# Deep Agent Search with Virtual File System

This project demonstrates a simple deep agent search system that operates on **virtual files** stored entirely in memory. It uses **PyTorch**, **scikit-learn**, and **NumPy** to perform TF‑IDF vectorization and cosine similarity ranking.

## Features

- **Virtual File System**: Create, read, write, unload, and delete virtual files.
- **Search Agent**: Rank lines from a virtual file based on a query using TF‑IDF and cosine similarity.
- **Deep Learning Integration**: Uses PyTorch tensors for similarity calculations.
- **Easy to Extend**: Replace the search logic with more sophisticated models (e.g., transformers) without changing the file system.

## Installation

```bash
# Clone the repository
git clone https://git.brojs.ru/kuzakhmetovartur/8.-samopisnyy-poiskovyy-agent-na-osnove-
cd 8.-samopisnyy-poiskovyy-agent-na-osnove-

# Create a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

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

## Usage

Run the example script:

```bash
python src/main.py
```

You should see output similar to:

```
Search results for query: 'neural networks'
1. Neural networks can approximate complex functions.
2. Deep learning has revolutionized many fields.
3. PyTorch provides dynamic computation graphs.
After unload: Cannot read from unloaded file 'sample.txt'.
```

## Project Structure

```
├── src
│   ├── main.py                # Entry point and demo
│   └── virtual_file_system.py # Virtual file system implementation
├── requirements.txt           # Dependencies
└── README.md                  # Documentation
```

## Extending the Search Agent

The `SearchAgent` class in `src/main.py` can be replaced with any model that accepts a query and returns ranked results. For example, you could:

- Load a pre‑trained transformer (e.g., BERT) and compute embeddings.
- Use a neural ranking model trained on relevance data.
- Integrate with external search APIs.

Just ensure that the agent receives a `VirtualFileSystem` instance and uses `VirtualFile.read()` to access data.

## Testing

Unit tests are not included in this minimal example, but you can add tests using `pytest` to verify:

- Virtual file read/write/unload behavior.
- Search agent ranking correctness.
- Integration of the virtual file system with the agent.

## License

MIT License
```