DeepAgent from Scratch

Overview

This repository contains a minimal implementation of a DeepAgent inspired by the Deep Agents from Scratch course. The agent can:

1. Search the web using DuckDuckGo.
2. Create virtual files in an in‑memory file system.
3. Persist those virtual files to the real file system when the task is finished.

The implementation uses:

• LangChain OpenAI (ChatOpenAI) for LLM interactions.
• DuckDuckGo Search for web queries.
• A simple VirtualFileSystem class to hold files in memory.

Requirements

langchain-openai>=0.3.0
langchain>=1.2.10
langgraph>=0.2.0
duckduckgo-search

Running the Agent

# Install dependencies
pip install -r requirements.txt

# Run the agent
python main.py

The script will perform a sample search for "LangChain deep agent" and create a file named summary.txt with the first search result. All virtual files are written to the current directory.

Extending the Agent

• Add more tools by decorating functions with @tool and passing them to DeepAgent.
• Modify the run method to change the interaction loop or add more sophisticated prompting.

License

MIT