Deep Agent based on LangGraph & LangChain
This repository contains a minimal implementation of a Deep Agent that can:
- Search the web using the Tavily search API.
- Create virtual files in an in‑memory file system.
- 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
# 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
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:
python -m unittest discover -s tests
License
MIT