task-6a1864fa8a94f887e50d46f0/README.md

Self‑Correcting LangGraph Agent

This repository contains a minimal implementation of a self‑correcting agent using LangGraph. The agent:

1. Executes a user‑supplied task via an unreliable tool that may fail.
2. Uses an LLM judge to verify the result (must answer success or failed).
3. Retries until the result is judged success or a maximum number of attempts is reached.

The implementation follows the specification from the course assignment.

Requirements

The project uses the following packages (all versions are >= 1.0.0):

• langchain>=1.0.0
• langgraph>=1.0.0
• langchain-openai>=0.2.0

Install them via:

pip install -r requirements.txt

Usage

# Run the agent for a simple arithmetic task
python agent.py "2+2"

You can also specify the maximum number of attempts:

python agent.py "2+2" --max_attempts 5

The output will show the number of attempts and the final status.

How it works

• unreliable_tool – a function that evaluates the task string with a 30 % chance of raising a ValueError.
• execute_task – calls the tool and stores the result or error.
• verify_result – asks the LLM to judge the result. The LLM must reply with either success or failed.
• handle_error – increments the attempt counter and resets the state for a retry.
• Graph – a LangGraph StateGraph that loops between these nodes until success or the attempt limit is reached.

Extending

Replace unreliable_tool with any external API or function. Adjust the LLM prompt in verify_result to fit your domain.