# Deep Agent based on LangGraph & LangChain

This repository contains a minimal implementation of a **Deep Agent** that can:

1. Search the web using the Tavily search API.
2. Create virtual files in an in‑memory file system.
3. Export all virtual files to the real filesystem.

The agent is built on top of the *LangGraph* framework and uses the *LangChain* tools API.

## Installation

```bash
# Create a virtual environment (recommended)
python -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt
```

> **Note**: The Tavily API key is required for the web search tool. Set it via the
> environment variable `TAVILY_API_KEY`.

## Usage

```python
from agent import create_agent_executor, vfs

# Create an executor
executor = create_agent_executor()

# Run the agent with a simple prompt
result = executor.invoke({"input": "Find the latest news about Python and create a file called news.txt with the summary."})
print(result)

# After the agent finishes, export the virtual files
vfs.export_to_disk("output")
```

The `output` directory will contain `news.txt` with the content produced by the agent.

## Testing

The project includes a simple test that verifies the existence of the two
required functions:

```bash
python -m unittest discover -s tests
```

## License

MIT