.run()
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# (e.g., mini-swe-agent's modal/docker backends). Running them in a separate
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# thread gives them a clean event loop so they don't deadlock inside Atropos's loop.
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_tool_executor = concurrent.futures.ThreadPoolExecutor(max_workers=8)
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# Size must be large enough for concurrent eval tasks (e.g., 89 TB2 tasks all
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# making tool calls). Too small = thread pool starvation, tasks queue for minutes.
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# Resized at runtime by HermesAgentBaseEnv.__init__ via resize_tool_pool().
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_tool_executor = concurrent.futures.ThreadPoolExecutor(max_workers=128)
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def resize_tool_pool(max_workers: int):
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"""
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Replace the global tool executor with a new one of the given size.
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Called by HermesAgentBaseEnv.__init__ based on config.tool_pool_size.
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Safe to call before any tasks are submitted.
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"""
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global _tool_executor
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_tool_executor = concurrent.futures.ThreadPoolExecutor(max_workers=max_workers)
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logger.info("Tool thread pool resized to %d workers", max_workers)
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logger = logging.getLogger(__name__)
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@@ -155,7 +171,11 @@ class HermesAgentLoop:
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reasoning_per_turn = []
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tool_errors: List[ToolError] = []
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import time as _time
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for turn in range(self.max_turns):
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turn_start = _time.monotonic()
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# Build the chat_completion kwargs
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chat_kwargs = {
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"messages": messages,
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@@ -172,10 +192,12 @@ class HermesAgentLoop:
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chat_kwargs["max_tokens"] = self.max_tokens
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# Make the API call -- standard OpenAI spec
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api_start = _time.monotonic()
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try:
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response = await self.server.chat_completion(**chat_kwargs)
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except Exception as e:
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logger.error("API call failed on turn %d: %s", turn + 1, e)
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api_elapsed = _time.monotonic() - api_start
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logger.error("API call failed on turn %d (%.1fs): %s", turn + 1, api_elapsed, e)
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return AgentResult(
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messages=messages,
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managed_state=self._get_managed_state(),
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@@ -185,8 +207,10 @@ class HermesAgentLoop:
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tool_errors=tool_errors,
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)
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api_elapsed = _time.monotonic() - api_start
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if not response or not response.choices:
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logger.warning("Empty response on turn %d", turn + 1)
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logger.warning("Empty response on turn %d (api=%.1fs)", turn + 1, api_elapsed)
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return AgentResult(
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messages=messages,
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managed_state=self._get_managed_state(),
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@@ -265,14 +289,16 @@ class HermesAgentLoop:
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try:
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if tool_name == "terminal":
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import os
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backend = os.getenv("TERMINAL_ENV", "local")
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cmd_preview = args.get("command", "")[:80]
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print(f" 🖥️ [{backend}] $ {cmd_preview}")
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logger.info(
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"[%s] $ %s", self.task_id[:8], cmd_preview,
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)
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# Run tool calls in a thread pool so backends that use
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# asyncio.run() internally (modal, docker) get a clean
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# event loop instead of deadlocking inside Atropos's loop.
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tool_submit_time = _time.monotonic()
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loop = asyncio.get_event_loop()
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tool_result = await loop.run_in_executor(
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_tool_executor,
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@@ -280,6 +306,16 @@ class HermesAgentLoop:
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tool_name, args, task_id=self.task_id
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),
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)
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tool_elapsed = _time.monotonic() - tool_submit_time
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# Log slow tools and thread pool stats for debugging
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pool_active = _tool_executor._work_queue.qsize()
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if tool_elapsed > 30:
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logger.warning(
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"[%s] turn %d: %s took %.1fs (pool queue=%d)",
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self.task_id[:8], turn + 1, tool_name,
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tool_elapsed, pool_active,
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)
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except Exception as e:
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tool_result = json.dumps(
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{"error": f"Tool execution failed: {type(e).__name__}: {str(e)}"}
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@@ -320,10 +356,11 @@ class HermesAgentLoop:
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}
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)
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logger.debug(
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"Turn %d: %d tool calls executed",
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turn + 1,
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len(assistant_msg.tool_calls),
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turn_elapsed = _time.monotonic() - turn_start
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logger.info(
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"[%s] turn %d: api=%.1fs, %d tools, turn_total=%.1fs",
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self.task_id[:8], turn + 1, api_elapsed,
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len(assistant_msg.tool_calls), turn_elapsed,
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)
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else:
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@@ -336,8 +373,10 @@ class HermesAgentLoop:
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msg_dict["reasoning_content"] = reasoning
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messages.append(msg_dict)
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logger.debug(
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"Turn %d: model finished naturally (no tool calls)", turn + 1
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turn_elapsed = _time.monotonic() - turn_start
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logger.info(
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"[%s] turn %d: api=%.1fs, no tools (finished), turn_total=%.1fs",
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self.task_id[:8], turn + 1, api_elapsed, turn_elapsed,
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)
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return AgentResult(
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