Deep Agent with Web Search and Virtual File Creation

Overview

This repository contains a minimal implementation of a Deep Agent built from scratch using the deepagents framework. The agent can:

Search the web for information using DuckDuckGo.
Create virtual files during its execution.
Export those virtual files to the real filesystem after the agent finishes.

The implementation follows the guidelines from the Deep Agents from Scratch course and uses the BroJS LLM endpoint.

Prerequisites

Python 3.10 or newer
A valid BroJS API key set in the environment variable JOURNAL_MCP_PAT.
(Optional) A virtual environment to isolate dependencies.

Installation

# Clone the repository
git clone https://git.brojs.ru/KirillKutlakhmetov/task-69de7223f309a98be0007e09.git
cd task-69de7223f309a98be0007e09

# Create and activate a virtual environment (recommended)
python -m venv .venv
source .venv/bin/activate  # On Windows use .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Usage

# Ensure the environment variable is set
export JOURNAL_MCP_PAT=your_brojs_api_key

# Run the agent
python main.py

The agent will perform a sample query ("Python async programming"). After completion, the virtual files created during the run will be exported to the ./exported_files directory.

Project Structure

main.py – Entry point and agent definition.
requirements.txt – Python dependencies.
README.md – Project documentation.

Customization

To change the query, modify the user_query variable in main.py.
To add more tools, define additional functions decorated with @tool and include them in the tools list when creating the agent.
The agent can be extended to accept user input at runtime by replacing the hard‑coded query.

License

MIT License.

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