# LangGraph Agent with OpenAI Integration

This project demonstrates a simple LangGraph agent that integrates with the OpenAI LLM via the `langchain-openai` package. The agent processes a single prompt and returns the model's response.

## Requirements

- Python 3.10+
- `langchain-openai` (automatically installed via `requirements.txt`)
- `langgraph`
- `langchain`
- `openai`

Install the dependencies:

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

## Configuration

Set your OpenAI API key as an environment variable:

```bash
export OPENAI_API_KEY="your-openai-api-key"
```

Alternatively, you can create a `.env` file in the project root with the following content:

```
OPENAI_API_KEY=your-openai-api-key
```

## Running the Agent

You can run the agent from the command line:

```bash
python -m src.agent "Hello, how are you?"
```

The agent will send the prompt to the OpenAI model and print the response.

## Project Structure

```
├── requirements.txt
├── src
│   └── agent.py
└── README.md
```

- `requirements.txt` – lists all Python package dependencies.
- `src/agent.py` – contains the LangGraph agent implementation and a simple CLI.
- `README.md` – this documentation file.

## Extending the Agent

The current graph contains a single node that calls the LLM. You can extend it by adding more nodes (e.g., for tool usage, memory, or custom logic) and connecting them in the graph.

Happy coding!