# LangGraph Reflection Demo

This project demonstrates a simple LangGraph agent that:
1. Generates a short answer (5–10 sentences) to a user‑supplied question.
2. Critiques the answer for completeness, concreteness, and fluff.
3. If the critique indicates `needs_revision`, rewrites the answer up to a maximum number of rounds.

## Features

- **Separate nodes** for drafting, reflecting, and rewriting.
- **LLM‑based critic** that returns a verdict (`ok` or `needs_revision`) and 2–3 critique points.
- **Controlled loop**: rewrites only if the verdict is `needs_revision` and the round count is below `max_rounds`.
- **CLI interface**: pass a question via `-q` or input interactively.
- **Configurable maximum rounds** via `-m` (default 2).

## Requirements

- Python 3.10+
- `langgraph`
- `langchain-openai`

Install dependencies:

```bash
pip install -r requirements.txt
```

## Usage

1. **Set your OpenAI API key**:

```bash
export OPENAI_API_KEY="your_api_key_here"
```

2. **Run the demo**:

```bash
python src/main.py -q "Explain the difference between a tool and a resource in MCP."
```

Or simply:

```bash
python src/main.py
```

and enter the question when prompted.

The script will output the final answer, the number of rounds performed, the verdict, and the critique points.

## Project Structure

```
src/
├── main.py      # CLI entry point
├── graph.py     # LangGraph definition
└── nodes.py     # Node implementations
requirements.txt
README.md
```

## License

MIT License