task-6a1d75d1fd30e81cf3126af8/README.md

Self-Reflective LangGraph Agent

Overview

This repository contains a minimal example of a LangGraph agent that writes a short answer to a question, then uses a critic node to evaluate the answer.
If the critic flags the answer as needs_revision, a rewrite node improves the text.
The process repeats until the answer is accepted or the maximum number of rounds is reached.

The agent is built on top of deepagents and uses OpenRouter via langchain_openai.

How to Run

1. Clone the repository

   git clone https://github.com/yourname/self_reflective_agent.git
   cd self_reflective_agent
   

2. Create a virtual environment

   python -m venv .venv
   source .venv/bin/activate   # On Windows use .venv\\Scripts\\activate
   

3. Install dependencies

   pip install -r requirements.txt
   

4. Set your OpenRouter API key

   export OPENAI_API_KEY=sk-or-...
   

5. Run the demo

   python main.py
   

   You should see the final answer printed to the console.

Project Structure

• main.py - Main script that defines the graph, the DeepAgent, and runs the demo.
• requirements.txt - Python dependencies.
• README.md - This file.

Notes

• The agent uses a fixed temperature of 0.0 for deterministic responses.
• The maximum number of rewrite rounds is set to 2 by default.
• All code uses only ASCII punctuation as required by the assignment.