# 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:

1. **Search the web** for information using DuckDuckGo.
2. **Create virtual files** during its execution.
3. **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
```bash
# 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
```bash
# 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.