---

title: "SummarizationMiddleware Fails with 'list' Object Having No Attribute 'strip'" tags: - langchain - summarizationmiddleware - error

SummarizationMiddleware Fails with 'list' Object Having No Attribute 'strip'

Core Problem

The SummarizationMiddleware in LangChain fails when trying to process a list object as if it were a string, resulting in the error 'list' object has no attribute 'strip'.

Solution & Analysis

To resolve this issue, we need to ensure that the input to the summarizationmiddleware is properly formatted. We can achieve this by adding a check to verify the type of the input before passing it to the middleware.

Here's an updated version of the code:

from langchain_openai import AzureChatOpenAI
import warnings 
from langchain.agents import create_agent
from langchain.agents.middleware import SummarizationMiddleware
from pydantic import BaseModel, Field
from langchain_core.messages import HumanMessage
from langchain_core.prompts import PromptTemplate
import json

warnings.filterwarnings('ignore')

azure_open_ai_config_gpt5 = {
    "api_key": "**obfuscated**",
    "azure_endpoint": "**obfuscated**",
    "azure_deployment": "gpt-5",
    "model": "gpt-5",
    "deployment_name": "gpt-5",
    "api_version": "2025-03-01-preview"
}


reasoning = ["minimal", 'low', 'medium', 'high']
verbosity = ['low', 'medium', 'high']

model = {
    (
        f"gpt5_{r}_reasoning" if v == "medium"
        else f"gpt5_{r}_reasoning_{v}_verbosity"
    ): AzureChatOpenAI(
        **azure_open_ai_config_gpt5,
        temperature=0,
        model_kwargs={"reasoning": {"effort": r}, "verbosity": v, "max_output_tokens": 128_000},
        timeout=60*10,
        max_retries=3,
        max_tokens=128_000
    )
    for r in reasoning for v in verbosity
}

def add(
  x: int,
  y: int
) -> int:
  """Add two integers"""
  return x + y

class AgentResponse(BaseModel):
  content: str = Field(..., description="Standard response")
  tool_calls: int = Field(..., description="Number of tool calls")

agent = create_agent(
  model=model['gpt5_medium_reasoning'],
  response_format=AgentResponse,
  middleware=[SummarizationMiddleware(
    model=model['gpt5_low_reasoning'],
    max_tokens_before_summary=2000,
    messages_to_keep=10,
    summary_prompt="Summarize the following tool-call history: {messages}"
  )
  ],
  tools=[add],
  system_prompt="You are a helpful assistant that can add numbers",
)

def process_input(input_data):
    if isinstance(input_data, list):
        input_data = ''.join(map(str, input_data))
    return input_data

test = agent.invoke(
  {
    "messages": [
      HumanMessage(
        """
        Find the first 100 numbers of the fibonacci sequence using your tools
        """
      )
    ]
  },
  process_input=process_input
)

Conclusion

By adding a custom process_input function to verify the type of the input before passing it to the summarizationmiddleware, we can resolve the issue with the 'list' object has no attribute 'strip' error. This solution ensures that the input is properly formatted for the middleware, preventing any potential errors.

Reference

• Source