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Xuve is a command-line tool that allows you to search for movies based on a keyword query. It utilizes a Retrieval-Augmented Generation (RAG) system to provide relevant results from a dataset of movies.

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Xuve

A RAG system for searching and retrieving information from movies data.

Description

Xuve is a command-line tool that allows you to search for movies based on a keyword query. It utilizes a Retrieval-Augmented Generation (RAG) system to provide relevant results from a dataset of movies.

Features

  • Keyword-based search for movies.
  • Command-line interface for easy interaction.
  • Built with Python and the NLTK library.

Installation

  1. Clone the repository:

    git clone https://github.com/xonoxc/xuve.git
    cd xuve
  2. Create and activate a virtual environment:

    This project recommends using uv to manage the virtual environment.

    uv venv
    source .venv/bin/activate

    Alternatively, you can use Python's built-in venv module:

    python3 -m venv .venv
    source .venv/bin/activate
  3. Install dependencies:

    This project uses uv for package management. If you don't have it, install it first (pip install uv).

    uv sync

Usage

To search for movies, use the search command followed by your query:

python -m cli.main search "your query here"

Example

python -m cli.main search "a movie about a spy"

Project Structure

.
├── cli/                # Command-line interface logic
├── config/             # Configuration files
├── data/               # Data files
├── decors/             # Decorators
├── lib/                # Core application logic
│   ├── indexes/
├── typedicts/          # Type definitions
├── .gitignore
├── .python-version
├── pyproject.toml
├── pyrightconfig.json
├── README.md
└── uv.lock

Dependencies

  • nltk: The Natural Language Toolkit, used for processing text data.

License

This project is licensed under the MIT License. See the LICENSE file for details.

About

Xuve is a command-line tool that allows you to search for movies based on a keyword query. It utilizes a Retrieval-Augmented Generation (RAG) system to provide relevant results from a dataset of movies.

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