Agent with RAG Memory

This project demonstrates a simple RAG (Retrieval-Augmented Generation) agent that uses LangChain tools to perform basic operations via an interactive command line interface (CLI).

Features

Add Numbers – Add two integers using the add_numbers tool.
Search Items – Search a predefined list of strings for a query using the search_item tool.
Interactive CLI – Use /add, /search, and /quit commands to interact with the agent.

Installation

# Clone the repository
git clone https://git.brojs.ru/kuzakhmetovartur/agent-s-rag-pamyatyu.git
cd agent-s-rag-pamyatyu

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

# Install dependencies
pip install -r requirements.txt

Usage

Run the CLI:

python -m src.main

You will see a prompt:

Welcome to the RAG Agent CLI!
Available commands:
  /add <int> <int>   - Add two numbers.
  /search <query>   - Search items in memory.
  /quit             - Exit the program.

Commands

/add
Add two integers.
```
>> /add 5 7
Result: 12
```

/search
Search the internal memory for a query string.

>> /search python
Matches found:
  1. Python programming

/quit
Exit the program.
```
>> /quit
Goodbye!
```

Project Structure

agent-s-rag-pamyatyu/
├── src/
│   ├── __init__.py
│   ├── cli.py
│   ├── main.py
│   └── tools.py
├── README.md
├── requirements.txt
└── pyproject.toml

Dependencies

langchain – The core library for building language model agents.
python-dotenv – (Optional) For loading environment variables if needed.

License

MIT License

Feel free to extend the tools or the CLI to suit your needs!

1.9 KiB Raw Blame History Unescape Escape