CAMeL Tools is suite of Arabic natural language processing tools developed by the CAMeL Lab at New York University Abu Dhabi.
Please use GitHub Issues to report a bug or if you need help using CAMeL Tools.
You will need Python 3.8 - 3.12 (64-bit) as well as the Rust compiler installed.
You will need to install some additional dependencies on Linux and macOS. Primarily CMake, and Boost.
On Ubuntu/Debian you can install these dependencies by running:
sudo apt-get install cmake libboost-all-dev
On macOS you can install them using Homewbrew by running:
brew install cmake boost
pip install camel-tools
# or run the following if you already have camel_tools installed
pip install camel-tools --upgrade
On Apple silicon Macs you may have to run the following instead:
CMAKE_OSX_ARCHITECTURES=arm64 pip install camel-tools
# or run the following if you already have camel_tools installed
CMAKE_OSX_ARCHITECTURES=arm64 pip install camel-tools --upgrade
# Clone the repo
git clone https://github.com/CAMeL-Lab/camel_tools.git
cd camel_tools
# Install from source
pip install .
# or run the following if you already have camel_tools installed
pip install --upgrade .
To install the datasets required by CAMeL Tools components run one of the following:
# To install all datasets
camel_data -i all
# or just the datasets for morphology and MLE disambiguation only
camel_data -i light
# or just the default datasets for each component
camel_data -i defaults
See Available Packages for a list of all available datasets.
By default, data is stored in ~/.camel_tools
.
Alternatively, if you would like to install the data in a different location,
you need to set the CAMELTOOLS_DATA
environment variable to the desired
path.
Add the following to your .bashrc
, .zshrc
, .profile
,
etc:
export CAMELTOOLS_DATA=/path/to/camel_tools_data
Note: CAMeL Tools has been tested on Windows 10. The Dialect Identification component is not available on Windows at this time.
pip install camel-tools -f https://download.pytorch.org/whl/torch_stable.html
# or run the following if you already have camel_tools installed
pip install --upgrade -f https://download.pytorch.org/whl/torch_stable.html camel-tools
# Clone the repo
git clone https://github.com/CAMeL-Lab/camel_tools.git
cd camel_tools
# Install from source
pip install -f https://download.pytorch.org/whl/torch_stable.html .
pip install --upgrade -f https://download.pytorch.org/whl/torch_stable.html .
To install the data packages required by CAMeL Tools components, run one of the following commands:
# To install all datasets
camel_data -i all
# or just the datasets for morphology and MLE disambiguation only
camel_data -i light
# or just the default datasets for each component
camel_data -i defaults
See Available Packages for a list of all available datasets.
By default, data is stored in
C:Usersyour_user_nameAppDataRoamingcamel_tools
.
Alternatively, if you would like to install the data in a different location,
you need to set the CAMELTOOLS_DATA
environment variable to the desired
path. Below are the instructions to do so (on Windows 10):
env
.CAMELTOOLS_DATA
in the Variable name input box and the
desired data path in Variable value. Alternatively, you can browse for the
data directory by clicking on the Browse Directory... button.To get started, you can follow along the Guided Tour for a quick overview of the components provided by CAMeL Tools.
You can find the full online documentation here for both the command-line tools and the Python API.
Alternatively, you can build your own local copy of the documentation as follows:
# Install dependencies
pip install sphinx myst-parser sphinx-rtd-theme
# Go to docs subdirectory
cd docs
# Build HTML docs
make html
This should compile all the HTML documentation in to docs/build/html
.
If you find CAMeL Tools useful in your research, please cite our paper:
@inproceedings{obeid-etal-2020-camel,
title = "{CAM}e{L} Tools: An Open Source Python Toolkit for {A}rabic Natural Language Processing",
author = "Obeid, Ossama and
Zalmout, Nasser and
Khalifa, Salam and
Taji, Dima and
Oudah, Mai and
Alhafni, Bashar and
Inoue, Go and
Eryani, Fadhl and
Erdmann, Alexander and
Habash, Nizar",
booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://www.aclweb.org/anthology/2020.lrec-1.868",
pages = "7022--7032",
abstract = "We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python. CAMeL Tools currently provides utilities for pre-processing, morphological modeling, Dialect Identification, Named Entity Recognition and Sentiment Analysis. In this paper, we describe the design of CAMeL Tools and the functionalities it provides.",
language = "English",
ISBN = "979-10-95546-34-4",
}
CAMeL Tools is available under the MIT license. See the LICENSE file for more info.
If you would like to contribute to CAMeL Tools, please read the CONTRIBUTE.rst file.