app.py

import contextlib
import re
import tempfile
from functools import lru_cache

import gradio as gr
from git import Repo
from httpx import Client
from typing import Optional
from huggingface_hub import create_repo, upload_folder
from toolz import groupby

client = Client()


def clone_into_temp_dir(github_repo_url):
    temp_dir = tempfile.TemporaryDirectory()
    return Repo.clone_from(github_repo_url, temp_dir), temp_dir


# repo = clone_into_temp_dir("https://github.com/chen-zichen/XplainLLM_dataset/")

# clone_into_temp_dir("https://github.com/chen-zichen/XplainLLM_dataset/")


def upload_directory_to_hf(
    repo_id: str,
    directory: str,
    oauth_token: str,
):
    private = False
    url = create_repo(
        repo_id,
        token=oauth_token,
        exist_ok=True,
        repo_type="dataset",
        private=private,
    )

    commit_url = upload_folder(
        repo_id=repo_id,
        folder_path=directory,
        path_in_repo="data",
        repo_type="dataset",
        token=oauth_token,
        commit_message="Migrated from GitHub",
        ignore_patterns=[
            "*.git*",
            "*README.md*",
            "*.DS_Store",
            "*.env",
        ],  # ignore git files, README, and .env files
    )


def push_to_hf(
    source_github_repository,
    destination_hf_hub_repository,
    subdirectory,
    oauth_token: gr.OAuthToken,
):
    gr.Info("Cloning source GitHub repository...")
    repo, temporary_directory = clone_into_temp_dir(source_github_repository)
    gr.Info("Cloning source GitHub repository...Done")
    gr.Info("Syncing with Hugging Face Hub...")
    if subdirectory:
        src_directory = f"{repo.working_dir}/{subdirectory[0]}"
    else:
        src_directory = repo.working_dir
    upload_directory_to_hf(
        repo_id=destination_hf_hub_repository,
        directory=src_directory,
        oauth_token=oauth_token.token,
    )
    gr.Info("Syncing with Hugging Face Hub...Done")
    temporary_directory.cleanup()
    return f"Pushed the dataset to [{destination_hf_hub_repository}](https://huggingface.co/datasets/{destination_hf_hub_repository})"


def extract_user_name_and_repo_from_url(github_url: str):
    pattern = r"https://github.com/([^/]+)/([^/]+)"
    if match := re.search(pattern, github_url):
        return match[1], match[2]
    print("No match found in the GitHub URL.")
    return None


def get_files_and_directories(response):
    data = response.json()
    grouped_by_type = groupby(lambda item: item["type"], data["tree"])
    files = grouped_by_type.get("blob", [])
    directories = grouped_by_type.get("tree", [])
    if files:
        files = [file["path"] for file in files]
    if directories:
        directories = [directory["path"] for directory in directories]
    return {"files": files, "directories": directories}


@lru_cache(maxsize=128)
def list_git_repo_files_and_directories(repo_url: str, branch: str = "main"):
    user_name_and_repo = extract_user_name_and_repo_from_url(repo_url)
    if user_name_and_repo is None:
        return None
    user_name, repo_name = user_name_and_repo
    url = f"https://api.github.com/repos/{user_name}/{repo_name}/git/trees/{branch}"
    response = client.get(url)
    if response.status_code == 200:
        return get_files_and_directories(response)


def show_files_and_directories(url: str):
    with contextlib.suppress(Exception):
        files_and_directories = list_git_repo_files_and_directories(url)
        directories = files_and_directories.get("directories", [])
        files = files_and_directories.get("files", [])
        print(directories)
        return gr.Dropdown(
            label="Directories",
            choices=directories,
            max_choices=1,
            visible=True,
            interactive=True,
            multiselect=True,
        ), gr.Dropdown(
            label="Files",
            choices=files,
            max_choices=None,
            visible=True,
            interactive=True,
            multiselect=True,
        )


html_text_app_description = """
Whilst GitHub is great for hosting code the Hugging Face Datasets Hub is a better place to host datasets. 
Some of the benefits of hosting datasets on the Hugging Face Datasets Hub are:
<br>
<ul>
<li>Hosting for large datasets</li>
<li>An interactive preview of your dataset</li>
<li>Access to the dataset via many tools and libraries including; datasets, pandas, polars, dask and DuckDB</li>
</ul>

<br>
This app will help you migrate a dataset currently hosted on GitHub to the Hugging Face Datasets Hub.
"""

with gr.Blocks(theme=gr.themes.Base()) as demo:
    gr.HTML(
        """<h1 style='text-align: center;'> GitHub to Hugging Face Hub Dataset Migration Tool</h1>
        <center><i> &#x2728; Migrate a dataset in a few steps &#x2728;</i></center>"""
    )
    gr.HTML(
        """<center> GitHub is a great place for sharing code but the Hugging Face Hub has many advantages for sharing datasets. 
        <br> This Space will guide you through the process of migrating a dataset from GitHub to the Hugging Face Hub. </center>"""
    )
    with gr.Row():
        gr.LoginButton(size="sm")
        gr.LogoutButton(size="sm")
    gr.Markdown("### Location of existing dataset")
    gr.Markdown("URL for the GitHub repository where the dataset is currently hosted")
    source_github_repository = gr.Textbox(lines=1, label="Source GitHub Repository URL")
    gr.Markdown(
        "Use advanced options to select specific files and folders to migrate. Currently this app supports migrating specific subfolder(s) or top level files. If this is not sufficient for your use case please open a discussion!"
    )
    with gr.Accordion("Advanced Options", open=False):
        gr.Markdown("### Select files and folder to migrate")
        gr.Markdown(
            "(Optional): select a specific folder and/or files to migrate from the GitHub repository. If you select a folder all the files in that folder will be migrated."
        )
        folder_in_github_repo = gr.Dropdown(
            None,
            label="Folder in the GitHub Repository to migrate",
            allow_custom_value=True,
            visible=True,
        )
        files_in_github_repo = gr.Dropdown(
            None,
            label="Files in GitHub Repository to migrate",
            allow_custom_value=True,
            visible=True,
        )
        source_github_repository.change(
            show_files_and_directories,
            [source_github_repository],
            [folder_in_github_repo, files_in_github_repo],
        )
    gr.Markdown("### Destination for your migrated dataset")
    gr.Markdown("Destination repository for your dataset on the Hugging Face Hub")
    destination_hf_hub_repository = gr.Textbox(
        label="Destination Hugging Face Repository",
        placeholder="i.e. <hugging face username>/<repository_name>",
    )
    # gr.Markdown("## Authentication")
    # gr.Markdown(
    #     """You need to provide a token with write access to the namespace you want to upload to.
    #             You can generate/access your Hugging FAce token from [here](https://huggingface.co/settings/token)."""
    # )
    # hf_token = gr.Textbox(label="Hugging Face Token", type="password")
    summit_btn = gr.Button("Migrate Dataset")
    result = gr.Markdown(label="Summary", visible=True)
    summit_btn.click(
        push_to_hf,
        [
            source_github_repository,
            destination_hf_hub_repository,
            folder_in_github_repo,
        ],
        [result],
    )
    gr.Markdown(
        """You should add a dataset card for your dataset to help people discover and understand your dataset. You can find instructions for creating a dataset card [here](https://huggingface.co/docs/datasets/dataset_card). 
        If you have any questions or feedback feel free to reach out to us on using the [Discussion tab](https://huggingface.co/spaces/librarian-bots/github-to-huggingface-dataset-migration-tool/discussions/1)"""
    )


demo.launch()