# Copyright (c) Meta Platforms, Inc. and affiliates
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.

from pathlib import Path
from typing import Iterable

import pkg_resources
from setuptools import find_packages, setup


def _load_requirements(fname: str) -> Iterable[str]:
    with open(Path(__file__).parent / fname) as fp_in:
        for req in pkg_resources.parse_requirements(fp_in):
            yield str(req)


default_requirements = list(_load_requirements("requirements.txt"))
dev_requirements = list(_load_requirements("dev_requirements.txt"))

setup(
    name="seamless_communication",
    version="1.0.0",
    packages=find_packages(where="src") + ['m4t_scripts.finetune', 'm4t_scripts.predict'],
    package_dir={"m4t_scripts": "scripts/m4t", "seamless_communication": "src/seamless_communication"},
    package_data={"": ["seamless_communication/assets/cards/*.yaml"]},
    description="SeamlessM4T -- Massively Multilingual & Multimodal Machine Translation Model",
    long_description=open("README.md", encoding="utf-8").read(),
    long_description_content_type="text/markdown",
    readme="README.md",
    python_requires=">=3.8",
    author="Fundamental AI Research (FAIR) at Meta",
    url="https://github.com/facebookresearch/seamless_communication",
    license="Creative Commons",
    install_requires=default_requirements,
    extras_require={"dev": default_requirements + dev_requirements},
    entry_points={
        "console_scripts": [
           "m4t_predict=m4t_scripts.predict.predict:main",
           "m4t_finetune=m4t_scripts.finetune.finetune:main",
           "m4t_prepare_dataset=m4t_scripts.finetune.dataset:main",
        ],
    },
    include_package_data=True,
)