Update README.md

README.md

@@ -1,61 +1,50 @@
 # Self‑Correcting LangGraph Agent
 
-## Overview
+This repository contains a minimal implementation of a **self‑correcting agent** using LangGraph.  The agent:
 
-This project implements a **self‑correcting agent** using LangGraph. The agent
-performs a task, asks an LLM to judge the result, and retries automatically until
-the result is judged **success** or the maximum number of attempts is reached.
+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 key components are:
+The implementation follows the specification from the course assignment.
 
-| Component | Purpose |
-|-----------|---------|
-| `AgentState` | Typed state that tracks the task, result, attempts, status, error and max_attempts |
-| `unreliable_tool` | Simulates a tool that fails 30 % of the time (used to demonstrate retry logic) |
-| `verify_result` | LLM judge that must reply with the single word `success` or `failed` |
-| `handle_error` | Resets the error and sets the status back to `pending` for a retry |
-| `execute_task` | Runs the unreliable tool and updates the state |
-| `create_agent` | Builds the LangGraph with the above nodes and a retry loop |
-| `create_agent_executor` | Compiles the graph into a runnable executor |
-| CLI | Run the agent from the command line: `python agent.py "2+2" --max 5` |
+## Requirements
 
-## How It Works
+The project uses the following packages (all versions are >= 1.0.0):
 
-1. **Start** – The graph begins at `execute_task`.
-2. **Execute** – The tool runs. If it throws an exception, the state status becomes `failed`.
-3. **Check attempts** – If the number of attempts is >= `max_attempts`, the graph ends with status `max_attempts`.
-4. **Verify** – The LLM judges the result. If the verdict is `success`, the graph ends. If `failed`, it goes to `handle_error`.
-5. **Retry** – `handle_error` clears the error and sets status to `pending`, then the graph loops back to `execute_task`.
+* `langchain>=1.0.0`
+* `langgraph>=1.0.0`
+* `langchain-openai>=0.2.0`
+
+Install them via:
+
+```bash
+pip install -r requirements.txt
+```
 
 ## Usage
 
 ```bash
-# Install dependencies
-pip install -r requirements.txt
-
-# Run the agent
-python agent.py "2+2" --max 5
+# Run the agent for a simple arithmetic task
+python agent.py "2+2"
 ```
 
-The console will show the final state, e.g.:
+You can also specify the maximum number of attempts:
 
-```
---- Final State ---
-result: 4
-attempts: 2
-status: success
-error: None
-max_attempts: 5
-``` 
-
-## Requirements
-
-```text
-langchain>=1.0.0
-langgraph>=1.0.0
-langchain-openai>=1.0.0
+```bash
+python agent.py "2+2" --max_attempts 5
 ```
 
-## Note
+The output will show the number of attempts and the final status.
 
-The agent uses the OpenAI API. Make sure the environment variable `OPENAI_API_KEY` is set.
+## 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.