Why am I encountering a '>=' type mismatch error in LangChain's Agent during ML job search?

I'm developing a Python script that uses LangChain and OpenAI to search for machine learning job listings based on my CV. However, I run into the following error during the ML job search step:

Error searching for jobs: '>=' not supported between instances of 'int' and 'str'

PYTHONCopied
from langchain_openai import ChatOpenAI
from browser_use import Agent
import asyncio
from dotenv import load_dotenv
import json
import PyPDF2

# Load environment variables (e.g., OpenAI API key)
load_dotenv()

# Function to read a PDF CV
def read_pdf_cv(file_path):
    try:
        with open(file_path, "rb") as file:
            reader = PyPDF2.PdfReader(file)
            text = ""
            for page in reader.pages:
                page_text = page.extract_text()
                if page_text:  # Check if text extraction was successful
                    text += page_text
            return text
    except Exception as e:
        print(f"Error reading PDF: {e}")
        return ""

async def main():
    # Step 1: Read the CV
    cv_path = "my_cv.pdf"  # Replace with your CV file path
    cv_content = read_pdf_cv(cv_path)

    if not cv_content:
        print("No content extracted from CV. Exiting.")
        return

    print("CV Content Extracted:", cv_content)

    # Initialize the Agent
    agent = Agent(
        task=f"Read my CV and extract relevant information for ML job applications. CV content: {cv_content}",
        llm=ChatOpenAI(model="gpt-4"),
    )

    # Step 2: Search for ML jobs
    try:
        ml_jobs = await agent.run("Search for machine learning jobs based on the CV information.")
        print("Raw ML Jobs Data:", ml_jobs)

        # Ensure all job entries are dictionaries with consistent fields
        if isinstance(ml_jobs, list):
            for job in ml_jobs:
                if isinstance(job, dict):
                    # Normalize 'salary' field
                    if 'salary' in job:
                        try:
                            job['salary'] = int(job['salary'])  # Convert salary to int
                        except (ValueError, TypeError):
                            print(f"Invalid salary value for job: {job['salary']}. Setting to 0.")
                            job['salary'] = 0
                else:
                    print(f"Warning: Job entry is not a dictionary: {job}")
        else:
            print(f"Error: Expected 'ml_jobs' to be a list, but got {type(ml_jobs)}")
            return

    except Exception as e:
        print(f"Error searching for jobs: {e}")
        return

    # Step 3: Save the ML jobs to a file
    try:
        with open("ml_jobs.json", "w") as file:
            json.dump(ml_jobs, file, indent=4)
        print("ML jobs saved to 'ml_jobs.json'.")
    except Exception as e:
        print(f"Error saving jobs to JSON: {e}")

    # Step 4: Start applying for the jobs in new tabs
    for job in ml_jobs:
        try:
            apply_result = await agent.run(f"Apply for the ML job: {job}. If you need help, ask me.")
            print(f"Application Result for {job}:", apply_result)
        except Exception as e:
            print(f"Error applying for job {job}: {e}")

# Run the main function
if __name__ == "__main__":
    asyncio.run(main())

Detailed Error Information
The traceback points to an internal comparison in the Agent’s run loop where a counter (likely an integer) is being compared with a max_steps value that is unexpectedly a string. Notably, the error appears in the following snippet from the traceback:

BASHCopied
Traceback (most recent call last):
  File "C:\Users\LENOVO\anaconda3\Lib\site-packages\browser_use\agent\service.py", line 468, in run
    for step in range(max_steps):
                ^^^^^^^^^^^^^^^^
TypeError: 'str' object cannot be interpreted 
as an integer

...
max_steps_reached=self.n_steps >= max_steps,
                      ^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: '>=' not supported between instances of 'int' and 'str'

What I've Tried

• I inspected the ml_jobs output and normalized numeric fields like 'salary' to integers.
• I verified that ml_jobs is a list of dictionaries before processing each job.
• I suspect that an environment variable or default parameter (e.g., max_steps) might be causing the mismatch internally within the Agent.

Questions

1. Why might the Agent or ChatOpenAI be using the >= operator with a string value for max_steps?
2. Are there known issues with the Agent's internal handling of configuration values? How should I resolve this type mismatch?
3. What additional debugging steps could help isolate the source of the problem?

Any guidance or suggestions would be greatly appreciated!