TGS (Terminal Generative Shell)

TGS is a conversational shell that combines the power of Rust with the intelligence of GPT-based natural language processing. Designed as a spinoff of the TerminalGPT project, TGS aims to redefine the way users interact with their terminals.

Features

Conversational Interface: Interact with your terminal in natural language. Instead of remembering complex commands, just tell TGS what you want to do.
Rust Integration: Built with the robustness and efficiency of Rust, ensuring a fast and reliable terminal experience.
Intelligent Suggestions: TGS provides smart suggestions and corrections, making your terminal experience smoother and more intuitive.
Safety Measures: TGS has built-in safety checks to prevent accidental execution of potentially harmful commands.

Installation

# Placeholder for installation commands
git clone <repository_link>
cd tgs
./install.sh

Usage

Start TGS with the following command:

tgs

Once inside TGS, you can start conversing with your terminal:

tgs> Create a new directory called "projects"
Directory "projects" created.

tgs> List all files in the current directory
...output...

Testing

To run the unit tests for TGS:

cargo test

Contributing

We welcome contributions! Please see our CONTRIBUTING.md for guidelines.

Working with the probject

This library relies on the tch crate for bindings to the C++ Libtorch API. The libtorch library is required can be downloaded either automatically or manually. The following provides a reference on how to set-up your environment to use these bindings, please refer to the tch for detailed information or support.

Furthermore, this library relies on a cache folder for downloading pre-trained models. This cache location defaults to ~/.cache/.rustbert, but can be changed by setting the RUSTBERT_CACHE environment variable. Note that the language models used by this library are in the order of the 100s of MBs to GBs.

Manual installation (recommended)

Download libtorch from https://pytorch.org/get-started/locally/. This package requires v2.1: if this version is no longer available on the "get started" page, the file should be accessible by modifying the target link, for example https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.1.1%2Bcu118.zip for a Linux version with CUDA11. NOTE: When using rust-bert as dependency from crates.io, please check the required LIBTORCH on the published package readme as it may differ from the version documented here (applying to the current repository version).
Extract the library to a location of your choice
Set the following environment variables

Convert weights to .ot

python ./utils/convert_model.py model/pytorch_model.bin

Linux:

export LIBTORCH=/path/to/libtorch
export LD_LIBRARY_PATH=${LIBTORCH}/lib:$LD_LIBRARY_PATH

Windows

$Env:LIBTORCH = "X:\path\to\libtorch"
$Env:Path += ";X:\path\to\libtorch\lib"

macOS + Homebrew

brew install pytorch jq
export LIBTORCH=$(brew --cellar pytorch)/$(brew info --json pytorch | jq -r '.[0].installed[0].version')
export LD_LIBRARY_PATH=${LIBTORCH}/lib:$LD_LIBRARY_PATH

Automatic installation

Alternatively, you can let the build script automatically download the libtorch library for you. The download-libtorch feature flag needs to be enabled. The CPU version of libtorch will be downloaded by default. To download a CUDA version, please set the environment variable TORCH_CUDA_VERSION to cu118. Note that the libtorch library is large (order of several GBs for the CUDA-enabled version) and the first build may therefore take several minutes to complete.

Verifying installation

Verify your installation (and linking with libtorch) by adding the rust-bert dependency to your Cargo.toml or by cloning the rust-bert source and running an example:

git clone git@github.com:guillaume-be/rust-bert.git
cd rust-bert
cargo run --example sentence_embeddings

License

TGS is licensed under the MIT License.

Research references

Feel free to customize the README further to match the specific features, installation steps, and other details of your project. Remember to replace placeholders (like <repository_link>, path_to_logo.png, etc.) with actual links or paths as needed.

Citations

@inproceedings{becquin-2020-end,
    title = "End-to-end {NLP} Pipelines in Rust",
    author = "Becquin, Guillaume",
    booktitle = "Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS)",
    year = "2020",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.nlposs-1.4",
    pages = "20--25",
}

Troubleshooting

For Mac.

In case of running into torch-sys error refer to this solution

NiallJoeMaher / tgs