Problem Summary

ToolTimeoutMiddleware for LangGraph-backed agents to prevent system crashes due to unresponsive API calls.

Root Cause Analysis

The root cause is the lack of a timeout mechanism to prevent the orchestration layer from freezing when a tool exceeds the threshold.

Fix Plan

Step 1: Install the required package

pip install langchain

Step 2: Create a ToolTimeoutMiddleware class

import asyncio
from langchain import ToolTimeoutMiddleware

class ToolTimeoutMiddleware:
    def __init__(self, threshold):
        self.threshold = threshold

    async def __call__(self, tool):
        try:
            result = await asyncio.wait_for(tool(), timeout=self.threshold)
            return result
        except asyncio.TimeoutError:
            return ToolMessage(status="error")

Step 3: Use the ToolTimeoutMiddleware in your LangGraph-backed agent

from langchain import LangGraph

class MyAgent:
    def __init__(self):
        self.lang_graph = LangGraph()
        self.middleware = ToolTimeoutMiddleware(threshold=30)  # 30 seconds

    async def run(self):
        tool = self.lang_graph.get_tool()
        result = await self.middleware(tool)
        return result

Verification

1. Set up a test environment with a LangGraph-backed agent.
2. Simulate a tool that exceeds the threshold.
3. Verify that the middleware intercepts the tool and returns a ToolMessage with status="error".

Extra Tips

• Adjust the threshold value based on your specific use case.
• Consider implementing a more sophisticated timeout mechanism, such as exponential backoff.
• Make sure to test the middleware thoroughly to ensure it works as expected.