"""
Upload UD dataset to HuggingFace Hub.
Dataset: undertheseanlp/UDD-v0.1

Usage:
    export $(cat .env | xargs) && python upload_to_hf.py
"""

import json
import os
from os.path import expanduser, join

from datasets import Dataset, DatasetDict
from huggingface_hub import HfApi, login


def load_jsonl(filepath):
    """Load JSONL file."""
    data = []
    with open(filepath, "r", encoding="utf-8") as f:
        for line in f:
            data.append(json.loads(line))
    return data


def main():
    # Login with token from environment
    token = os.environ.get("HF_TOKEN")
    if token:
        print("Logging in with HF_TOKEN...")
        login(token=token)
    else:
        print("Warning: HF_TOKEN not set. Using cached credentials.")

    source_folder = expanduser("~/Downloads/UD_Vietnamese-UUD-v0.1")
    jsonl_file = join(source_folder, "train.jsonl")
    readme_file = join(source_folder, "README.md")

    print("Loading data...")
    data = load_jsonl(jsonl_file)
    print(f"Loaded {len(data)} sentences")

    # Create HuggingFace Dataset
    print("Creating HuggingFace Dataset...")
    dataset = Dataset.from_list(data)

    # Create DatasetDict with train split
    dataset_dict = DatasetDict({
        "train": dataset
    })

    print(f"Dataset: {dataset_dict}")
    print(f"Features: {dataset.features}")

    # Push to HuggingFace Hub
    repo_id = "undertheseanlp/UDD-v0.1"
    print(f"\nPushing to HuggingFace Hub: {repo_id}")

    dataset_dict.push_to_hub(
        repo_id,
        private=False,
        commit_message="Update: 1000 sentences from Vietnamese Legal Corpus"
    )

    # Upload README.md
    print("Uploading README.md...")
    api = HfApi()
    api.upload_file(
        path_or_fileobj=readme_file,
        path_in_repo="README.md",
        repo_id=repo_id,
        repo_type="dataset",
        commit_message="Add README with dataset card"
    )

    print(f"\nDone! Dataset available at: https://huggingface.co/datasets/{repo_id}")


if __name__ == "__main__":
    main()